Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Section 1 INTRODUCTION

As required by Section 303(d) of the Federal Clean Water Act, the State of Florida must develop total maximum daily loads (TMDLs) for impaired waters (i.e., do not meet their designated uses). A TMDL is the maximum loading of a particular pollutant that can be discharged in a surface water and still meet its designated uses and applicable water quality standards. However, the term TMDL is also used when referring to the overall process involved in the assessment and restoration of impaired waters. According to Subsection 303(d) of the Clean Water Act (CWA) and Section 403.067, Florida Statutes, impaired waters are “those not meeting applicable water quality standards, a broad term that includes designated uses, water quality criteria, the Florida antidegradation policy, and moderating provisions” (Chapter 62-303, FAC). For each of the impaired waters, where the impairment is due to abatable, human-induced causes, Florida must define the TMDL. Pursuant to United States Environmental Protection Agency (EPA) TMDL regulations, the TMDL is expressed as follows:

TMDL = WLA + LA + MOS

where:

WLA = the Wasteload Allocation for point sources,
LA = a Load Allocation for nonpoint sources including natural background conditions, and
MOS = a margin of safety (implicit or explicit).
TMDLs are usually defined using waterbody-spec ific data, mathematical models and tools that consider the magnitude and fate of pollutants discharged from various sources. TMDL implementation focuses on assessing point source treatment needs or best management practices (BMPs) for nonpoint sources of pollution that can be applied to reduce anthropogenic pollutant loads enough to achieve the water quality standards necessary to meet designated beneficial uses.

The CWA and the TMDL process require amplification and interpretation in the context of the physical environment and regulatory structure in place within the State of Florida. The Florida Department of Environmental Protection (FDEP) has determined that TMDLs should be developed using standard protocols for the following reasons:

 

### The development of a standard approach will identify appropriate methods to comply with the TMDL process and facilitate a technology transfer that will substantially increase the understanding of the complex TMDL process;

 

### A standard process for developing and applying TMDLs will reduce confusion and inappropriate approaches to TMDL implementation in Florida;

1-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Definition of standard practices will improve the consistency of TMDL studies conducted by FDEP staff or by local government agencies;

 

### TMDL studies consistent with application of standard practices will facilitate the comparison of results and extension of data in nearby watersheds;

 

### Standardization will result in more efficient implementation of TMDLs in accordance with the schedule defined in the TMDL Consent Decree between EPA and EarthJustice, while maintaining effective standards in developing those TMDLs; and,

 

### Standardization will reduce costs for practitioners responsible for developing and reviewing the TDML;

 

### A TMDL study conducted using standardized, technically peer-reviewed protocols would be more defensible if challenged in court.

This document presents example standard protocols and references that may be considered for use by practitioners for conducting TMDL analyses and preparing TMDLs. This protocol report has been developed as a modular tool and reference, and includes the following sections (Version 6.0, June 2005):

 

### Section 1 presents the regulatory requirements for TMDLs and Florida’s watershed approach for TMDL implementation, example references, acronyms (Appendix 1A), and the Florida Watershed Restoration Act (Appendix 1B).

 

### Section 2 presents the applicable water quality regulations and targets.

 

### Section 3 presents guidance for data collection and analysis of impaired waters and for model preparation.

 

### Section 4 discusses model selection.

 

### Section 5 defines protocols for model preparation, verification, calibration, and validation.

 

### Section 6 discusses model application.

 

### Section 7 presents treatment alternatives and Best Management Practices.

 

### Section 8 defines example documentation for TMDL analyses.

This document provides and references standard protocols or practices to develop TMDLs for lakes, rivers, streams, and estuaries. The term “water segment” is defined as a portion of a waterbody for which FDEP assesses for a TMDL. The Waterbody Identification (WBID) number is a unique number assigned to each water segment or waterbody and is used to identify the location and extent of water bodies within the state. Each TMDL pertains to only one pollutant affecting a given water quality parameter and/or standard in the water segment or waterbody. A given waterbody or segment may have several TMDLs that address different pollutants (e.g., TN, TP, BOD, and Chl-a effects on DO). Most cases will be

1-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### adequately addressed by these standard practices. Because of specific circumstances and variability, it might be necessary to develop approaches for special or unforeseen cases not considered during the development of this st andard protocol document to develop the TMDL for a given water segment or waterbody. FDEP must approve both the use of any nonstandard techniques used for TMDL development, and the application of such techniques to the water segment in question. After FDEP review and approval, other methods could be added to this protocol at FDEP’s discretion.



# 1.1 REGULATORY BACKGROUND

The TMDL requirements were originally promulgated as a part of the Federal Water Pollution Control Act of 1972 and were later expanded by the Clean Water Act (1977) and the Water Quality Act (1987). The law requires states to define state-specific water quality standards for various designated uses and to identify waterbodies for which the ambient water quality has been determined to not meet established standards (Subsection 303(d)). Waterbodies that do not achieve such water quality standards as a result of human-induced conditions are to be considered impaired. An updated list of impaired waterbodies must be presented by the state to the EPA every two years and must designate which of the listed impaired waterbodies will require implementation of the TMDL process. Florida issued a full 303(d) planning list in 2002 and has been producing basin-specific 303(d) impaired waters lists recently in accordance with the Florida Watershed Restoration Act (FWRA, Chapter 403.067, Florida Statute).

In Florida, the TMDL process is multi-phased and includes the identification, verification, and listing of impaired waters, followed by t he development and implementation of the TMDL. First, FDEP develops a planning list of impai red waters based on existing data. FDEP then prepares a verified list following the collection of additional corroborating water quality, biological, or other data. The verified list is adopted by the FDEP Secretary as the basin specific 303(d) List to be sent to EPA in compliance with the CWA. Once a waterbody is adopted on the verified list of impaired waters, then the next phase of the TMDL process is the development of a TMDL, including the initia l allocation of allowable loads. The next phase of the TMDL process is the development of the Basin Management Action Plan (BMAP), or the TMDL implementation plan, in which detailed allocations of allowable loadings to point and nonpoint sources is done and load reduction strategies are evaluated. The following lists Florida's phased approach:

Phase 1 Data Compilation and Assessment

Phase 2 Collection and Assessment of Additional Data

Phase 3 Determination of Total Maximum Daily Load

Phase 4 Development of Allocation and Basin Management Action Plan (BMAP)

Phase 5 Implementation of the TMDL and BMAP

1-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### This process for the determination of impaired waters is described in the Impaired Water Rule, 62-303 FAC provided in Appendix 2A. In Phase 3, the TMDL is estimated, generally with the use of mathematical models associated with water quantity and quality data and watershed information.

Once the TMDL is defined in Phase 3, the allowable loads are allocated in Phase 4 to point and nonpoint sources. Point sources would include domestic and industrial wastewater and National Pollutant Discharge Elimination Syst em (NPDES) industrial and municipal separate storm sewer systems (MS4s) stormwater disc harges. Nonpoint sources would include septic tanks, agricultural, silvicultural, atmospheric, and natural flora and fauna discharges, as well as legacy sediment effects. One or more implementation plans are then developed to define how each source will be controlled to achieve the allocated load. For contributing pollutant sources under NPDES permits, the allocation will be achieved through permit-specified effluent limitations and load reductions. For other sources, such as agricultural areas thatare not regulated by NPDES permits, load allocations will be achieved through nonregulatory programs based on the implementation of BMPs associated with each agricultural type. In Phase 5, the implementation of the BMAPs are initiated.



# 1.2 WATERSHED APPROACH

FDEP has decided to implement the five phases of the TMDL program described above using a watershed approach (i.e., managing water resources within their natural boundaries). To implement the watershed approach for all water bodies in Florida, FDEP divided each of the six FDEP Districts into five geographically based groups of watersheds. A map of the groups is shown in the inset ( Figure 1.1 ) and a table that lists the groups by basin and district is provided below ( Table 1.1 ). As illustrated in Table 1.2

, the five phases of the State’s TMDL program for each group are completed in annual cycles, starting with Group 1. Figure 1.1



# 1.3 TECHNICAL BACKGROUND

For each TMDL completed under the phased watershed management approach outlined above, a technical analysis of the assimilative capacity of the subject water segment in question may be conducted. The assimilative capacity is the total amount of a pollutant that can be discharged into a water segment without causing use impairment. Thus, the assimilative capacity, as a result, is numerica lly equivalent to that segment’s TMDL with a MOS. To determine the assimilative capacity, the fate of the total loading to a water segment may be compared to water quality criteria and other environmental targets to test for use impairment. Such comparisons are usually done using water quality data and modeling.

1-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

YEAR* 00 01 01 02 02 03 03 04 04 05 05 06 06 07 07 08 08 09 09 10

Group 1 Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 1 Phase 2 Phase 3 Phase 4 Phase 5

Group 2 Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 1 Phase 2 Phase 3 Phase 4

Group 3 Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 1 Phase 2 Phase 3

Group 4 Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 1 Phase 2

Group 5 Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 1

1 st Five-year Cycle – High-Priority Waters 2 nd Five-year Cycle – Medium-Priority Waters

Table 1.1 Watersheds Listed by Group and FDEP District



### DEP District Group 1 Basins Group 2 Basins Group 3 Basins Group 4 Basins Group 5 Basins

NW OchlockoneeSt. Marks ApalachicolaChipola ChoctawhatcheeSt. Andrews Bay 

### Pensacola Bay Perdido Bay

NE Suwannee Lower St. Johns Nassau-St. Marys Upper East Coast

Central Ocklawaha Middle St. Johns Upper St. Johns Kissimmee Indian River Lagoon

SW Tampa Bay Tampa Bay Tributaries Sarasota BayPeace

### Myakka Withlacoochee Springs Coast

S Everglades West Coast Charlotte Harbor Caloosahatchee Fisheating Creek Florida Keys

SE Lake Okeechobee St. LucieLoxahatchee Lake Worth Lagoon- Palm Beach Coast Southeast Coast - Biscayne Bay Everglades

Table 1.2 Schedule of Phases for Each Group



### 1-5Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Figure 1.2 shows the overall flow chart for a standard TMDL study consisting of four elements: Data Acquisition and Assessment; Model Preparation, Verification, Calibration, Validation, and Application; Control Strategies Assessments; and Publication and Data Transfer. Element V will be produced by FDEP and will cover allocation and implementation.

Element I - Data Acquisition and Assessment and Model Selection. During this element, data necessary for the TMDL analysis are acquired (collected) and assessed (analyzed). The first step is the collection and analysis of existing data in conjunction with the assessment of the watershed and/or receiving waterbody. An analysis of the variability of the available data is completed to define and assess the potential portion of TMDL uncertainty attributable to data variability. If the available data are insufficient to apply the model or evaluation tool, then additional data may need to be collected. A variety of models can also be used to analyze a TMDL for a receiving waterbody. An assessment of watershed and receiving waterbody models will generally be performed, and a model (or set of models) may be selected on the basis of this assessment. A watershed model is one that simulates the loadings of pollutant from land surface runoff and groundwater flows into the receiving waters. A receiving waterbody model, or assimilative capacity model, is one that simulates the fate of the pollutant once it reaches the receiving water. It should be noted that the processes of data acquisition, data assessment, and model selection are iterative in nature and, while they are described in series in this document, many of these activities are done in parallel.

Element II - Model Preparation, Verification, Calibration, Validation, and Application. In this second element, the model (or set of models) is prepared, verified, calibrated, and validated (PVCV in figure) and applied to the subject watershed and receiving waters. The model is calibrated using available data to confirm that the model(s) simulate the watershed pollutant load generation and receiving water responses to pollutant loading within a defined uncertainty and/or error. Model verification and validation refer to the processes and techniques that are used to check if the model reasonably matches the specifications and assumptions used in applying the model and reasonably matches measured data for the watershed and/or receiving waterbody. The data and models are applied to calculate the TMDL, uncertainty, and MOS.

Element III - Control Strategies Assessments. Using the verified, calibrated, and validated model(s), design condition and continuous simulations are used to define the total allowable loading for the subject pollutant and the potential sources of the pollutants. In Florida, industrial and domestic WWTP point sources are required to provide a high degree of treatment; therefore, the initial control strategies to be considered may generally pertain to stormwater point and nonpoint sources for most pollutants. To help the development of a TMDL implementation plan, simulations of three potential control strategies may be conducted (FDEP, 2001) as follows:

 

### The first strategy simulates application of BMPs to 45 percent of the land area;

 

### The second strategy simulates application of BMPs to 90 percent; and

1-6Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### The third strategy simulates the results for some intermediate or higher (e.g. >90 percent) participation for all sources depending on the need for pollutant discharge control.

Element IV - Publication and Data Transfer. The data collection, model application and control strategy assessment should be doc umented and made available for review by stakeholders and the public along with the data, model data sets and simulations.

Element V – TMDL Allocation and Implementation. The next step is to allocate and implement the TMDL. FDEP developed the protocol for the allocation and implementation. These data and model results are incorporated into the BMAP process.

Although this is not a simple process for many TMDL assessments, FDEP must produce a significant number of TMDLs to achieve its goals for the watershed approach and also must meet the schedule defined in the TMDL Consent Decree between EPA and EarthJustice. In order to accomplish these difficult tasks in the short period of time available, the elements defined above should be standardized as much as possible.



# 1.4 PURPOSE OF TMDL PROTOCOL DOCUMENT

The purpose of this document is to define standard practices to be considered for use in the State of Florida to guide TMDL analyses and to establish TMDL requirements. Initially, the general elements of TMDL activities will be defined for the majority of watersheds and receiving waters in the State. However, it is recognized that as more TMDL studies are completed, additional protocol components may be added and/or refined based on these experiences. Therefore, this document may need to be updated periodically. Although this document provides protocols for the standard methods of analyzing watersheds and receiving waters, there will likely be exceptions. For this reason, where appropriate, this document defines methods for consideration by FDEP to use for TMDL analyses.
Based on the definition of the elements of a standard TMDL (Section 1.3), the following purposes are defined for this TMDL Protocol:

 

### To define protocols for watershed and receiving water data analysis. While the data for each water segment will be highly variable, the analysis techniques are not and can be standardized. In particular, data analysis techniques are defined to consider pollutants of concern, natural background levels, surrogate parameters, and design conditions.

 

### To define watershed and receiving water model selection, preparation, verification, calibration, validation, and application protocols. Over the last 30 years, a significant number of watershed and receiving water models have been developed. These range from very simple and data-minimal models to very complex, data-intensive models. This protocol document provides a description of the model selection process and describes standard practices for the calibration, verification, and validation of the models, and the application of the models to develop TMDLs and pollutant control strategies.

 

### To define standard documentation protocols. The last set of protocols is related to the documentation and transfer of information to FDEP and the public for review and use during the TMDL implementation process. Standard reports for data assessments and

1-7Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### model application will be addressed, as well as digital data transfers and graphic formats.



# 1.5 TECHNICAL ADVISORY AND REVIEW COMMITTEE (TARC)

This document has been reviewed at two stages of its development by a Technical Advisory Review Committee (TARC) made up of the following:

Melvin W. Anderson, Ph.D., P.E.

Gail B. Boyd

Kenneth L. Campbell, Ph.D., P.E.

Wendy Graham, Ph.D.

Susan Morea

Stephen Nix, Ph.D.

A. Charles Rowney, Ph.D.

Martin Wanielista, Ph.D., P.E.

Gour-Tsyh (George) Yeh, Ph.D., P.E.

Most of the excellent comments from the TARC have been incorporated into this document and this document is envisioned as a living (or dynamic) document which will undergo regular updates and improvements as new data, met hodologies, and technologies become available.



# 1.6 PROTOCOL PREPARATION

This TMDL Protocol was primarily prepared by CDM with support and review by URS and review by the TARC and FAU. Michael F. Schmidt, P.E., DEE served as the chief editor with CDM technical review and guidance provided by John Hartigan, P.E., DEE, Richard Wagner, P.E., Scott McClelland, and Thomas Quasebarth.

1-8Model Developmentand VerificationNotes:1.Preparation, verification, calibration, and validation (PVCV)2.Uncertainty and sensitivityanalysis are conducted with calibration and validation.3.Diamonds ( ) are provided for general sequence and locational reference within theflow chart.4.Data TMDLs may result from adequate longterm flow and water quality data inElement I.PVCV ofCurrent ConditionsReceiving WaterModel1Definition ofThree ControlStrategies andBMP ParticipationOptionsTMDL ReportPrepare the DraftTMDL ReportProtocol to Allocateand ImplementTMDLFinalize theDraft TMDLReportTMDL ReportProceed toElement IVDataAdequatefor TMDLUse ExistingNoYesCurrent ConditionsReceiving WaterModel, TMDL,Uncertainty, andRecommendationsElement VYesWBID DataYesClarification/Liaison/StatusMeetingClarification/Liaison/StatusMeetingClarification/Liaison/StatusMeetingClarification/Liaison/StatusMeetingNoElement IData Acquisition and AssessmentRevised: 6/17/2005Update theWBID DatasetFDEPAcceptanceReviewCommentsTARCReview7Figure 1.2 TMDL PROCESSElement IVPublication and Data TransferElement IIIControl Strategies AssessmentElement IIAssessment ofInitial WBIDData SetDevelopmentOf InitialWBID DataPacketSupplementalData Collection orMonitoring forWBIDUncertaintyAnalysis andData NeedsforSelected ModelAnticipatedUncertainty ofTMDLTech MemoAssessment ofWatershed andReceivingWater ModelsWatershed andReceiving WaterModelRecommendationsTech MemoPVCV ofCurrent ConditionsWatershed Model1FDEPAcceptanceNoTARCReviewSummary ofControl StrategiesTech MemoAssessment of theThree AcceptedControl StrategiesFDEPAcceptanceNoFDEPAcceptanceNoYesCurrent ConditionsWatershed ModelTech MemoYesPotential Benefitsof ProposedControl StrategiesTech MemoDraft ReportYesIndependentTechnicalReviewFinal ReportFDEPAcceptanceNoDuplication andDistribution of the FinalTMDL ReportYesTransfer of FinalElectronic Files andDocumentationData Adequacyand SupplementalCollection NeedsTech MemoSupplementalData CollectionReviewCommentsReviewCommentsTMDL ModelingTech MemoRefinement ofTMDL ObjectivesDefinition ofConditionsRestatement ofTMDL ModelingObjectivesTech MemoTARCReviewReviewCommentsProjectKick-OffMeetingIssuance ofNotice toProceed forPhased WorkOrderProject Start12345869101112131614151718192021242223YesTech MemoCommenceNo8FDEPDecision:AdequateData?FDEPDecision:AdequateData?YesNoCollectSupplementalDataModel Preparation,Verification,Calibration and ValidationDesign andSimulationDesign andSimulationConditionsFlorida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# SECTION 1 REFERENCES

Cleland, B. Date unknown. “Observations on Technical Achievability in TMDL Development.” From TMDLs.net, TMDL Circuit Rider Program.

One method to develop a TMDL and to provide for technical achievability by the stakeholders in a watershed is a “bottom up” approach, which is developed by the definition of BMPs by affected parties in the watershed. The bottom up approach takes advantage of already established jurisdictional agreements across city and county boundaries to provide achievable improvements which build up to a successful recovery of an impaired water segment. To address nonpoint sources, the article supports a flow-duration and/or load duration approach as a targeting tool set that is supported by adaptive management.

EPA. 1999. “Protocol for Developing Nutrient TMDLs (First Edition).” EPA 841-B-99-007, Office of Wetlands, Oceans, and Watersheds.

This is a technical guidance produced by EPA to help states, tribes and others develop TMDLs for nutrients (primarily, nitrogen and phosphorus. The document provides methods to identify target values, to assess sources, to identify links between targets and sources, to allocate resultant loads, to develop follow-up monitoring and evaluation and to assemble the TMDL document.

EPA, 1999. “Draft Guidance for Water Quality-based Decisions: The TMDL Process (Second Edition).” EPA841-D-99-001, Office of Water.

This is a technical guidance produced by EPA to help states, tribes and others to prepare proper documentation for the establishment and implementation of a TMDL. An overall discussion of the TMDL regulatory process is included as well as the 303(d) listing protocols and submittal requirements.

EPA Region 9. January 7, 2000. “Guidance for Developing TMDLs in California.”

The guidance describes the minimum federal requirements for developing and establishing TMDLs in California. The guidance is tailored to California’s unique legal and administrative processes and is based on the federal and state requirements for TMDLs as of January 2000. Provided in the document are minimum elements required for TMDLs, descriptions of the steps necessary to develop a TMDL and a TMDL review checklist.

EPA. 2002. “The Twenty Needs Report: How Res earch Can Improve the TMDL Program.”

EPA, Region 10, 2002. “TMDL Review Guidelines.”

Florida Administrative Code. Impaired Waters Rule. Chapter 62-303.

1-10Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Florida Statutes. Florida Air and Water Pollution Control Act. Section 403.

Florida Statutes. 1999. Florida Watershed Restoration Act.

Idaho Division of Environmental Quality, 1999. “State of Idaho Guidance for Development of Total Maximum Daily Loads.”

Indiana Department of Environmental Management, January 2003. “TMDL Strategy (Guidelines for TMDL Development)”. IDEM 32/01/003/2003.

This document defines the strategy to complete TMDLs within Indiana. The document includes staffing and resources, definition of an Advisory Group, TMDL development schedule, and discussion of the interaction with EPA as well as the technical programs for the TMDL. The TMDL process includes three phases: Planning and sampling; TMDL development and stakeholder outreach; and TMDP implementation plan.

Poole, W. Date Unknown. “Uncertainty and Adaptive Management.” From TMDLs.net, TMDL Circuit Rider Program.

Uncertainty is a part of every TMDL, no matter how much data have been collected or modeling analysis completed. To address this uncertainty, Dr. Poole stresses the need for adaptive management as a strategy for th e implementation of TMDLs. Adaptive management is a means by which adjustm ents to the watershed management plan are made as new data or analysis refines the strategy. To be successful, Dr. Poole notes that the process must be built in to the start of the implementation program, identify goals to be checked periodically, and monitoring performed to check movement toward the goals.

Texas Natural Resource Conservation Commission and US Environmental Protection Agency. 1999. “Developing Total Maximum Daily Load Projects in Texas: A Guide for Lead Organizations.” Austin, TX.

Prepared by the Texas Natural Resource Conservation Commission (TNRCC), this document provides the approach to be used by consultants and governments in the state of Texas for TMDLs. The document describes methods for determining the pollutant targets, data sources, modeling techniques, public participation, quality assurance, and documentation.

Virginia Department of Environmental Quality, 2000. “Total Maximum Daily Load Program: A Ten Year Implementation Plan.”

  

1-11Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## APPENDIX 1A

ACRONYMS AND ABBREVIATIONS

AC Atypical Coliform Bacteria

BASINS Better Assessment Science Integrating Point and Nonpoint Sources

BMAP Basin Management Action Plan

BMPs Best Management Practices

BOD Biochemical Oxygen Demand

BPJ Best Professional Judgment

C/L/S Clarification/Liaison/Status

CAFO Concentrated Animal Feeding Operation

CBOD Carbonaceous Biochemical Oxygen Demand

CDM Camp Dresser & McKee Inc.

CDS Continuous Deflection Unit

CES Center For Environmental Studies

CFR Code of Federal Regulations

cfs cubic feet per second

CGP Construction General Permit

Chl-a Chlorophyll a

CO-OPS Center for Operational Oceanographic Products and Services

CWA Clean Water Act

DCIA Directly Connected Impervious Area

DEM Digital Elevation Model or Map

DMR Discharge Monitoring Report

1-12Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### DO Dissolved Oxygen

EFDC Environmental Fluid Dynamics Computer Code

EMC Event Mean Concentration

EPA Environmental Protection Agency

ERP Environmental Resource Permit

ET Evapotranspiration

FAC Florida Administrative Code

FAU Florida Atlantic University

FC Fecal Coliform Bacteria

FDACS Florida Department of Agriculture and Consumer Affairs

FDEP Florida Department of Environmental Protection

FDOH Florida Department of Health

FLUCCS Florida Land Use and Cover Classification System

FS Florida Statutes

FTP File Transfer Protocol

FWRA Florida Watershed Restoration Act

GIS Geographical Information System

GP General Permit

GPS Global Positioning System

GUI Graphical User Interface'

HEC Hydrologic Engineering Center

HEC-RAS HEC River Analysis System

HSG Hydrologic Soil Groups

HSPF Hydrological Simulation Program - FORTRAN

1-13Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### HUC Hydrologic Unit Code

ID Identification

IFAS Institute of Food and Agricultural Services

IWR Impaired Waters Rule

K-S Kolmogorov-Smirnov

LA Load Allocation

LCI Lake Condition Index

MEP Maximum Extent Practicable

mg/l Milligrams per liter (also parts per million - ppm)

MGD Million Gallons per Day

MIA Marine Industries Association of Florida

MOS Margin of Safety

MS4 Municipal Separate Storm Sewer System

MSGP Multi-Sector General Permit

NAVD North American Vertical Datum 1988

NAWQA National Water Quality Assessment

NCDC National Climatic Data Center

NEP National Estuary Program

NGDC National Geophysical Data Center

NGVD National Geodetic Vertical Datum 1929

NO2 + NO3 Nitrite + Nitrate

NOAA National Oceanic and Atmospheric Administration

NOD Nitrogenous Oxygen Demand

NPDES National Pollutant Discharge Elimination System

1-14Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### NPS Nonpoint Source

NPSM Nonpoint Source Model

NRCS National Resource Conservation Service

NSIP USGS National Streamflow Information Program

NTU Nephlemetric Turbidity Units

NWFWMD Northwest Florida Water Management District

NWS National Weather Service

O&M Operation and Maintenance

OFW Outstanding Florida Waters

P8 Program for Predicting Pollution Particle Passage through Pits, Puddles and Ponds

PCS Permit Compliance System

PCU Platinum-Cobalt Units

PO4 Orthophosphate

PS Point Source

RMS Root Mean Square

SCI Stream Condition Index

SFWMD South Florida Water Management District

SJRWMD St Johns River Water Management District

SLAMM Source Loading and Management Model

SOD Sediment Oxygen Demand

SOP Standard Operating Protocol or Procedure

SRWMD Suwannee River Water Management District

SSO Sanitary Sewer Overflow

1-15Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### STORET EPA or FDEP STOrage and RETrieval Program

SW Stormwater

SWAT Soil and Water Assessment Tool

SWFWMD Southwest Florida Water Management District

SWMM Storm Water Management Model

TARC Technical Advisory and Review Committee

TBNEP Tampa Bay National Estuarine Program

TKN Total Kjeldahl Nitrogen

TMDL Total Maximum Daily Load

TN Total Nitrogen

TP Total Phosphorus

TSI Trophic State Index

TSS Total Suspended Solids

UAA Use Attainability Analysis

ug/l Micrograms per liter (also parts per billion - ppb)

USACE United States Army Corps of Engineers

USDA United States Department of Agriculture

USGS United States Geological Survey

WAM Watershed Assessment Model

WASP Water Quality Analysis Simulation Program

WBID Water Body Identification

WERF Water Environment Research Foundation

WLA Waste Load Allocation

WMM Watershed Management Model

1-16Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### WQBEL Water Quality Based Effluent Limit

WWW World Wide Web

1-17Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Section 2 WATER QUALITY STANDARDS AND TARGETS

A TMDL is the maximum loading of a pollutant allowed to a water segment that will not cause an impairment of the water segment. The Federal Clean Water Act (CWA) requires states to identify water segments that are impaired, to develop TMDLs that define the maximum loading allowed, and to implement pr ograms to control discharges by reducing pollutant loads to levels that will eliminate the impairment. A major key in the TMDL program is clear and consistent definition of conditions that result in the impairment of designated beneficial uses. Discussed in more detail later in this section, the State of Florida defines impairment as follows in the Impaired Water Rule (Rule 62-303, Florida Administrative Code, or FAC, as shown in Appendix 2A ):

“Subsection 303(d) of the CWA and section 403.067, F.S. describe impaired waters as those not meeting applicable water quality standards, which is a broad term that includes designated uses, water quality criteria, the Florida antidegradation policy and moderating provisions. However, as recognized when the water quality standards were adopted, many water bodies naturally do not meet one or more established water quality criteria at all times, even though they meet their designated uses.” [Rule 62-303.100(2)]

Accordingly, the purpose of this section of the TMDL Development Protocol is to identify the water quality standards which the TMDL analyst will use as a benchmark when making TMDL decisions. Water quality standards consist of designated uses (discussed below), water quality criteria, antidegradation policies and moderating provisions (e.g., mixing zones, site specific alternative criteria, etc.).



# 2.1 DESIGNATED USES

Water quality criteria (generally numerical limits for various pollution related parameters that, if exceeded, indicate an undesirable environmental condition) vary depending on the designated beneficial uses of the given water body . For example, a water segment that is used for swimming requires higher water quality than a water segment that is used to receive industrial discharges. The Clean Water Act authorizes states to define water quality criteria that vary depending on the water uses designated by the state. In Florida, the term “designated use” is defined as “the present and future most beneficial use of a body of water as designated by the Environmental Regulation Co mmission by means of the classification system...” [Rule 62-302.200(8), FAC]. Rule 62-302.400, FAC, defines the allowable classes within Florida. Generally, Class I waters have more stringent criteria than Class V:

Class I Potable Water Supplies

Class II Shellfish Propagation or Harvesting

2-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Class III Recreation, Propagation and Maintenance of a Healthy, WellBalanced Population of Fish and Wildlife

Class IV Agricultural Water Supplies

Class V Navigation, Utility and Industrial Use (No Florida waters are currently listed as Class V)

Rule 62-302.400(10), FAC, states that all surface waters of Florida are classified as Class III unless otherwise defined in the rule. Furthermore, this subsection notes that a Class I, II, or III water body also may be designated as Outstanding Florida Waters (OFW, see below).

As an illustration, Figure 2.1 shows Outstanding Florida Waters (OFW) as defined by Rule 62-302, FAC. Example areas include the Everglades and Florida Keys, estuaries along the west coast from Charlotte Harbor up to the Panhandle to Pensacola Bay. To confirm the class of a particular water segment, reference Rule 62- 302.

Waters within Classes I, II and III can be further designated as OFWs to which the highest protection is to be afforded. In particular, “no degradation of water quality ... is to be permitted” [Rule 62-302.700(1)] except as authorized by Rule 62-4.242(2), FAC. Under this rule, requirements for discharge directly to, or which significantly degrades, an OFW include that

 

### the proposed discharge or activity is “clearly in the public interest” and

 

### either a permit was issued to the discharge prior to the OFW designation or the existing ambient water quality will not be lowered outside of a mixing zone.

Additional conditions for discharge to OFWs are provided in Rule 62-4.242(2).



# 2.2 APPLICABLE WATER QUALITY STANDARDS

In this section, water quality criteria, antidegradation policies and moderating provisions are discussed as they pertain to TMDL studies.

In consideration of these water quality standards, the following findings noted in Rule 62,302.300, FAC, are of particular importance:

2-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Subsection (15) states that “pollution that causes or contributes to new violations of water quality standards or to continuation of existing violations is harmful to the waters of this State and shall not be allowed.” This is the criterion by which most TMDL analyses will be conducted.

 

### Subsection (15) also states that “the Department shall not strive to abate natural conditions.” Therefore, each TMDL analysis needs to consider natural background conditions.

 

### Subsection (13) highlights excessive nutrients (e.g., total nitrogen and total phosphorus) as “one of the most severe water quality problems facing the State.” The current nutrient criteria are narrative, and specific TMDL analyses must therefore be related to other criteria (e.g., turbidity or light attenuation) or to resource targets (see Section 2.3 below).



## 2.2.1 Minimum Conditions
State regulations define the minimum conditions for all surface waters in the state. These regulations (which are referred to as the “free froms”) require that, at all places and times, such waters must be free from man-induced, non-thermal discharges containing pollutants that alone or in combination:

 

### Settle to form putrescent or nuisance deposits;

 

### Floating debris in such amounts to be a nuisance;

 

### Produce color, odor, turbidity or other conditions to be a nuisance;

 

### Are acutely toxic;

 

### Are in carcinogenic, mutagenic or teratogenic concentrations to humans or significant, local wildlife; or,

 

### Pose a serious danger to public health, safety and welfare. [Rule 62-302.500(1)]

Thermal discharges are also regulated with one minimum condition: that they do not produce nuisance conditions.
For typical TMDL analyses, minimum conditions are generally not assessed through the TMDL process because these conditions are not usually the source of designated use impairment and if found in a water segment, are the impetus to specific, local enforcement and action. However, where a mixing zone is applicable or where health related pollutants are discharged, both the toxic condition and the carcinogenic, mutagenic and teratogenic conditions must be considered. Mixing zones are discussed later in this section. Thermal effects, on the other hand, are not only highly significant in regulating water quality conditions and therefore assimilative capacity, but are very amenable to explicit measurement and analysis.

2-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## 2.2.2 Water Quality Criteria
Water quality criteria are generally numeric ally-stated concentrations of chemical constituents or measurable levels of physical conditions. However, water quality criteria can also be expressed as narrative statements that qualitatively describe water quality required to support existing or future beneficial uses. The water quality criteria listed in Rule 62-530, FAC, apply depending on the use classification except for mixing zones (see below) and waters for which relief has been granted by FDEP. Rule 62-302.500(2) also states that an exception to the water quality criteria includes the provisions of Section 403.061(7), F.S., which states that “Rules... shall not require discharges of waste into waters of the state to improve natural background conditions.” Appendix 2B provides the table of non-thermal, water quality criteria associated with this rule. It should be noted that Rule 62-302.500(2)(e), FAC, states that the “numeric criteria are based on annual average flow conditions” unless listed otherwise in Rule 62-530, FAC.
Where thermal pollution is a potential problem, the criteria listed in Rule 62-302.520, FAC, apply. This rule requires all existing or proposed discharges of heated water be assessed through a thorough study of the consequences of the heated discharge. This means that, for TMDL purposes, most point source thermal discharges (e.g., the cooling water discharges from power plants) already have been assessed by significant studies that can be used for establishing site-specific TMDL limitations for thermal discharges. More difficult to consider are the thermal discharges associated with industrial wastewater and urban stormwater. Where potential stress could be caused by such thermal discharges, Rule 62-302.520, FAC, must be consulted.

Finally, some of the criteria are related to “natural background.” Rule 62-302.200, FAC, defines natural background to be “the condition of waters in the absence of man-induced alterations based on the best scientific information available to the Department.” Furthermore, the definition of natural background for a water segment may be based on “a similar unaltered water body or on historical pre-alteration data.”



## 2.2.3 Moderating Provisions
Associated with the designated uses and water quality criteria are the moderating provisions included as part of the water quality standards to provide “an even-handed and balanced approach to attainment of water quality objectives” [Rule 62-302.300(10)(c)]. Moderating provisions include “mixing zone, zone of discharge, site-specific alternative criteria, exemption, and equitable allocation.” These provisions are discussed below.

Mixing Zones or Zones of Mixing . A mixing zone is defined by Rule 62-302.200(30) as “a volume of surface water containing the point or area of discharge and within which an opportunity for the mixture of wastes with the receiving waters has been afforded.” Rule 62- 4.244 considers mixing zones further by authorizing water quality in a mixing zone to be degraded below applicable class criteria but no worse than the minimum conditions or “free froms” specified under Rule 62-302.500(1). A mixing zone may not, by itself or in combination with others, cause significant impairment of the designated use of the water segment [Rule 62-4.244(1)(a)]. A mixing zone must meet the following provisions:

2-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### It can not include an existing drinking water supply intake if the constituents in the zone would impair the use;

 

### It can not include a nursery or area approved by FDEP for shellfish harvesting;

 

### In canals, rivers, and streams, the maximum length of a mixing zone may not exceed 800 meters (approximately 0.5 miles). The length of the zone is from the point of discharge to the point of complete mixing with the ambient waters.

 

### In lakes estuaries, bays, lagoons and other coastal waters, the area of the mixing zone “shall be 125,600 square meters (about 31 acres) unless a lesser area is necessary to prevent significant impairment of a designated use.”

 

### In open ocean waters, the mixing zone “shall be 502,655 square meters” (approximately 124 acres) unless a smaller area is needed.

 

### Cumulatively, mixing zones may not exceed 10 percent of the total length of a stream, river, canal or tributary or 10 percent of the area of a lake, estuary, bay, lagoon, bayou or sound.

 

### Within a mixing zone, besides the minimum conditions requirements, dissolved oxygen can not average less than 4.0 mg/l, and turbidity may not average more than 41 NTUs above natural background.

Additional mixing zone limitations related to toxicity are provided in Rule 62-4.244(3).
Site-Specific Alternative Criteria. The State regulations recognize that, due to “natural conditions or man-induced conditions that cannot be controlled or abated”, a water segment may not meet the applicable water quality criteria [Rule 62-302.800, FAC]. “Man-induced conditions that cannot be controlled or abated” means “conditions influenced by human activities” that “would remain after removal of the point sources; would remain after imposition of [BMPs] for non-point sources; and cannot be restored or abated by physical alteration of the water body, or there is no reasonable relationship between the economic, social and environmental costs and the benefits of restoration or physical alteration.” Under these circumstances, an “affected person” or FDEP itself may petition the Secretary of FDEP to establish a site-specific alternative criterion based upon an “affirmative demonstration” that the alternative criterion is more appropriate. The demonstration must show that the condition is due to natural conditions or man-induced conditions that cannot be controlled or abated.

According to Rule 62-302.800((4)(d), this provision does not apply to the “free froms” or to criteria that are related to the following parameters:
Bacteriological quality Oils and grease
Biological integrity Radioactive substances
BOD Specific Conductance
Chlorides Substances that injure or are chronically toxic

2-5Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Color Substances causing dominance of nuisance species
Detergents Total dissolved gases
Dissolved Oxygen Transparency
Dissolved Solids Turbidity
Nutrients Minimum mixing zone parameters

Odor
Rule 62-302.500(2)(f) does allow for the alteration of Dissolved Oxygen (DO) levels through alternative DO criteria that are based on conditions attributable to natural background or man-induced conditions which cannot be controlled or abated. The site-specific criteria may not allow a lowering of DO levels in the segment, and daily and seasonal fluctuations must be maintained.

Exemptions. Rule 62-4.243 defines two exemptions that allow water segments to not achieve certain applicable water quality criteria. The first is for artificial water bodies that are classified as agricultural water supplies. The exemption applies to Class IV waters only and applies only for the duration of a permit issued by FDEP. The second is for water segments classified for “Navigation, Utility and Industrial Use.” This exemption is for Class V waters only and as above applies only for the duration of a permit issued by FDEP. Both exemptions require a petition to and approval by FDEP.

Equitable Abatement. Rule 62-4.242(4) provides additional state policy for waters “whose quality has been artificially lowered below the quality to support their designated uses.” Under these conditions, FDEP cannot issue permits unless the permit applicant “affirmatively demonstrates” that water quality standards once achieved would not be violated due to the proposed activity, the activity is “necessary or desirable under federal standards,” and the activity is in the public interest. Furthermore, to equitably allocate the abatement responsibility, the applicant is required to petition FDEP to instigate an equitable allocation process by 1) identifying the contributing sources and 2) quantifying the total contribution and individual contributions of each source. FDEP is then to consider previously completed abatement programs for the water segment, the costs of alternative abatement techniques and the economic impacts of additi onal abatement on the contributing sources.



# 2.3 WATER QUALITY TARGETS

Some Florida water quality criteria are narrative (rather than numerical) or are related to a biological or natural condition. Under these circumstances, the TMDL analysis must focus on water quality targets. Water quality targets are surrogate criteria or parameters, the violation of which would constitute impairment of the designated use.

For example, a surrogate may be needed for the narrative nutrients criterion that states, “in no case shall nutrient concentrations of a body of water be altered so as to cause an imbalance in natural populations of aquatic flora and fauna” [Rule 62-302.530(48)(b)]. Another example pertains to Biochemical Oxygen Demand (BOD). While BOD is a pollutant that reduces the oxygen dissolved in water, there are no specific criteria for BOD in the State regulations. In this case, the criteria itself identifies the target, dissolved oxygen.

2-6Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## 2.3.1 Nutrients
Nutrient enrichment is considered to be one of the primary water quality problems facing Florida water bodies based on previous water quality assessments. TMDLs to establish allowable nutrient loadings may consider water quality targets. FDEP is currently working on a set of numerical nutrient criteria, and the associated regulations are expected to be available by the end of 2006. In the interim, the following are examples of surrogate parameters which can be used to address the narrative criteria for nutrients:

 

### For rivers, lakes and estuaries, chlorophyll ‘a’ concentrations can be directly related to algal biomass, which in turn is a measure of nutrient enrichment. In general, the higher the chlorophyll ‘a’ concentration, the more potential for unnatural alterations to the “natural populations of aquatic flora and fauna.” For TMDL purposes, chlorophyll ‘a’ concentrations may be used as a surrogate water quality target for nutrients.

 

### In estuaries, the relative health and coverage of grass beds represent examples of surrogate measures of nutrient enrichment. For example, for the Tampa Bay National Estuary Program (NEP), research (TBNEP, 1999) has shown that the protected resource in the bay system is grass beds. Since grass beds provide spawning areas for juvenile fishes and are a general indication of the health of Tampa Bay, increasing the coverage of submerged grass beds became the target of recovery. Further studies have shown that nitrogen discharges induced excessive algae growth, which in turn reduced the light penetration from the water surface to the bottom of the Bay (as measured by Secchi disk depth). The studies also showed that the grass beds could potentiallyrecover by increasing light penetration. Therefore, for Tampa Bay NEP, the resourcebased criteria (i.e., criteria based on the protection or enhancement of a definedresource) were related to the control of nitrogen. For estuaries, then, similar resourcebased criteria may be defined for nutrient control.



## 2.3.2 Background Conditions
A number of water quality criteria defined in Rule 62-302, FAC, are based on concentrations above either “background” or “natural background.” Rule 62-302.200 FAC defines both conditions:
“(3) ‘Background’ shall mean the condition of waters in the absence of the activity or discharge under consideration, based on the best scientific information available to the Department.”
“(14) ‘Natural Background’ shall mean the conditions of waters in the absence of man-induced alterations based on the best scientific information available to the Department. The establishment of natural background for an altered waterbody may be based upon a similar unaltered waterbody or on historical pre-alteration data.
The parameters biological integrity, chlorides, and specific conductance are related to “background” levels (e.g., “the index for benthic macroinvertibrates shall not be reduced to less than 75% of background levels”). The parameters pH, transparency and turbidity are also related to “natural background” (e.g., “[pH] shall not vary more then one unit above or below natural background”).

2-7Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Since TMDL load allocations must consider both nonpoint sources and natural conditions, an assessment of background conditions must be conducted. Where only “background” conditions are needed, the analysis may use long-term water quality monitoring data collected from a sampling station located upstream, if that station is not affected by any point or nonpoint source discharges. For “natural background”, the analysis needs to consider water quality conditions that would exist in the absence of any man-induced discharges to the water segment. Methods to evaluate these conditions are provided in Section 3 (Data Collection and Analysis) and Section 5 (Model Preparation, Verification, Calibration, and Validation).



# 2.4 IMPAIRED WATERS RULE

In Florida, a TMDL study is required when a water segment is determined to be impaired. This process has been legislatively defined by the Florida Watershed Restoration Act (Appendix 1B), and regulations have been promulgated under the Impaired Waters Rule (IWR) 62-303, FAC. Provided below is a description of the important elements of the rule. The rule defines methods to identify water segments requiring a TMDL. The rule is presented here to help the TMDL analyst understand the reasons for the listing of a particular water segment.

The two-step process for the listing of impaired waters is based on the Florida Watershed Restoration Act (Chapter 4.3.067, FS). The first step involves developing an initial “planning list” that names potentially impaired waters based on existing impairment related data. The second step involves developing a focused list of “verified” impaired waters based on additional data. It is this latter list that is adopted by the FDEP Secretary and constitutes the required 303(d) list. TMDL studies must be conducted for the waters on the verified list. Rule 62-303, FAC, describes the methods by which the State is to prepare the planning and verified lists as well as methods to delist water segments. The process for listing and delisting is summarized below.



## 2.4.1 Planning List
The planning list delineates the surface water bodies (or segments) for which additional assessments will be conducted to evaluate whet her the water is impaired and a TMDL is needed, as required under subsection 403.067(2), F.S. A water segment is placed on the planning list if it is found not to meet the minimum criteria (“free froms”), designated uses, or water quality standards [Rule 62-303.300(1)]. Specific requirements are described in separate sections of the rule for each of the following designated uses: aquatic life support, primary contact and recreation, fish and shellfish consumption, and drinking water and protection of human health. The requirements are summarized below.

Aquatic Life Support . Water segments are placed on the planning list related to aquatic life support (Classes I, II and III) if the segment:

 

### Exceeds the water quality criteria appropriate to the classification . This is based on a statistical inference that 10 percent of the samples for the parameter exceed the criteria with an 80 percent statistical confidence. The EPA STOrage and RETrieval (STORET) database is the primary data source for this inference. Data from the last 10 years are to be used; however, more recent data may take precedence if a significant change in

2-8Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### water quality is indicated and the older data do not meet data quality requirements. A minimum of 10, temporally independent (1 week interval) samples within the 10-year period are needed for this assessment. Data collected from monitoring locations within 200 meters of each other are considered to be from the same station unless there is an intervening tributary or outfall or significant change in hydrography. Sample data must be available for three of the four seasons for a calendar year as defined in the impaired waters rule.

 

### Does not meet biological assessment thresholds . Bioassessments for the purposes of this rule include biological reconnaissance (BioRecons), Stream Condition Indices (SCIs) and the benthic macroinvertebrate component of the Lake Condition Index (LCI). Water segments that fail one or more bioassessment or biological integrity criteria are placed on the planning list. For this rule, “failure” means a poor or very poor rating on the bioassessment.

 

### Is acutely or chronically toxic . Waters with two samples (taken at least 2 weeks apart) indicating acute or chronic toxicity in a 12-month period will be placed on the planning list.

 

### Exceeds nutrient thresholds . To assess impairment due to nutrients in aquatic life supporting segments, trophic state indices (TSIs) and annual mean chlorophyll ‘a’ values may be used as surrogates. Other indicators such as algal blooms, excessive macrophyte growth, decrease in seagrass distribution (density or areal extent), changes in algal species richness and excessive diel oxygen ranges may also be considered. A stream segment is placed on the planning list if algal mats are present in quantities sufficient to produce a nuisance, the annual mean chlorophyll ‘a’ concentration is greater than 20 μg/l, or the annual mean chlorophyll ‘a’ concentration increases by more than 50 percent over historical values for at least two consecutive years. Lakes are placed on the planning list if the TSI exceeds 60 for lakes with color greater than 40 platinum-cobalt
units ( PCU); the TSI exceeds 40 for lakes with color less than or equal to 40 PCU; or for any lake, the annual mean TSIs have increased by more than 10 units over historical values. The TSI targets can be increased if paleolimnological data exist indicating historically higher TSI data. Finally, estuaries are placed on the planning list if the annual mean chlorophyll ‘a’ for any year exceeds 11 μg/l or if the annual mean chlorophyll ‘a’ has increased by 50 percent over historical values for at least two consecutive years.

Primary Contact and Recreation Use Support. Water segments in Class I, II or III are placed on the planning list if:

 

### The segment does not satisfy applicable water quality criteria for bacteriological quality.

 

### The segment includes bathing areas that were closed by a local health department for more than one week or more than once over a year due to bacteriological data.

 

### The segment included bathing areas for which closures, advisories or warnings were issued by a local health department for 21 days or more during a calendar year based on bacteriological data.

2-9Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### The segment includes bathing areas that were closed or had advisories or warnings for more than 12 weeks of a calendar year based on previous bacteriological data or derived relationships between bacteria levels and flow or rainfall.

Closures, warnings and advisories due to non-chronic events such as red tide, rip tides, spills, sharks, hurricanes or other factors not related to pollutant discharges are not used to identify water segments for the planning list.
Fish and Shellfish Consumption Use Support. Class I, II or III water segments are placed on the planning list if:

 

### The segment does not satisfy applicable Class II criteria for bacteriological quality.

 

### There is either a “limited consumption” or “no consumption” advisory issued by an authorized agency.

 

### The segment includes a Class III water body that, although once approved for harvesting at some previous time has since been downgr aded to a more restrictive classification. Downgrading from “restricted” to “unclass ified” does not constitute impairment.

Drinking Water Use Support and Protection of Human Health. A Class I water segment is placed on the planning list if:

 

### The segment does not satisfy applicable Class I water quality criteria.

 

### A public water system demonstrates that tr eatment costs have increased by 25 percent or more to treat contaminants or algae in the source water or has changed to an alternative water supply because of the treatment costs of the original source.

 

### The water segment does not satisfy applicable human health-based criteria expressed as maximums.

 

### The water segment has average annual water quality that does not satisfy the annual average human health-based criteria.



## 2.4.2 Verified List
The verified list identifies the impaired water bodies or segments for which TMDLs will be calculated, as provided in subsection 403.067(4), F.S., and which will be submitted to EPA pursuant to paragraph 303(d)(1) of the CWA. The verified list is a subset of the planning list. After the planning list is prepared, additional data are compiled to further assess the identified waters leading to the verified list. Except for data used for historical comparisons, only the most recent 7.5 years of data are to be used for the verified list assessment. Similar to the planning list, the requirements for placing a water segment on the verified list depend on the designated uses as discussed below.
Aquatic Life Support. A water segment on the planning list is placed on the verified list if the segment:

 

### Exceeds the water quality criteria appropriate to the classification . For the verified list, FDEP must re-examine the data used for the planning list augmented with newer data

2-10Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### collected by FDEP or other local agencies. If the exceedances are not a result of pollutant discharges and are related to either physical alterations that cannot be abated or to natural background, the segment will not be placed on the verified list. If less than 20 samples were used to put the segment on the planning list, additional samples must first be collected in order to have at least 20 samples for the assessment. As with the planning list, if the water segment exceeds the applicable water quality criteria for the classification, it will be placed on the verified list. This is based on a statistical inference that 10 percent of the samples for the parameter exceed the criteria with a 90 percent statistical confidence. Data from the prec eding 5 years are used for this assessment. If worst-case data were used to place the segment on the planning list (i.e., the worst data were used from a common site collected within a small window of time), the FDEP must re-evaluate the validity of these data.

 

### Does not meet biological assessment thresholds . Water segments that fail two or more bioassessment or biological integrity criteria within five years preceding listing on the planning list are placed on the verified list. For this rule, “failure” means a “poor” or “very poor” rating on the bioassessment. If there were less than two bioassessments during the preceding five years, then additional bioassessments must be conducted. If other indicators of biological impairment are used to place the segment on the planning list, then additional bioassessments of the segment must be conducted. Failure of the new bioassessments provides confirmation that the segment must be placed on the verified list. However, the pollutant causing the failed bioassessment must be identified before the water body can be included on the verified list.

 

### Is acutely or chronically toxic . Water segments are placed on the verified list if acute toxicity data were the basis for placing the segments on the planning list, or if chronic toxicity data were used, the impairment is confirmed by a failed bioassessment completed within 6 months of chronic toxicity data. Toxicity due to spills, upsets, bypasses or rainfall in excess of the 25-year, 24-hour storm event are to be excluded from the assessment.

 

### Exceeds nutrient thresholds . If the data used to place the segment on the planning list were collected during the last 5 years, along with historical data that were sufficient to meet the data sufficiency requirements of the planning list rules related to nutrients, then the segment will be placed on the verified list. If the data are not sufficient, sufficient additional data must be collected and a re-evaluation is required. Data collected for the 5 years prior to the planning list assessment are to be used for the verified list
assessment.

Primary Contact and Recreation Use Support. Water segments in Class I, II or III are placed on the verified list if it is verified that the local closures, warnings or advisories have been due to chronic pollutant discharges (e.g., not red tides, storms). After re-evaluation of the dataset that excludes non-discharge related closures, the segment will be placed on the verified list if it still meets the criteria identified for the planning list. If the segment was placed on the planning list due to exceedances of the bacteriological criteria, the source of the contamination will be evaluated to confirm that the source is not natural background (i.e., bacteria sources are sanitary sewer leakage, septic tank seepage, or domestic animals).

2-11Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Fish and Shellfish Consumption Use Support. For the verified list, fish consumption data for the segment are re-evaluated to confirm that the fish consumption advisories were based on evaluation of fish tissue from at least 12 fish, the data were collected according to FDEP standard practices, and there are sufficient data within 7.5 years of placing the water body on the planning list. If each of these conditions is confirmed, the water segment is placed on the verified list.

Drinking Water Use Support and Protection of Human Health. If data from the last 5 years were determined to be insufficient, additional health-based data are to be collected and re-evaluated. If the water segment is still found to exceed the conditions identified for the planning list, then the segment is placed on the verified list.
The Impaired Water Rule provides additional information related to impaired waters prioritization and evaluation of existing pollution control measures. Water segments identified on the verified list are prioritized according to the severity of impairment of designated uses, accounting for serious water quality problems, valuable and threatened resources, and risk to human health and aquatic life. Highest priority is given to segments listed due to threats to potable water or human health and to segments with impairment associated with the federally listed threatened and endangered species. Lowest priority is given to segments with impairment due to mercury-related fish consumption data prior to 2010, human-made canals and ditches impair ed due to dissolved oxygen and segments identified after the development of the planning list (unless the impairment is related to a high priority issue). The rest of the segments are considered medium priority, and these are prioritized based on OFWs, multiple designated use impairment, water quality criteria exceedance of 25 percent of the samples with a 90 percent confidence, multiple criteria exceedances, and FDEP TMDL priorities.



## 2.4.3 Pollution Control Mechanisms
Since many governments and private agencies in Florida already have embarked on major pollution control plans and strategies, the IWR contains a provision [Rule 62-303.600] that allows FDEP to consider whether the plan would be likely to result in the attainment of water quality standards within the impaired water body or segment. If FDEP determines that 1) the water segment is expected to attain water quality standards in the future; and 2) “reasonable progress” toward attainment is expected to be achieved within 5 years (i.e., the next time the water segment is considered in the basin rota tion schedule), then the water segment is not to be listed as a verified water segment for TMDLs. Water segments that are already making reasonable progress toward achieving the applicable water quality standards do not need to be restudied under a TMDL process.
The key to this provision is that there must be “reasonable assurance” that the proposed pollution control measures (plan or strategies) would indeed be very likely to result in attainment of the water quality standards for the segment. To more closely define this phrase, FDEP issued a draft memorandum providing guidance to address reasonable assurance for such pollution control measures. A very important consideration of this review by FDEP is that the pollution control program must be “under local, state, or federal authority” to assure that the program is implemented. The guidance states that this provision would be satisfied if the following conditions occur: 1) the program is subject to or required by ordinance, regulation, rule, or law; or, 2) the program is subject to a written agreement

2-12Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### signed by local stakeholders and one or more governmental entities. The agreement must include measurable goals, performance criteria, benchmarks, and a corrective action plan.
Documentation of reasonable assurance must include the following elements:

 

### A description of the impaired water segment including the type of water, description of the impairment and the suspected source(s) of the impairment;

 

### A description of the water quality or ecological goals to which the water segment is to be restored including a schedule when the goals are to be met;

 

### A description of the pollution control actions that will be implemented including the responsible participating agencies, the actions to be taken, the estimated pollution load reductions, written agreements and sources of funding; and,

 

### A description of corrective actions to be taken in the event water quality does not improve to the degree or according to the schedule defined.



## 2.4.4 Delisting
The last major element of the Impaired Waters Rule is the process for removing a stream segment from the TMDL program. This proces s is known as delisting. The fundamental premise is that waters that are “verified to not be impaired during development of the verified list shall be removed from the State’s planning list” [Rule 62-303.720(1)]. There are two ways to delist a water segment from the planning list: 1) completion of a TMDL for all of the pollutants for which the segment was placed on the planning list in the first place, or 2) verification that the water quality of the segment under scrutiny meets applicable water quality standards. As with the listing procedure, the procedure for delisting is based on an assessment of the segment’s ability to support the designated uses.

 

### For waters that were originally listed for failure to meet aquatic life support:

 

### For listings that were based on water quality exceedances , the segment is delisted when: the number of exceedances indicate less than a 10 percent exceedance frequency with a minimum of a 90 percent statistical confidence (minimum sample size is 30 samples); following implementation of pollution control activities, new water quality data show that the segment no longer meets the conditions for listing; or demonstration that the water segment was inappropriately assessed during the original listing process and reanalysis of the data shows that the segment no longer meets the conditions for listing.

 

### For listings that were based on biological data , the segment is delisted when it passes two independent bioassessments with no failed bioassessments for at least one year.

 

### For listings that were based on toxicity data , the segment is delisted when the segment passes two toxicity tests with no failed toxicity tests for a year.

 

### For listings based on fish consumption advisor ies, the segment is delisted when the advisory is lifted or removed and the reasons for the advisory are no longer applicable.

2-13Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### For listings based on shellfish, the segment is delisted when the segment is reclassified to its original or higher harvesting classification.

 

### For listings based on bathing closures or advisories, the segment is delisted when the listing thresholds do not apply for five consecutive years.

 

### For listings based on threats to potable water supplies, the segment is delisted when applicable water quality criteria are met (see sampling requirements above) and the costs for higher treatment are removed.

 

### For listings based on human health based annual criterion, the segment is delisted when there are no exceedances of the criterion for a period of three consecutive years (see sampling requirements above).

 

### For listings based on nutrient impairment, the segment is delisted if the listing criteria are not exceeded for a period of three consec utive years (see sampling requirements above).

 

### Finally, for any listed waters, segments can be delisted if there is a change in the approved analytical procedures that results in the segment no longer meeting the listing criteria.

The FDEP Secretary must issue an order to approve the decision for the segment to be formally delisted.

  

2-14Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Section 3 DATA ACQUISITION AND ASSESSMENT

Ye s

Yes Proceed to Element IV Data Adequate for TMDL Use Existing WBID Data

No Yes Ye s

No Clarification/Liaison/Status Meeting Update the WBID Dataset

Review Comments TARC Review 8 7 Assessment of

Initial WBID Data Set

Supplemental Data Collection or

monitoring for WBID

Uncertainty Analysis and Data Needs for Selected Model Anticipated Uncertainty of

TMDL Assessment of Watershed and

Receiving Water Models Watershed and Receiving Water Model Recommendations

Tech Memo Data Adequacy and

Supplemental Collection Needs

Tech Memo

Supplemental Data Collection

3

4

5 Tech Memo No

FDEP Decision Adequate

Data FDEP Decision: Adequate

Data?

No Collect Supplemental Data 6 2

FDEP Acceptance



### 3-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# 3.1 INTRODUCTION

The purpose of this section is to describe the data that may be needed to conduct a TMDL assessment of specific pollutants for specified water segments. Data are required for the estimation of point and nonpoint pollution loadings and receiving water effects. This section presents a wide range of data types to be considered; however, not all may be required for specific application, and in some cases other specific data may be needed that are not listed here. Typically, both water quantity and quality data are needed, as well as data related to pollutant sources, inputs, background and natural sources, atmospheric deposition, geomorphic conditions and other pertinent information. Table 3A.1 in Appendix 3A provides an inventory of data types and sources that may be used in a TMDL study.

This section provides potential sources of pertinent data to support TMDL assessments and provides general protocols for compiling, generating, and analyzing these data. Data may be required for multiple purposes. For example, water quality data may be used to develop model coefficients, calibrate and validate model results, and provide a basis for pollutant loading reduction assessments. During many TMDL modeling studies, the need for additional data can be iterative. Initial data collection efforts may be sufficient to develop a TMDL model that allows screening-level load allocations. As the TMDL is refined and targeted to specific pollutant processes, additional data collection and/or analysis may be required to refine modeling efforts aimed toward identifying the amount of pollutant reduction required to achieve water quality standards. At each step, the TMDL analyst must evaluate whether the available data are adequate to support the level of modeling required to develop the TMDL. The TMDL analyst also must consider data uncertainty and accuracy. The TMDL process includes sensitivity and uncertainty analysis to help define a margin of safety (MOS) to account for uncertainty in the data and in the models that are prepared from these data.

Data are available in various forms and spatial and temporal scales. Daily time series data are often available for many hydrologic and water quality parameters. However, for TMDL assessments, rainfall, stage, flow, and velocity may be needed at smaller time scales (e.g. hourly). Therefore, daily time series data as well as more frequent data time series may be considered for acquisition and evaluation. Al l data used in TMDL assessments may be inspected and evaluated for reasonableness and quality (check ranges of typical values and attempt to verify extremes and outliers).

The first major step in the TMDL process is to identify the relevant and necessary data. The next step is to collect and analyze existing data including identification of existing models and studies for an area. Much of the required data may already be available through Federal, State, city, county, and private entity files and may have already been analyzed and assessed using the methods consistent with the principles described in this document. For this reason, the initial effort for a TMDL assessment is generally a data definition, collection, and evaluation task to obtain locally available pertinent watershed and receiving water data and to maximize, to the extent practical, the use of these data throughout the TMDL development process. In some cases, TMDLs will be developed with a concurrent stakeholder outreach process. The stakeholder outreach process for the TMDL program should start well before the definition of TMDL loading reductions in order to facilitate the initial data collection efforts.

3-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### This section presents water quantity and water quality data and methods to support TMDL analyses.



# 3.2 WATER QUANTITY DATA

Water quantity and water quality data are required to estimate pollutant mass loadings from the watershed to receiving water bodies. This section establishes protocols for determining and analyzing water quantity data as a part of the TMDL process.



## 3.2.1 Streamflow Data
Understanding the hydrologic cycle and different flow regimes under dry, average, and wet weather conditions in natural and manmade systems is critical to reliably estimate pollutant load transport and deposition. Flow is rarely measured directly. It is generally estimated by measuring water depths and velocities for given cross-sections to produce rating curves.

The longest-term or most complete data set available may be considered for TMDL analysis because a longer period of record will better account for year-to-year or month-to-month hydrologic variability. In some cases use of shorter-term current data may be more representative, particularly if there have been recent changes in the upstream watershed that might affect flows (e.g., new reservoirs or flow diversions). In the absence of reliable historical data, alternate methods for flow estimation may need to be employed. These may include:

 

### Application of regression equations for estimating flow in ungaged areas;

 

### Tributary area ratio techniques; or,

 

### Development of hydrologic models to synthesize (estimate) flow records.

Flow data for riverine (non-tidal) systems in Florida are available from a number of sources, including United States Geological Survey (USGS), Water Management Districts (WMDs), and County, City or privately operated gages. Potential data sources listed above are discussed below in the general order of preference/reliability.



### 3.2.1.1 United Stat es Geological Survey Where available, data from USGS streamflow gagi ng stations are typically the first choice for long-term records of daily average stream fl ow. The USGS subjects all officially published data to rigorous review. The United Stated Geological Survey (USGS) Office of Surface Water (OSW) currently publishes streamflow data for 619 locations in Florida. Time series datasets are retrievable online. Many sites have historical streamflow data spanning decades and up-to-the-hour real time streamflow data are also available for many sites ( http://nwis.waterdata.usgs.gov/usa/nwis/discharge ). Data may also be obtained from the USGS National Streamflow Information Program (NSIP) web site [http://water.usgs.gov/nsip], through review of annually published Water Resources Data Reports, by request from local USGS offices, and through EarthInfo data CDs or web site [http://www.earth-info.org]. In some cases more recent data, including real time data, can also be obtained from the USGS. However, some such data may not have undergone the

3-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### full quality-control review. Such data are released by the USGS as “provisional” (i.e., subject to revision) and must be used with caution. Using provisional data for TMDL analyses could increase the level of uncertainty in pollutant loading estimates and could require a greater margin of safety. This may be a tradeoff with the need to use data that are applicable to current land use and hydraulics conditions where major changes could make calibration difficult and/or incorrect. Figure 3.1 and Figure 3.2 show plots of stage and flow data, while Figure 3.2 includes a comparison from a hydrologic model to the USGS gage data (sometimes called measured).

Figure 3.1 Example Plot of Stage versus Time and Rainfall

3-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Figure 3.2 Example Plot of USGS Daily Streamflow



### 3.2.1.2 Water Management and Flood Control Districts Florida’s WMDs participate in water resource management activities that include the installation and monitoring of stream-gaging stations. WMDs publish periodic Surface Water Reports that present collected data. Some of the WMDs also maintain databases that include information from other sources, such as the U.S. Army Corps of Engineers (USACE), USGS, National Oceanic and Atmos pheric Administration (NOAA), FDEP, and county/city/private data collection efforts. Data are subject to revision and are not guaranteed to be up-to-date. However, there is a wealth of information available for establishing general flow trends and stage boundaries or trends for a variety of Florida streams and rivers. The following five WMD data sources can be accessed from the internet by simple keyword searches. Data requests also can be made via telephone, fax or e-mail requests to the applicable District.

 

### Northwest Florida Water Management District – Relies on USGS and USACE, Mobile District data collection

 

### Suwannee River Water Management District – Keyword “Water Data”

 

### St. Johns River Water Management District – Keyword “Hydrologic Conditions and Controlled Water Levels”

3-5Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Southwest Florida Water Management District – Keyword “Hydrologic Data”

 

### South Florida Water Management District – Keyword “DBHYDRO database”



### 3.2.1.3 County/City/Private Data Data collected by local governments or priv ate entities can be useful for supplementing other primary data sources. Local data collection efforts tend to be shorter-term and more narrowly focused in scope. Data are often collected and reported by professional consultants or by trained municipal staff. In so me cases, trained citizen volunteers are used for data recording. Such data may be treated as provisional and TMDL pollutant loading estimates based on these data may have a higher level of uncertainty.



### 3.2.1.4 Flow Data Collection
In the absence of historical data, a flow measurement and data collection program may be required. Short-term flow data may be collected during the preparation of the TMDL; however, such data would cover only a limited period of time and generally would not sufficiently characterize long-term hydrologic variability. In these cases, the TMDL implementation plan may require development a nd implementation of a long-term flow data collection program.

Efforts to obtain and manage field measured flow data should carefully follow standard field protocols such as those established by the USGS or Bureau of Reclamation, as documented in the publications referenced below:

 

### “Techniques of Water Resources Investigations of the United States Geological Survey, Discharge Measurements at Gaging Stations, General Procedure for Gaging Streams, and Stage Measurements at Gaging Stations”; and,

 

### “Department of the Interior Bureau of Re clamation Water Measurement Manual.”

Field instream flow measurements general ly rely on probes and dataloggers that continuously measure and record depth or velocity. A channel rating curve must be developed that relates flow depth to discharge. Application of the channel rating relationships to depth measurements can be used to develop estimates of continuous discharge records. It is preferable to obtain channel/rating field measurements at various flow levels including both dry- and wet-weather conditions. This is not, however, always practical and estimates of flows, particularly high flows, are commonly slope-area relationships or other indirect measurements. The following USGS Techniques of Water Resources Investigations may be consulted (http://usgs.gov):

 

### Measurements of Peak Discharge by the Slope Area Method

 

### General Field and Office Procedures for Indirect Discharge Measurements

 

### Measurement of Peak Discharge at Width Contractions by Indirect Methods

 

### Measurement of Peak Discharge at Dams by Indirect Methods

3-6Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### General Procedure for Gaging Streams

 

### Stage Measurement at Gaging Stations

 

### Discharge Measurements at Gaging Stations

 

### Measurement of Time of Travel and Dispersion by Dye Tracing



### 3.2.1.5 Flow Data Analysis Flow data obtained using the methods cited above may undergo an analyses process consisting of the following steps:

1. Evaluation of the data set for completeness and consistency

2. Filling data gaps

3. Time series analysis

4. Baseflow analysis

5. Determination of hydrological characteristics

6. Development of coefficients and data required for modeling

Described below are the required steps for the above flow data analyses.

Evaluation for Completeness and Consistency
Data may be collected electronically where feasible, or data may be entered in a database if obtained in a hard-copy format. The database may be checked for completeness of record and statistically analyzed. Simple x-y plots of flow hydrographs are often the best initial check for data completeness and consistency. In addition simple statistics such as means, standard deviations, maximum and minimum val ues can be used to determine data outliers, and for comparison with other streamflow or rainfall data to ensure that the data make “hydrological sense.” For example, such a review of data would expect to indicate that large rainfall events that are evenly distributed over a watershed may result in large streamflow events, and large streamflow events in upstream tr ibutaries of a river system may result in large streamflow events in a downstream channel of the same river system. Other factors, such as antecedent moisture conditions may influence these general relationships and may be considered when evaluating hydrologic data.

Actual or even apparent inconsistencies can serve as “red flag” indicators of problems with data. Plots that superimpose time-series of streamflow and rainfall data will facilitate data comparisons and data quality assessments. Plots that superimpose the daily or monthly means, maximums, minimums, and standard deviations can also be developed for rainfall and streamflow for the study watershed or for watersheds within the region that have similar

3-7Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### tributary areas and land use patterns. Estimates of monthly or annual runoff volumes may also be converted to units of depth (e.g., inches of water depth over the entire tributary area) for comparison with runoff measured at other gages or incipient precipitation. Typically, the annual runoff volumes should not exceed rainfall volumes unless large springs are feeding groundwater inflows from adjacent basins.

Data found to be inconsistent, without a plausible explanation, may be flagged and may need to be eliminated from the database. Inconsistent data typically include flow volumes that exceed monthly or annual precipitation volumes or flows that do not appear to be a response to a precipitation event or a known discharge in the upstream watershed.

Potential Hysteresis Florida has a relatively high potential for hysteresis (more than one value of streamflow possible for a given stage) in stage-discharge datasets due to a relatively flat topography, urbanization and locations with backwater potential. For a given stage, the expected discharge may vary depending on whether the measurement was taken on the rising or receding limb of the event hydrograph and the degree of tailwater. This is also called a “looped rating curve”. A highly varied flow regime can result in even wider variety of elevations that correspond to a given discharge magnitude, resulting from changes in water surface slope due to complex storage and constraint relationships with upstream and downstream conditions (Bedient and Huber, 1992). This is most evident in urban areas with relatively flat terrain where significant variations in headwater and tailwater conditions can

occur.

For locations with hysteresis potential, additional information regarding the instrumentation is in order. The USGS typically does not measure flow directly at many sites where the agency collects streamflow data. Pressure transducers are used to measure stage and estimate flow based on a site-specific physi cally determined stage-discharge relationship. Standard protocol requires collection of a significant number of stage-discharge data pairs across a range of flow events. Potential hysteresis is accounted for by conducting separate rising and falling hydrograph analysis, and by incorporating stage rate of change into the development of the rating curve. These are used to create regression relationships between stage and flow. In practice, data are seldom available to create a comprehensive relationship incorporating multiple independent variables and differentiating low flow, bankfull, and flood conditions.

For larger rivers and areas with identified hyst eresis, multiple velocity meters or acoustic Doppler technologies are also employed by the USGS in conjunction with pressure transducers to develop velocity-discharge relationships. For these locations, the implications of unidentified hysteresis are less pronounced. If hysteresis is evident, the TMDL analyst should calibrate to stage, velocity, and flow where such data are available.

Figure 3.3 shows an example of a mild hysteresis condition compared to a rating curve as derived from a calibrated hydraulic model to measured stages. One option in this casewould be to adjust the rating curve using a hydraulic model (e.g., SWMM EXTRAN or HECRAS) with consideration of measured depths to better average the “looped data” for flows.

3-8Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Figure 3.3 Florida Example of Flow Hysteresis

Filling Data Gaps Correlation or hydrologic synthesis techniques may be considered as a means to address incomplete hydrologic records or data gaps if this would result in more accurate TMDL analysis. If long-term records of streamflow data are available with very few missing data, the data may be adequate to complete the analysis described in this section, and filling of data gaps may not be necessary. However, if filling data gaps could significantly extend the time series to provide a more representative long-term hydrologic record, then gaps may be filled. Standard statistical or linear interpolation/extrapolation techniques may be used. Correlation methods include the following:

 

### Precipitation-runoff relationships,

 

### Ratio of tributary (drainage) areas method,

 

### Correlation of records from similar gaging stations, and

 

### Comparison of flow duration curves

More sophisticated hydrologic synthesis techniques include:

 

### Markov process or autoregressive models, and

 

### Moving average models.

Detailed procedures to implement each method are well documented in standard hydrology handbooks (e.g. Handbook of Hydrology, D.R. Maidment, McGraw-Hill, 1993).

3-9Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### The statistical techniques can be conducted in spreadsheet or statistical software packages. For example, regression analyses can be c onducted using the streamflow data (with missing data) as the dependent variable, and corresponding streamflow data for another station as the independent variable. The number of paired data points to be used in the regression analysis may be statistically signific ant. The regression analysis will result in a correlation coefficient (e.g., “R”) or coefficient of determination (R 2 

### ) that may be tested for statistical significance. If the correlation is determined to be significant, the regression equation may be used to approximate the missing values. Figures 3.4a and 3.4b show example plots comparing two gages in South Florida and Central Florida, respectively.

y = 1.6127x + 4E+07

R 2 = 0.9716

0.0E+00 1.0E+09 2.0E+09 3.0E+09

0.0E+00 5.0E+08 1.0E+09 1.5E+09 2.0E+09



### Cumulative flow at S-308 (acre-ft/year) S-80=f(S-308) Linear (S-80=f(S-308))Cumulative Flow at S-80 (acre-ft-year)



### Figure 3.4a Cumulative Flow Comparison of Two Gages

0 1000 2000 3000 4000 5000 6000 7000

0 1000 2000 3000 4000 5000 6000 7000 8000
USGS Cocoa Daily Flow (cfs)USGS Christmas Daily Flow (cfs)



### Figure 3.4b Paired Daily Flow Comparison of Two Gages

3-10Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Time Series Analysis
If long-term streamflow records are available, a time series analysis may be conducted to determine if there are trends in the data. Trends may indicate changing conditions in the watershed that could affect TMDLs. For example, changing land use may cause increased flow rates, velocities, and pollutant loads. As a result, even if concentrations of water quality constituents were to remain constant, pollutant loading to a waterbody may be increasing. The establishment of TMDLs needs to take such factors into consideration.

Time series analysis may be conducted on annual time series of data and can be accomplished by using statistical software packages with procedures such as regression or Kendall-Tau, or by regression analysis in a spreadsheet platform. Trend analyses may be conducted with the year as an independent variable and flow as a dependent variable. Regardless of the procedures used, the results must be tested for significance. Other methods include Spearman, Mann-Whitney, and Pearson Chi-square (Snedecor and Cochran, 1973). These methods test the association between variables via cross-tabulation. Figure 3.5a and Figure 3.5b show example time series analysis by use of frequency distributions, illustrating the distribution of probabilities for a range of flows being equaled or exceeded during a given year and fo r a given day, respectively.

Figure 3.5a Example Average Flow Exceedance Curve

3-11Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

0 1000 2000 3000 4000 5000 6000 7000

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percent of Time Flow ExceededDaily Flow (cfs)

USGS Christmas



### Figure 3.5b Example Daily Flow Duration Curve

Baseflow Analysis
Baseflow analysis is required to distinguish between the in-stream effects of surface runoff and groundwater flow, in preparation for modeling analysis. Standard techniques that are presented in hydrology textbooks may be used. The USGS has a computer program called HYSEP, which performs baseflow separation for its gage data (http://water.usgs.gov/software).

Estimation of Hydrologic Characteristics
Definition of hydrologic characteristics may provide an understanding of the principal hydrologic processes that take place in the TMDL study watershed. Local hydrologic characteristics may be used to develop a framework for analyses and modeling. Prior to conducting modeling studies, it is import ant to thoroughly understand the hydrologic processes that pertain to the local environment that must be reflected in the development of a model framework, input, and simulation sc enarios for modeling. The selection of an appropriate model for a TMDL analyses is dependent not only on the project requirements, but also on the data available for model calibration.

Streamflow data may be compared with available data regarding rainfall, geology, soils, meteorology, and groundwater. Characteristics such as closed basins, sinkholes and springs that can complicate typical runoff/rainfall relationships may be investigated. Seasonal attributes may be determined by examining monthly flow averages. The tools for examining and properly accounting for local hy drological characteristics generally would include the following: spreadsheets, published maps including geologic maps (hydrologic, hydrogeologic, climatologic, topographic) and ot her computer software. These tools can be used to develop runoff/rainfall coefficients, flow duration curves, low-flow and high-flow frequency analysis, or other indices of flow that describe the hydrological system. Maps may

3-12Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### be used to identify locations of sinkholes, springs, runoff, rainfall patterns, potentiometric surfaces and water table elevations, and aquifer properties.

If adequate streamflow data are available at the point of interest where the river enters the receiving waterbody, analyses described above may be adequate for defining flow conditions for a TMDL. If the point of interest is not gaged, but a large portion of the watershed is gaged, simple extrapolation techniques (e.g., multiplying streamflow by tributary area ratios) may be used to simulate a time series of flow data for use in establishing TMDLs. If a large portion of the watershed is not gaged, then modeling will be necessary. Typically, modeling is necessary because of a limitation of data. For TMDL refinement, additional supplemental flow monitoring may be conducted to check or verify this extrapolation.

Development of Hydrologic Coefficients and Data for Modeling
Definition of hydrologic characteristics w ill assist in developing an appropriate model framework and coefficients for modeling. The coefficients and data depend on the model framework but could include runoff/rainfall coefficients, infiltration rates, land slopes, channel slopes, soil moisture antecedent conditions, curve numbers, unsaturated soil storage values, roughness coefficients, and universal soil loss equation coefficients. Appropriate hydrologic coefficients must be selected so that the model simulates flows that reasonably mimic the watershed. Sections 3.4, 5, and 6 discuss model coefficients and data in more detail.



## 3.2.2 Stream Stage, Elevation and Velocity Data
For the TMDL process, stage and elevation data are used primarily for estimating flow by the development of stage-discharge rating curves as described below. Stage is usually expressed as an elevation of the water surface above a common datum (e.g., National Geodetic Vertical Datum [NGVD]). Flow depth is the difference between the stage and the elevation of the channel bottom at the point of interest. For specific points where a time series of stage and surveyed cross sections are available, a time series of depth can be developed and statistically analyzed. A depth-duration curve may be developed to show the percentage of time that specific depths of stream flow are exceeded or equaled in a system. The procedure may be accomplished in a spreadsheet that has an option to rank and simulate percentiles of exceedances. Stage data also can be used to define modelboundary conditions, and to establish water column depths and subsequently depthdependent lighting conditions for aquatic plant use. Velocity is also sometimes measured continuously and provides a valuable parameter to apply with flow depth and area to calculate flow and/or rating curves.

Stream stage data may be obtained from the same sources previously recommended for streamflow data. Important factors include the proximity of the monitoring locations to the study area, length of record (long-term), and whether available records reflect current watershed conditions. Potential data sources are discussed below in their general order of preference/reliability.

3-13Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### United States Geological Survey - USGS data from recording gage stations are less available for lakes than for streams. Where av ailable, lake stage data are reported by USGS as a water surface elevation above some reference datum. Measurements are typically instantaneous readings (not continuous records). The USGS subjects all officially published data to rigorous review. Lake stage data may be obtained from the USGS National Streamflow Information Program (NSIP) web si te [http://water.usgs.gov/nsip], but are more easily found through review of annually published Water Resources Data Reports, by request from local USGS offices, or through EarthInfo data CDs or web site [http://www.earth-info.org].

Water Management and Flood Control Districts - Water Management District staff gages and control structures provide much of the available historical data regarding lake stages. WMDs publish periodic Surface Water Reports that present collected data. Some of the WMDs also maintain databases that include information from other sources such as the USACE, USGS, NOAA, FDEP, and County/City/Private data collection efforts. Data are subject to revision and are not guaranteed to be up-to-date. Water Management District data sources can be accessed from the Internet by a simple keyword search as described previously. Data requests also can be made by telephone, fax or e-mail request to the applicable District.

County/City/Private Data - Data collected by local governments and private entities can be useful for supplementing other primary data sources. Local data collection efforts tend to be shorter-term and more narrowly focused. Such data are often collected and reported by consultants or by trained municipal staff. In so me cases, trained citizen volunteers are used for data recording.

Field Measured Data - Measurement protocols for stage m easurement in lakes are similar to those described in Section 3.2.2 for riverine systems.



### 3.2.2.1 Field Measured Data It is important that stage measurements at stream gaging stations be conducted over an adequate data collection period to characterize hydrologic variability. Typically, at least one year of data are required to define seasonal characteristics, but monitoring periods of several years are typically more appropriate.

Stage may be measured by standard protocols established by the USGS and described in documents such as “Techniques of Water Resources Investigations of the United States Geological Survey, General Procedure for Gaging Streams, and Stage Measurements at Gaging Stations” (USGS). Stage measurements may be coupled with rating curves and flow measurements to provide estimates of continuous discharge records. It is preferable toobtain stage measurements at various flow rates that encompass a wide spectrum of dryweather and wet-weather flow conditions for the system. However, this is not always practical and estimates of stage (particularly at high stages) are made from historical flood levels as indicated by high water marks. Valuable information can sometimes be obtained from residents who are able to recall landmarks that indicate the maximum or minimum water levels experienced during historical floods or droughts. USGS “Techniques for Water Resources Investigations” may be consulted.

3-14Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## 3.2.3 Lake Volume, Depth, and Residence Time
Lake depth data are used to determine the volume of water in a lake and to establish depthdependent light penetration conditions that are used in more complex water quality models. Depths are calculated as the difference between the water surface elevation and the elevation of the bed of the lake at a given location. Lake volume is important in determining residence times, mixing values, and concentrations. For example, a small lake with long residence times may not have sufficient assimilative capacity for a large pollutant loading mass without resulting in exceedances of water quality standards.

As discussed previously, lake elevation (sta tic water) data may be obtained from the USGS, WMDs, and County or City operated gages. Longest-term and most complete record sets may be used. Large lakes may have significant wave action which can affect gage results (e.g., Lake Okeechobee).

Residence time is an estimate of the length of time that inflowing waters and associated pollutants are likely to remain within a lake system before being discharged through an outfall. For steady-state conditions, residence time can be estimated by dividing the lake volume (cubic-feet) by the annual inflow rate (cubic-feet per year). While residing in the lake, pollutants may be expected to undergo changes, such as chemical transformation, sedimentation and biological uptake. The fraction of pollutant mass stored or lost is therefore dependent on the residence time. Short circuiting effects may be considered in the analysis.

Information concerning water residence time for Florida lakes is not generally available in public databases, but may be estimated through dye tracing studies, or by storage-routing computations, provided suitable data are available regarding lake bathymetry, inflow rates and outfall rates. Field review of the lake subject to a TMDL can assist in assessing whetherthe general lake configuration and inflow/outflow locations are likely to result in shortcircuiting or stagnant areas.

Residence time can also be estimated from linked hydrodynamic and water quality models. If models are used, a particle of a conservative substance can be injected (conceptually) into a remote part of the waterbody within the model, and the time that it takes to exit the system can be simulated.

Potential data sources are cited in Section 3.2.2.



## 3.2.4 Estuarine Tides and Circulation

In cases where TMDLs are to be established fo r estuarine systems, data regarding tides and circulation are important because pollutants are mixed and diluted at rates that are tidally influenced. Consequently, information on circulation and driving tidal forces is required. Estuarine systems are typically more complex than riverine systems because, in addition to freshwater inflows from a watershed, there are saltwater inflows that occur when tides flow in an opposing direction from the sea. Consequently, reverse flows and split-flow sometimes occur. For example, flows may be split with near-surface flows consisting of

3-15Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### freshwater flowing downstream in a seaward direction, and near-bottom flows consisting of saltwater flowing in an upstream direction.

Long-term historical data for tidal water levels are available from NOAA stations located along both coasts of Florida. Available data may include hourly heights, daily heights, and high and low water levels. Data may be requested through the Center for Operational Oceanographic Products and Services (CO-OPS) databases [http://co-ops.nos.noaa.gov]. The nearest station to the study area with adequate data availability may be selected for modeling. Should tidal stages need to be field-measured, a full tidal cycle over a 25-hour period or longer may be appropriate.

Pollutant transport, transformation, settling, and removal in an estuary are dependent on estuary hydrodynamics, which may be analyzed with complex hydrodynamic models or with more simplified flushing analyses. Models are described in Section 4. An example of a Tidal Prism Calculation Method is described in Appendix 3B

. 

# 3.3 WATER QUALITY DATA

As a part of the TMDL process, water quantity data and water quality data are required to estimate the pollutant mass loading from the watershed to receiving water bodies, and to estimate pollutant masses and concentrations present in the waterbody. This section describes the protocols for collection and analyses of water quality data in support of TMDLs.



## 3.3.1 Historical Data Collection and Analysis

3.3.1.1 Watershed Land-Based Load Data In urbanized areas, pollutant transport is typi cally modeled using “build up” and “washoff” coefficients that describe how pollutants accumulate in dry conditions, are washed off in rainfall events, and are conveyed into the stor m drain and natural systems. For agricultural areas, pollutant transport is typically associat ed with soil erosion processes from cropland areas, as well as with irrigation methods.

Groundwater contributions of flow and load may also be considered in the analysis. The mass load of pollutant transport from a river to a receiving waterbody is a function of the water quality constituent-concentrations and the flow rates. Mass loads are calculated by multiplying pollutant concentration data by the corresponding flow rates. Flow is usually expressed in units of volume per unit of time (e.g., cubic feet per second) and pollutant concentration in units of mass per unit of volume (e.g., milligrams per liter). A conversion factor is necessary to obtain unit and mass load results (e.g., pounds per year or pounds per acre per year).

Data are required for determining land use-based wash-off coefficients, establishing concentrations and loading from streams, and assessing concentrations in waterbodies subject to TMDLs for comparison with water quality standards. Land use-based “build-up” and “wash-off” coefficients are typically obtained from published literature, calibrated models, the Nationwide Urban Runoff Program (NURP), NPDES MS4 monitoring data, and/or other measurements. Build-up may consist of atmospheric, automobile, application

3-16Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### (fertilizer, pesticide, herbicide), and other sources which are commonly included implicitly in event mean concentration (EMC) and loading fact ors. These literature values are derived from measurements of particular pollutant concentrations for specific land uses at various locations. There are several Florida references for EMCs (e.g., Harper, 1992; CDM, 1995; ERD, 2003; and ERD, 2006). Some federal and state environmental regulatory agency databases also can provide information on water quality of specific discharges. Some of these discharges are associated with specific land uses and may be an acceptable source of data for pollutant wash-off rates.



### 3.3.1.2 Ambient Receiving Water Data Historical water quality data for rivers, lakes, streams and bays may be obtained from several public water quality databases. At the national level, the EPA maintains the STORET database. Requests for data may be made online at www.epa.gov/storet . The STORET database is split into “Legacy” data (before 1999) and “Modernized” data. The joining of data from the two databases into one dataset for TMDL analysis may be required. If so, the user may verify the combined dataset (e.g., check mean, median, standard deviation, minimum, maximum for each “piece”, and for the “whole”). The USGS National Water Quality Assessment (NAWQA) Program maintains a database that contains information collected through its activities. That database can be accessed through the website [http://water.usgs.gov/nawqa/].

Florida water quality data may also be obtained, as available, through the Generalized Water Information System (GWIS3), Florida STORET (storet.dep.state.fl.us), FDEP NPDES MS4 long-term monitoring data and published reports, and through WMDs. Other relevant water quality data also may be available through local counties, cities or other municipalities, other government institutions or private firms.

As with each data source, analyses of water quality data coverage, period of record, accuracy uncertainty, and quality may be performed. Detection methods and limits may be confirmed for each parameter.



## 3.3.2 Data Gap Analysis
Data gaps may be filled with caution by using some of the protocols described in Section 3.2 for water quantity. However, water quality data are often more complex, and interpolation or regression techniques should be used with caution. For example, a constituent such as dissolved oxygen is related to many environmental factors including time of day, solar radiation, water temperature, photosynthetic activity, availability of nutrients, respiration of plants and animals, growth and death rates of plants, and depth of water. These factors may cause a diurnal fluctuation. Data regarding dissolved oxygen is difficult to interpolate accurately across highly variable temporal and spatial conditions. Based on the complexity of the issues, water quality data gaps are not typically filled; rather, deterministic water quality modeling is used to predict water quality.

Data identified as below detection limit (BDL) should be evaluated with caution and may be appropriate for sensitivity analyses. For example, the practitioner may consider the use of the detection limit, one-half the detection limit, or zero for the BDL values for sensitivity analyses to determine the effect on calibration and validation.

3-17Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## 3.3.3 Field Data Collection
Protocols for developing and implementing field programs for water quality monitoring should be executed in accordance with Operating Procedures DEP-SOP-001/01.



## 3.3.4 Data Analyses
Water quality analysis may include compilation of available data and subsequent statistical analysis. Many of the analytical approaches described in Section 3.2.1 regarding flow can also be used to analyze water quality data.
Natural Background
Definition of natural background conditions is generally dependent on the length of the water quality records, yielding two possible conclusions:

1. Historical records extend back to a “pre-development” condition, or

2. Historical records are not sufficient (either too short or too incomplete).

If records extend to a pre-development era that corresponds to (pristine) conditions, then the natural background data may be adequately represented by the data for that period. These data may be assessed by considering:

 

### The amount of human impact related to the pollutant(s) of concern;

 

### Whether the historical conditions identified are achievable or not; and,

 

### Statistical measurements of normal daily and seasonal variability of the data.

Reference Sites
Records are typically not available for pre- development conditions. Under these conditions, other techniques such as modeling or impor tation of data for undeveloped areas in similar environments (e.g., reference sites) may be used. The State of Florida has identified 47 ecoregions for lakes as well as a compilation of bioregions ( Figure 3.6 ). These regions can be used to identify potential waters in the same ecoregion or bioregion that may be used as reference.

3-18Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Design Conditions and Time Periods
a may be used to establish design conditions. For

Seasonality

concentrations, maxi mums, minimums, variation, as well as data trends may

Variability and Long-term Statistics
, various statistical techniques are used to estimate Figure 3.6 Ecoregions and Sub-ecoregions of Florida

The statistical analysis of long-term dat example, a time series of data may provide information for trends and cyclic components of water quality conditions and/or to identify exceedances of standards. Data may be analyzed to provide time series for design conditions us ed in modeling. For example, indices such as chlorophyll-‘a’ and dissolved oxygen may be statistically analyzed to determine statistical description. A time period with “good”, “poor”, and “average” conditions can then be selected and if possible, this may be in the most recent 5 to 10 years to account for current conditions, land use, and hydraulics. Wet, average, and dry year conditions may also be considered for the choice of the simulation period.

Monthly mean be analyzed from long-term historical data using the same procedures described in Section 3.2.1. Monthly means may be used to establish seasonality. It should be recognized, however, the water quality data may not be normally distributed and thus, non-parametric statistical techniques may be needed. In many parts of Florida, a wet and dry season distinction may be adequate (as opposed to four seasons).

As discussed with water quantity data status (e.g., compliances, trends, central tendency and variability). Standard deviation, mean, median, minimum, maximum, and coefficient of variation may be calculated for each parameter of interest to assess the water qua lity data, its variability (locally, spatially, temporally) and interaction with watershed hydrology, hydraulics, and biology.

3-19Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### TMDL Calculation from Data
It may be possible to calculate the TMDL (termed “Data TMDL”) and necessary load reductions directly if there are adequate long-term flow and water quality data that cover both periods of standards compliance and exceedance. The data may also be used to develop appropriate coefficients for model simulations to establish TMDLs. If adequate historical streamflow and water quality dat a are available spatially and temporally, establishment of TMDLs may be accomplished for a specific waterbody by analysis for conservative substances as follows:

1. Multiply the allowable concentration (considering a margin of safety) by the long-term flow series and plot the allowable load distribution. The TMDL may be calculated for a time period applicable to the current watershed and receiving water conditions.

2. Multiply measured concentrations for each pollutant of concern by flow (or inflow) rates to the receiving water to calculate existing pollutant mass loads.

3. Use the plotted relationships to determine the pollutant load reduction that will be necessary to obtain the necessary reductions of pollutant concentrations in the receiving water.

TMDL Model Data Analyses
Sections 5 and 6 present details on TMDL model analyses. This section presents considerations for water quality model data preparation.

Short-term as well as long-term data may provide information for modeling. Data may be used to calibrate and validate a water quality model. The assessment may therefore include the arrangement of data time series in a form that is appropriate for model calibration and validation. The water quality model time series could consist of watershed and receiving water components.

For the watershed component, soil erosion and wash-off coefficients are often required. The published literature values and data are typically highly variable, even for the same geographic region and land use. These values, therefore, may be used to establish ranges for model calibration and indicate model variability.

Analyses of receiving waters require data to establish pollutant transformation as a pollutant travels in a river system may include the calculation of relevant model coefficients. The data, if available, could be used to calculate nitrification/de-nitrification rates, phytoplankton growth and death rates, and other water quality parameters, depending on the model being used. Typically, many of these parameters would be estimated as a part of the model calibration process. In-stream water quality data may be used to establish coefficients for pollutant transformation. For example, if there are two monitoring points along a channel, and there are no significant tributary or groundwater inflows, then changes in pollutant concentration are likely attributed to transformation. Some models simulate the process as a first-order decay, and the data may be used to calculate the decay coefficient. Such coefficients may also be established by model calibration and sensitivity.

3-20Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Examples of these techniques are described in EPA publications, including “Rates, Constants, and Kinetics Formulations in Surface Water Quality Modeling (2 nd 

### Edition)” (EPA, 1985) and the US EPA Storm Water Management Model (SWMM) Users Manual (Version 4, Huber and Dickinson, 1992; and recent Version 5 release).



# 3.4 WATERSHED DATA

As part of the TMDL process, watershed data ar e typically required to conduct analysis or to develop watershed models for water quantity and water quality.



## 3.4.1 Land Use Data
Land use data are required to define impervious area and provide or establish relationships for determining nonpoint source and point source loadings. For example, nonpoint sourceloadings can be estimated based upon relationships between land use and pollutant buildup and/or wash-off rates.

GIS land use data are available from many Florida counties, FDEP, WMDs, Natural Resources Conservation Service - formerly the Soil Conservation Service (NRCS) and the University of Florida GEOPlan center. Depending on the location of the site, data may be obtained from any of the above organizations. The data originate from the NRCS, using the Florida Land Use and Cover Classification System (FLUCCS). Statewide FLUCCS data in GIS coverages are available for 1988, 1995 and in some areas, 2000 [ftp.dep.state.fl.us/pub/gis/data].

Available information regarding land use data may be assessed to determine if the data are current and whether aerial photography updates are necessary. Updating may be performed either by obtaining more recent land use GIS coverages, and/or by ground-truthing the watershed. The GIS maps can be “marked up” in the field to identify differences are noted between the maps and the existing conditions. The new information may then be updated in the GIS database. If recent aerial photographs are available, they can also be used to update the GIS layer.

Depending on the model framework selected, similar land use categories with similar hydrological and water quality characteristics may be aggregated into representative categories. Percent imperviousness is typically a good parameter for aggregating land use categories. An example of imperviou s cover per land use is shown in Table 3.1.

3-21Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 3.1 Impervious Cover per Land Use
Land Use Category Range of Typical Percent Impervious
Forest/Open 0 to 1%
Agriculture/Pasture 0 to 1%
Cropland 0 to 1%
Low Density Single Family Residential 5 to 15%
Medium Density Single Family residential 25 to 35%
High Density Single Family Residential 40 to 60%

Commercial 80 to 90%
Office/Light Industrial 60 to 80%
Heavy Industrial 80 to 95%

Waterbodies 100%

Wetlands 25 to 100%
Major Roads 80 to 90%

Source: CDM, 1992



### It may be necessary to obtain land use maps for both historical and projected future conditions. Historical land use conditions often can be interpreted from historical aerial photographs, and future land use patterns may be interpreted from county comprehensive plans or zoning maps.



## 3.4.2 Meteorological Data
Meteorological data are required to quantify rainfall, evaporation, transpiration, and other parameters for modeling or analysis of nonpoint source pollutant loads.

Rainfall
Rainfall is the main input that drives watershed runoff during wet weather conditions. It is also a direct source of fresh water, as it falls on lake or other waterbody surfaces. Annual rainfall totals can be used to define average, wet, or dry years.

Long-term rainfall time series data are available from local WMDs, the USGS, the National Weather Service (NWS), and the National Climatic Data Center (NCDC), as well as from county and municipality gauges. The NWS and NCDC are good sources of data for short time-step electronically stored rainfall (e.g., 15 minutes and hourly). As rule of thumb, hourly rainfall time series may be sufficient for most TMDL studies. Data from major airports and NWS stations are typically stored in the NWS database. The WMDs typically store daily rainfall data, but also have been recently storing short-timestep rainfall data. The USGS has, in recent years, begun installing short time-step rainfall gauges at some of its streamflow

3-22Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### monitoring stations. Counties and municipalities often monitor rainfall for special studies, such as estimating seepage into municipal sanitary sewer pipes during flood events. An additional source of short time-step rainfall data is the University of Florida IFAS FAWN website ( http://fawn.ifas.ufl.edu/ ) that has data starting in 1998 for stations throughout Florida. Depending on the analytical or modeling framework chosen, data may be obtained by requesting data from the above referenced agencies. In addition, the FDEP has contracted with Florida State University to develop methods to allow Doppler radar records to be used in TMDL modeling.

The level of rainfall analysis that will be needed will depend on its intended use. For example, long-term simulations could use data from one representative rain gauge, but calibration would require data from at least three rain gauges to define spatial and temporal variation. Typically, the availability of rainfall data for the watershed may first beinvestigated. All rain gauges may be located and labeled to indicate if daily or shortincremental rainfall data are available, and the period of availability noted. If a detailedwatershed model is being constructed for nonpoint source pollutant evaluation, then shorttimestep rainfall is desirable (5 to 60 minute). If rain gauges with short-timestep rainfall are located on the watershed with adequate distribution to define rainfall spatially, then a Theissen polygon network may be developed with the short-timestep rain gauges. If the daily rain gauges would add significant improvement to the spatial distribution, they may be used to supplement the short-time step rain gauges, by using the hourly temporal distribution of a nearby rain gauge.

Rainfall data can be used to develop runoff/rainfall relationships, frequency analysis, double mass flow relationships ( Figure 3.7 ), or wet-pollutant load estimation from atmospheric deposition. Runoff/rainfall relationships are described in Section 3.2. Frequency analyses may be performed on annual rainfall totals from long-term datasets to determine “wet”, “dry”, and “average” years. Years that have short-time step data for the “wet”, “dry”, and “average” year may be selected for modeling normal and extreme conditions. The terms “wet” and “dry” are relative terms and in this instance means “wetter than average annual total rainfall” and “drier than average annual total rainfall”, respectively.

Double mass curves can be developed to detect and correct inconsistencies or changes in rainfall datasets. They are created by developing a cumulative plot with the cumulativerainfall of one gauge on the x-axis and cumulative rainfall of another nearby gauge on the yaxis. A constant slope in the line indicates a constant relationship between the gauges over time relationship, whereas a change in the slope indicates that a divergence in cumulative rainfall catch (Figure 3.7).

3-23Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Figure 3.7 Double Mass Curve

Solar Radiation and Air Temperature
Solar radiation data and air temperature data are the important components of a watershed or receiving waterbody. They influence evaporation and evapotranspiration, described below. In addition, they are required input for some receiving water quality models because they influence the simulated respiration and growth of the biota.

Solar radiation and temperature data are available from the NWS and several universities, e.g., Institute of Food and Agricultural Science (IFAS) of the University of Florida. Data also may be available from specific studies spons ored by the WMDs, USGS, FDEP, counties and municipalities. These studies typically report the monthly average duration of daylight hours and the maximum solar radiation that can be expected during those months.

The analysis may result in the preparation of time series datasets of air temperature andsolar radiation data suitable for modeling. If solar radiation data are not available, latitudedependent cloud cover can be used to estimate solar radiation. Some texts provide information regarding typical seasonal latitude-dependent cloud cover.

3-24Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Evaporation and Evapotranspiration
Evaporation and evapotranspiration (ET) rates prov ide estimates of atmospheric losses from the watershed land surfaces or receiving waterbody surface, which are important components in annual hydrologic balances and in modeling. ET is sometimes established by subtracting other known terms from rainfall and other inflows in a mass balance.

Evaporation data for Class-A evaporation pans are available from the same sources as described above regarding solar radiation and air temperature. Evapotranspiration rates are dependent not only on seasonal conditions, but also on soil moisture availability. Generally, there are only limited measurements of evapotr anspiration conducted by lysimeter or other instruments, and typically evapotranspiration is calculated from an upper limit, potential evapotranspiration (PET). PET may be estimated from pan evaporation rates, or from meteorological indices such as humidity, air temperature, wind speed, and solar radiation. Figure 3.8 shows an example of the seasonal variation of daily evaporation for an application in northeast Florida.

The USGS has published several references on ET, including direct measurement in some areas (USGS, 1996), and the Handbook of Hydrology (Maidment, 1993) which provide several methods to estimate ET and PET.

Figure 3.8 Example of Potential Evapotranspiration Data



## 3.4.3 Topographic Data
Topographic data are required for watershed delineation and runoff modeling. The data will provide information on watershed slopes, channel slopes, basin and subbasin tributary

areas.

Topography
Topographic data are typically obtained from hard copy or digital topographic maps available from the USGS, the WMDs, countie s, cities and other municipalities. USGS quadrangle series maps are available for the entire state at a scale of 1 inch = 2,000 feet (1:24,000). USGS maps typically do not provide a contour interval of less than 5 feet. More detailed maps are available for specific Section/Township/Ranges from the WMDs at a scale

3-25Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### of 1 inch = 200 feet (1:2400). Digital elevation model (DEM) data are often available from the WMDs or USACE and Light Detection and Ranging (LiDAR) datasets are becoming more common. It should be cautioned that all topographic data may be checked against verification sources (e.g., survey), and LiDAR may not accurately represent topography in heavily forested areas and does not provide bathymetry.

Cross Sections
Analysis of topographic data is performed in pre paration for modeling. Typically, information is extracted from hard copy maps by defin ing channels and cross sections and obtaining measurements with a map odometer or by di gitization and measurement in a GIS system. DEM may be used to define cross sections with GIS software. It should be cautioned that DEMs may not have adequate contour interval resolution to define incised channel or bathymetry of water bodies.

Surveys
Channel or river cross sectional data may also be obtained from surveys. Field visit and desk studies may be conducted to determine appropriate sites to be surveyed. The desk studies may include a review of available topographic maps to define points where survey information is required to ensure adequate spatial coverage and to define places where there are significant changes in channel geometry. The purpose of the field studies is to confirm or modify the findings of the desk study.

Basin/Subbasin Boundaries
Basin/subbasin boundaries may be defined by examining topographic ridges on a contour map. The definition of subbasins may be consistent with the modeling requirements as described in Section 5. Measurements of basin and subbasin areas may be made with a planimeter or may be digitized in a GIS.

Overland Flow Slopes and Roughnesses
Many hydrologic models consider the over land flow slope, length, and roughness (e.g., Manning n) in the estimation of runoff. Slopes and lengths are derived from topographic maps and Table 3.2 presents shallow overland flow Manning n values. Note that the roughness values for overland flow are higher than streamflow since roughness features are generally higher than overland flow depths (1 inch to 6 inches).

3-26Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 3.2 Manning n Roughness Values for Shallow Overland Flow

Source Ground Cover n Range Crawford and Linsley (1966) a 

### Smooth asphalt 0.012 Asphalt of concrete paving 0.014 Packed clay 0.03 Light turf 0.20

Dense turf 0.35 Dense shrubbery and forest litter 0.4

Engman (1986) a 

### Concrete or asphalt 0.011 0.01-0.013

Bare sand 0.01 0.01-0.016
Graveled surface 0.02 0.12-0.03 Bare clay-loam (eroded) 0.02 0.12-0.033 Range (natural) 0.13 0.01-0.32 Bluegrass sod 0.45 0.39-0.63 Short grass prairie 0.15 0.10-0.20 Bermuda grass 0.41 0.30-0.48 CDM (1989, 1992) c 

### Pine palmetto flatwoods 0.4 0.3-0.6 Various grass 0.2 0.2-0.3

Forested wetlands 0.4 0.3-0.6

a Obtained by calibration of Stanford Watershed Model.

b Computed by Engman (1986) by kinematic wave and storage analysis of measured rainfall-runoff data.

c Values from calibration of models in Volusia County and Duval County.



### Bathymetry
The NOAA’s National Geophysical Data Center (NGDC) compiles bathymetric data for coastal areas and provides public domain DEMs . A data search may be run using their web site [www.ngdc.noaa.gov/mgg/bathymetry] and av ailable mapping ordered in hardcopy or digital formats. DEM files may be directly downloaded for some areas, but DEMs are not always reliable sources of bathymetry data. Reliable coastal bathymetry data are also available through USGS mapping. Inland waterbody bathymetric data may be available from special studies performed by the WMDs or by local municipalities.



## 3.4.4 Soils Data
Soils data are required to establish infiltration characteristics for hydrologic modeling and for estimating water storage in the soils profile. For agricultural TMDL studies, detailed soils information is needed to estimate erodilibity and nutrient/metals content of the soils (e.g., soils potency factors). Soils texture and grain size distribution data are needed for sediment generation models.

3-27Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Soil Types
Data on soil types are available from the NRCS Soil Survey, published for each county. The Soil Survey manual provides a name for each soil type as well as information on the characteristics of each soil type. Such information includes the soil type, infiltration rate, permeability, water holding capacity, water table conditions, classification (e.g., sand, clay, silt), and hydrologic soil groups. The Nati onal Engineering Handbook Section 4 – Hydrology (SCS now NRCS, 1985) presents further information on soils and runoff properties as well as WMD ERP applicant’s Handbooks (e.g., SJRWMD, 2005; http://www.sjrwmd.com/programs/regulation/ handbooks/pdfs/msswhdbk.pdf). The soil types may be aggregated into Hydrologic Soil Groups (HSGs) for some hydrologic models. For other models, infiltration coefficients must be estimated based on soil characteristics.

The soil-type database for each watershed typically consists of many different soil types developed by the NRCS. For modeling purposes the soil types may be aggregated into the HSGs A, B, C, and D, as described below:

Group A . Soils having a high infiltration rate (and therefore a low runoff potential) when thoroughly wet. These consist mainly of deep, well drained to excessively drained sands or gravelly sands. These soils have a high rate of water transmission.

Group B . Soils having a moderate infiltration rate when thoroughly wet. These consist chiefly of moderately deep or deep, moderately well drained or well-drained soils that have moderately fine texture to moderately coarse texture. These soils have a moderate rate of water transmission.

Group C . Soils having a slow infiltration rate when thoroughly wet. These consist chiefly of soils having a layer that impedes the downward movement of water or soils of moderately fine texture or fine texture. These soils have a slow rate of water transmission.

Group D . Soils having a very slow infiltration rate (and therefore a high runoffpotential) when thoroughly wet. These consist chiefly of clays that have high shrinkswell potential, soils that have a permanent high water table, soils that have a claypan or clay layer at or near the surface, and soils that are shallow over nearly impervious material. These soils have a very slow rate of water transmission.

Dual class soils (e.g. A/D) indicate that a clay or hard pan may limit infiltration. For drained conditions, these soils can function as a class C, B, or A depending on degree of drainage.

Soil storage values can be estimated as identified in a Guide to SCS Runoff Procedures (SJRWMD, 1985). Table 3.3 presents examples soil storage and infiltration rate values for Florida applications (CDM, 1989 and 1991).

3-28Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 3.3 Typical Ranges of Values for Infiltration Rates (f), Horton Infiltration Shape Factor (k), and Soil Storage Capacity (S) for Different Antecedent Moisture Conditions (AMCs)

USDA NRCS Hydrologic Soil Group (HSG) Designation A B C D

Final constant infiltration rate, f c 

### (inches/hour) 15 - 0.30 2 - 0.15 0.25 - 0.05 0 – 0.10

Initial infiltration rate, f o 

### (inches/hour) 8 - 25 6 - 10 3 - 7 1 – 5

Shape factor, k for Horton infiltration curve (1/hour) 2 - 5 2 - 5 2 - 5 2 – 5

HSG A B C D

AMC 1, Dry (inches) 12.0 - 4.3 9.0 - 3.4 7.0 – 2.3 1.3 - 3.0

AMC 2, Normal (inches) 5.4 - 3.4 4.0 - 2.8 3.0 - 1.8 1.0 - 1.3

AMC 3, Wet (inches) 2.1 - 1.8 1.5 - 1.3 1.0 - 0.8 0.5 - 0.7

AMC 4, Saturated (inches) 0 0 0 0

Note: This soil storage S can be related to Curv e Number (CN) if desired using the standard SCS equation S= (1000/CN)-10.



### Defined Antecedent Moisture Conditions (AMCs) for Pervious Areas

Condition Description Total Rainfall during 5 Days Preceding Storm (inches)

1 Dry <1.4

2 Normal 1.4 - 2.1

3 Wet >2.1

4 Saturated Saturation

Soil Maps
Soil maps may contain the detailed soil types or aggregated hydrologic soil groups. Electronic GIS maps are available from sources such as the WMDs or NRCS. Depending on the model framework selected, the soils map may provide a basis for developing a GIS overlay of soils and land uses that is useful for establishing runoff and water quality characteristics.

3-29Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Soil Sorption Capacity for Organic Chemicals
Soils exhibit sorption capacity for pollutants and particularly for organic compounds (e.g. pesticides). The propensity of a soil to retain or adsorb organic chemical is typically proportional to its organic carbon content. Among the sorption models, the most common tool to measure this propensity is the retardation factor, R, which is defined as:



### θ ρ d 

### K R += 1

where K d 

### is the sorption partition coefficient, ρ is the soil bulk density and θ is the average soil moisture content. K d 

### is also expressed as a function of the soil organic carbon content. The physical significance of the retardation factor is that it measures how much slower the solute migrates than water because the solute spends part of its time sorbed on the soil matrix and immobile. This popular adsorption model assumes that the sorption mechanism is a linear function of the concentration and is isothermal. The Geographic Information System Department of the Soil and Water Scienc e Department at the University of Florida (http://grunwald.ifas.ufl.edu/GIS_Lab/gis_laboratory.htm#mission) has developed a large database that relates pesticides properties (e.g., K d 

### , half-life period) with soil properties (e.g., organic carbon content, clay content).



## 3.4.5 Groundwater Data
Groundwater contributes (and removes) flow and associated pollutant loads to surface water systems (e.g., springs or lateral seepage). To develop TMDLs, it is important to identify the fraction of pollutant loads that are contributed by groundwater. Relevant data include local geology, aquifer structure and properties and interactions between surface and groundwater in the vicinity of the TMDL study. The potentiometric surface of the deep aquifer and the water table elevation of the surficial aquifer in comparison to the surface water elevation are factors in determining the rates of groundwater contribution.

Potentiometric Surfaces
Maps of potentiometric surface are available from the USGS and WMDs. Data are also available for specific wells. The USGS web site [http://www.usgs.gov] has data that can be readily downloaded.

Potentiometric data may be analyzed by constructing or updating maps of groundwater contours. Software contour packages can be used to construct contours from point data.

Water Table and Seasonal Depth to Groundwater
Data regarding water table elevation are also available from the USGS and WMDs. Groundwater level contours for the surficial aquifer may be constructed.

Seasonal depth to groundwater may be established by examining a time series of groundwater level data for the surficial aquifer or the Floridan Aquifer in geographic locations where the Floridan is under water table conditions. The data are typically presented as elevation above the National Geodetic Vertical Datum (NGVD) or other datum.

3-30Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### These elevation data may be subtracted from land surface elevations, as determined from topographic maps or surveying, to determine the depth to water table.

Information on depth to seasonal high groundwater is also published in the Soil Survey Manuals developed by the NRCS.



## 3.4.6 Geomorphology
Streams and topographic features change from erosion and deposition of eroded material. Many of the lakes in Florida result from sinkhole erosion and subsequent collapse. Channels are scoured in locations by the erosional force of water, and sediments are deposited inother locations. Such geomorphologic processes may result in dynamic changes in crosssections and bathymetric data which may be required for detailed modeling of channels and receiving waters.

Cross-sectional data are described in Section 3.4.3. If available data were not based on recent surveys (past 5-10 years), then they may be field-verified to determine if morphological changes are significant enough to require new surveys.



## 3.4.7 Biological Data 3.4.7.1 Biological Assessment Techniques

Waters may be listed for biological impairment and biological data may be used in conjunction with water quality and hydrologic data to support the TMDL analyses.

Biological assessment techniques may consist of various tools used to measure the types, numbers, and diversity of species as well as the level of pollutants in the environment as an indicator of potential exposure. These pollutant levels do not necessarily indicate the occurrence of deleterious biological effects. Measures of exposure may be associated with the measures of effect in order to establish a causal relationship. Example biological assessment techniques are provided in the remainder of this section, and Appendix 3 provides further details.

3.4.7.1.1 Biological, Physiological and Histological Techniques
Tissue Analysis- Histopathology Chemical analysis of contaminants in biol ogical tissue is a very common technique of investigation. It is often related to environmental parameters such as water quality parameters, physiography, hydrology, and hydraulics to estimate the bioavailability of a constituent. These cause-and-effect relationships are very often valid for the specific site under investigation and may be transposed elsewhere for similar conditions. Parameter concentrations and their potential negative effect on tissue may be only comparable within the same species, for organisms at the same life stage, reproductive condition, size, weight, and sex. Many factors have to be considered when evaluating the tissue exposure to environmental contaminants. The most signifi cant ones include i) measurable parameter concentrations that vary with environmental conditions, ii) organisms that be collected and that are large enough to meet sampling requirement, iii) organisms that are easy to find and

3-31Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### that can withstand captivity during laboratory experiments, and iv) species with established body of knowledge on biological and toxicological effects.

It has been established that pathologic development of tissue has been related to the negative effect of acute as well as chronic ex posure to environmental contaminants. Due to their xenophobic and filtering functions, the liver and the kidneys are the primary target of interest for mammals (Couch, 1975). Of additional interest are the gonads and the immune system. For aquatic organisms, the gills are particularly sensitive to the contaminant exposure because they are the first uptake site, and fish tissue testing is often used as an indicator of cumulative toxicity and potential impacts for human consumption (e.g., fish advisory for mercury).

Semi Permeable Membrane Devices The Semi Permeable Membrane Device (SPMD) is an in-situ water sampling technique that reproduces the bioconcentration of organic contaminants in lipids of aquatic organisms (Huckins et al., 1993). It is not per se a biological assessment technique since it merely measures the concentration and not the level of exposure. This sampler made of a thin film of neutral lipid enclosed in a flat, and semi permeable membrane tube, passively sequestrates environmental contaminants. Whereas some organisms that metabolize and excrete toxic contaminants can eliminate t he causal link between residue and adverse effect, the SPMD will continue to accumulate contaminants to their maximum partitioning limit. The trapped constituents can be later analyzed with routine laboratory techniques.



### 3.4.7.1.2 Whole Organism and Single Species Techniques

Mortality, growth, and reproduction are the common measurements of toxicity tests applied to whole organism or single-species. Toxicit y test procedures have been provided for a large variety of species including microbes, algae, vascular plants, and aquatic and terrestrial invertebrates and vertebrates. For whole organism, the choice depends upon the species, life stage, and route of exposure. For a single-species, the choice depends upon sensitivity to contaminant, ease of culture and maintenance, and local relevance to the geographic

area.

Microbial Assays These type of assays use bioluminescent bacteria to detect the presence of cytotoxic and genotoxic environmental contaminants. Microtox® and Mutatox® are the most commonly used assays (Kaiser and Palabrica, 1991). Microtox® is used to evaluate the cytoxicity by quantifying light reduction and Mutatox® is used to detect the presence of DNA-damaging chemical.

Algal Assays Algal assays measure the effect of contaminants and nutrients on algal growth. A large variety of responses can be measured including optical density, oxygen production, carbon dioxide uptake, cell counts, gravimetric cell determination, and measurement of chlorophylla (American Society for Testing and Materials, 1997a). The behaviors of these parameters are then evaluated against some control responses.

3-32Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Aquatic Invertebrate Assays Growth of aquatic invertebrates is commonly used to evaluate the effect of environmental conditions on receiving water and aquatic sediments. The effect of waterborne contaminants is commonly evaluated using the Daphnia magna and Ceriodaphnia dubia (American Society for Testing and Materials, 1997b) whereas the effect of contaminant present in sediment is evaluated for several aquatic invertebrate such as Hyalella azteca and chironomus tentans (American Society for Testing and Materials, 1997c).

In-situ Toxicity Assessment In-situ toxicity assessments consist of obser ving survival, growth and behavior of indigenous species when exposed directly in water of the site of interest using environmental chambers (Finger and Bulak, 1988). Unlike laboratory toxicity studies that frequently focus on a single contaminant, the in-situ assessments provide insight into the cumulative and synergetic effect of contaminant mixtures.



### 3.4.7.1.3 Population a nd Community Techniques

The effects of environmental contaminants have been measured on tissue, organs, single species and whole organism. Evaluating their effect on populations and communities has focused on the structural and functional aspects of the biotic components of the ecosystem. Structural analysis techniques seek to identify the abundance and distribution of various taxa as indicators of population and community stress. Functional analyses are more interested in the ecological processes of ecosystems such as community respiration, nutrient cycling, decomposition rates, colonization rates, and trophic level analysis. Since these techniques seek to establish cause and effect relationship, it is important to integrate in the final analysis watershed geochemistry, water chemistry of the streams (pH, alkalinity, water temperature, dissolved oxygen), and the physical characteristics of the receiving water such as geomorphic channel unit, riparian vegetation, bank stability, stream depth, current velocity, and bed-sediment particle distribution.

Because of regional differences in habitat, species, thermal and hydrological regimes and water-quality problems, it may be difficult to make objective comparisons between sites. However, a large body of knowledge on population and community information for many areas of the country is readily available from the USGS, USEPA, and the US Fish and Wildlife Service.

Algal Population and Community Assessments Algae are an indicator for population and community assessment studies. They have a short life span, and they readily exchange constituents between the water column and the sediment bed. Since they are sedentary, they tend to reflect the local water quality. An example of protocols for design, sample collection, documentation and QA/QC for population and community assessment of algae is given by Porter et al. (1993).

Aquatic Invertebrate Population and Community Assessments Like the algae, aquatic invertebrates are a good indicator in assessing the long term effect of environmental contaminants on the indigenous community living in water column and sediments. They have longer life span than algae, live in close association with sediment

3-33Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### beds, and are relatively sedentary (e.g., benthic macroinvertebrates). An example of protocol design for regional and national sca le is provided by Cuffney et al. (1993).

Fish Population and Community Assessments The Index of Biotic Integrity is one of the most commonly used tools to measure the effect of contaminants on fish populations and community (Karr, 1981). That method develops different metrics related to fish composition, trophic composition, fish abundance and condition to measure the structural and functional status of the fish community. Meador et al. (1993) have developed a protocol for des ign, sample collection, and QA/QC for population and community assessment of fish. “Fish scores” have been used as a biological indicator in Georgia (CDM, 2001).



### 3.4.7.2 Trophi c State Index

Naumann (1929) developed the concept of trophic state as the biological response of a waterbody to forcing factors such as nutrient additions that can vary with time and space. The trophic state of a waterbody can also be defined as the total weight of living biological material (biomass) at a specific location and time. The Trophic State Index (TSI) developed by Carlson (1977) uses algal biomass as the basis of trophic state classification. Chlorophyll-a (CHLa), Secchi-disk depth (SD), and total phosphorous concentration (TP) are the three initial parameters used to independently estimate TSI; Total Nitrogen (TN) was added later as a fourth indicator. The measured values of these four parameters (CHLa, SD, TP, and TN) are used to calculate the four TSIs: TSI(CHLa), TSI(SD), TSI(TP), and TSI(TN). The range of the index is from 0 to 100 for convenience. The four index variables are interrelated by linear regression models and may produce the same index value for a given combination of variable values. Therefore, any of the four variables can theoretically be used to classify a waterbody. For the purpose of waterbody classification, a preference may be given to CHLa because it is directly related to biomass. The TSI based on CHLa is better than those of TP and TN which are better than that of SD.

The initial calculations of the TSI for each variable are straightforward:

1. TSI(CHLa)=9.81 Ln(CHL) + 30.6 (Carlson, 1977)

2. TSI(TN)=14.43 Ln(TN) + 54.45 (Kratzer and Brezonik, 1981)

3. TSI(TP)=14.42 Ln(TP) + 4.15 (Carlson, 1977)

4. TSI(SD)=60 – 14.41 Ln(SD) (Carlson, 1977)

Table 3.4 exhibits the TSI and its relationship with the trophic state of the waterbody according to Kratzer and Brezonik (1981). The TSI is an indicator of trophic state and not of water quality. TSI is an indicator of trophic conditions related to the biological status of the waterbody whereas water quality is related to specific water quality standards based on human needs or values. For example, an oligotrophic or eutrophic lake has attributes of production that remain constant regardless of the use of the lake or the location of the lake.

3-34Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 3.4 State of Waterbody and Trophic State (adapted from Kratzer and Brezonik, 1981)

TSI Trophic State

0 – 19 Ultraoligotrophic

20 – 39 Oligotrophic

40 - 59 Mesotrophic

60 – 79 Eutrophic

80 - 100 Hypereutrophic

The Trophic State Index is one of several methods used to describe the biological productivity of a waterbody. Forsberg and Ryding (1980) developed another method called the Trophic State Classification System ( Figure 3.9 ). Using this method, waterbodies can be grouped into one of four trophic states:

1. Oligotrophic: Waterbodies have the lowest level of productivity;

2. Mesotrophic: Waterbodies have a moderate level of biological productivity;

3. Eutrophic: Waterbodies have a high level of biological productivity; and

4. Hypereutrophic: Waterbodies have the highest level of biological productivity.

Figure 3.9 Trophic States, Concentrations of Constituents, and Typical Waterbody Uses (Source: Forsberg and Ryding)

3-35Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# 3.5 EXISTING POLLUTANT SOURCES

Existing sources of pollutants or other causes of impaired water quality must be quantified as part of the TMDL process. Existing sour ces include point and nonpoint sources that may impact a receiving waterbody and must be included in developing water quality models of the waterbody. Excluding background sources (see Section 3.3), these sources are categorized as: FDEP Regulated Sources, Water Management District Regulated Sources, and Sources Not Regulated by FDEP or WMDs. Each of these is described in more detail below.



## 3.5.1. Sources Regulated by FDEP
The FDEP has implemented two primary permitti ng programs for domestic and industrial wastewater facilities – the state permitting program for facilities that do not discharge to surface waters and the NPDES permitting program for facilities that discharge to surface
waters.

There are approximately 4,130 individually permitted wastewater facilities in Florida. These facilities represent both domestic and industrial wastewater facilities which are authorized to discharge wastewater either to ground water or surface water in the state.

At present, there are approximately 560 facilities authorized to discharge to surface water. As surface water dischargers, these facilities are subject to the Department’s federally authorized NPDES requirements. However, many of the NPDES facilities also discharge to ground water. The remaining 3,570 facilities are only authorized for groundwater discharges.

About two-thirds, or 2,750 of the individually permitted wastewater facilities in Florida are classified as domestic wastewater facilities. In general, domestic wastewater facilities are those principally designed to collect and treat s anitary wastewater or sewage from dwellings or homes, business buildings, institutions, and the like. The remaining one-third, or about 1,380 individually permitted facilities, is classified as industrial wastewater facilities.

Currently, FDEP permits over 17,000 sources including domestic wastewater, industrial wastewater, and stormwater facilities discharging to surface and ground water. Appendix 3D provides summaries of the permits for these three types of waters, respectively, for the counties in Florida. The largest type is Construction Stormwater permits at over 10,000, followed by Multi-Sector General Permits (M SGP) and Domestic Wastewater permits at about 2,500 each. Individual permit data for each of the facility types may be obtained from FDEP (www.dep.state.fl.us/water/wastewater/download).

Regulated pollutant sources, depending upon size and activity, are currently required to be registered with FDEP, and may be subject to discharge monitoring and reporting. Discharge Monitoring Reports (DMRs) submitted to EPA and FDEP are public records and may be requested for use in developing TMDLs. NPDES-regulated pollutant sources include the following:

3-36Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Domestic Wastewater Sources
Domestic wastewater facilities which discharge to surface waters and have design capacities of 10,000 gallons per day (gpd) domestic or 5,000 gpd domestic and commercial wastewater are regulated through the NPDES program. NPDES domestic wastewater permits require periodic submittal of Discharge Monitoring Reports (DMRs), generally monthly or quarterly. Reported parameters may include flow, pH, temperature, total residual chlorine, CBOD, TSS, nitrogen (TN, TKN, ammonia), phosphorus, and coliforms. Values may be reported as loads or concentrations based on effluent grab samples and flow measurements. DMR sampling requirements are ty pically weekly or monthly for parameters requiring lab analysis. Historical DMR data may be reviewed and copied from permit files by appointment with the local FDEP office. Records can be located using either the permit number or the Facility ID number. A full listing, by county, of FDEP Domestic Wastewater NPDES permittees may be downloaded from the FDEP wastewater web site [www.dep.state.fl.us/water/ wastewater]. FDEP Tallahassee maintains a DMR database and can perform data retrievals for specified time periods and parameters. Requests may be sent via fax or e-mail to the FDEP Tallahassee database manager depending on the type of activity.

Industrial Wastewater Sources
Industrial wastewater facilities that discharge to surface waters are regulated through the NPDES permitting program while those that discharge to ground waters are regulated through the state permitting program. Individual industrial wastewater discharges are highly variable in the amount and types of pollutants they may contain and the type of industrial activity. As such, NPDES permit discharge monitoring requirements are tailored specifically to each individual industrial facility, and reported parameters vary widely depending on the waste streams being treated. Permits typically require periodic submittal of DMRs (generally monthly or quarterly). Values may be reported as either loads or concentrations. Historical DMR data may be reviewed and copied from permit files by appointment with the local FDEP office. Records can be located using ei ther the permit number or the Facility ID number. A full listing, by county, of FDEP Industrial Wastewater permittees may be downloaded through the FDEP industrial wastewater web site [www.dep.state.fl.us/water/wastewater/iw]. FDEP Tallahassee maintains a DMR database and can perform data retrievals for specified time periods and parameters. Requests may be sent via fax or e-mail to the FDEP Tallahassee database manager.

Municipal Separate Storm Sewer Systems (MS4s)
MS4s in Florida are currently regulated by FDEP under the Phase I MS4 (large and medium systems) and Phase II MS4 (small) permitting system. Phase II MS4 systems are not likely to be good sources for monitored water quality data since the program was only recently initiated. However, except for relatively small municipal governments, all urban stormwater sources of pollutants are regulated through the NPDES Program in Florida. Phase I MS4 permits require development and implementation of stormwater monitoring programs, which may provide valuable data on runoff water quality from urbanized areas. Each Phase I MS4 permittee submits a monitoring plan for FDEP review and approval. The schedule of implementation, frequency of sampling, number of outfalls monitored, and parameters analyzed vary. Parameters that might be expected to be included in MS4 monitoring

3-37Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### programs include; dissolved oxygen, pH, specific conductance, TSS, metals, oil and grease, total nitrogen, total phosphorus, and possibly total and/or fecal coliform. Municipal stormwater agencies may be contacted directly to determine the scope and extent of MS4 permitrelated water quality data potentially available. Available data may be obtained from the municipality directly or through FDEP permit file review/data retrieval.

Industrial Stormwater
Industrial facilities in Florida that have on-site materials or processes exposed to rainfall or to stormwater runoff may be regulated by FDEP under the NPDES Individual or Multi-Sector General Permit (MSGP) for “stormwater discharges associated with industrial activity.” This permit covers discharges from several specified categories of industrial activity such as; heavy manufacturing, mining/oil and gas exploration, hazardous waste facilities, landfills and open dumps, recycling facilities, steam electric power generation facilities, transportation facilities, treatment works, and some light industry. The Industrial MSGP coverage is the most common. The discharge monitoring requirements vary by industrial activity. Monitoring frequency is typically once per quarter or biannual. Sampling is storm event-driven. Permits typically require periodic submittal of DMRs. Values are generally reported as concentrations with a total estimated storm volume recorded on the form. NPDES DMR data are forwarded to Tallahassee FDEP’s office and may be reviewed and copied from permit files by appointment, using either the permit number or the Facility ID number. A full listing, by county, of FDEP Industrial Stormwater permittees may be downloaded through the FDEP industrial wastewater web site [www.dep. state.fl.us/water/wastewater/iw]. The FDEP Tallahassee DMR database can be tapped for data retrievals for specified time periods and parameters. Requests may be sent via fax or e-mail to the Tallahassee FDEP database
manager.

Construction Site Runoff
Phase I NPDES permitting regulates construction site runoff from projects that are planned to disturb five acres or greater of land from the time of ground breaking to site stabilization. Originally promulgated and implemented for Fl orida under EPA Region IV, the program has since been delegated to FDEP. Phase II NPDES permitting for construction sites between one and five acres commenced in 2003, under FDEP. Discharge monitoring requirements under the FDEP Construction Generic Permit (CGP) emphasize visual evaluation of BMP effectiveness and do not require analytic monito ring of discharge for TSS. Quantitative data from this program are expected to be sparse. The EPA Region IV version of the CGP promulgated in April 2000 does require periodic, event-driven sampling and reporting of settleable solids, total suspended solids and turbidity in discharges from active construction sites that discharge into 303(d) listed waters. Estimates of potential pollutant contribution from active construction sites may be derived from data thus collected in other Region IV states by requesting DMR data from EPA Region IV. New agreements between FDEP and EPA have removed these sampling requirements.

3-38Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Concentrated Animal Feeding Operations – (This description may be added by FDEP later)

Mining Permits – (This description may be added by FDEP later)



## 3.5.2 Sources Regulated by Water Management Districts
Except for NWFWMD, the WMDs regulate stormwater discharges through Environmental Resource Permits (ERPs). NWFWMD does not have ERP authority, and stormwater permitting is accomplished through FDEP using Chapter 62-25, FAC. Permits are for the management and storage of surface waters as well as for dredge and fill activities. The WMDs have various levels of information available, such as the Southwest Florida Water Management District site that provides ERP information: [http://www.swfwmd.state.fl.us/data/gis/libraries /regulatory.htm]. Information generally can include the permit number, location, type, owner, and date of permit. However, the data quality is variable, as some permit data are complete while others are not.



## 3.5.3 Nonpoint Sources
There are a number of sources of pollutants that are not regulated with the same programs as point sources but are nevertheless regulated; these include septic tanks, agricultural sources, and diffuse sources such as atmospheric deposition, groundwater and sediment/legacy sources.

Septic Tanks
Septic tanks in Florida are regulated by the Florida Department of Health (FDOH) in conjunction with county Health Departments and are generally referred to as onsite sewage treatment or disposal. According to the FDOH Bureau of Onsite Sewage Programs, 31 percent of Florida’s population is served by about 2.3 million septic tanks. This represents about 426 million gallons per day (mgd) to be discharged to subsurface soils [http://www.doh.state.fl.us/environment/ostds/int ro.html]. The location, condition, type and maintenance frequencies data for septic tanks are very difficult to find and may require specific data inquiries to local Health Departments. Of particular interest to the TMDL program are data related to the number of septic tanks within a certain distance of surface waters and the frequency of failure. Septic tanks in close proximity (less than 300 ft) of lakes and streams have the greatest affect on water quality.
In the absence of specific septic tank data, local health and/or public works staff may be able to identify residential areas in a communi ty that are not served by public or private sewer systems. Historical evidence indicates that approximately 5 to 15 percent of septic tanks fail thereby producing high nutrient concentrations and loads to nearby water bodies through shallow ground water flows (EPA, 1986; CDM, 1989). If specific failure rates are not known, modelers can use a 10 percent failure rate and perform sensitivity analyses pending site-specific data collection efforts. Pollutant loading from septic tank leachate monitoring studies can be used to estimate loads contributed by failing septic tanks (doh.state.fl.us/environment/ostds/research). The range of concentrations for total surface loads from total-P and total-N based upon literature values is presented in Table 3.5.

3-39Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 3.5 Example Septic Tank Seepage Nutrient Concentrations

Total-P Total-N

Low 1.0 mg/L 7.5 mg/L

Medium 2.0 mg/L 15.0 mg/L

High 4.0 mg/L 30.0 mg/L

Source: Watershed Management Model Us er’s Manual Version 3.30, CDM, 1994



### Septic tank failures are a particular concern along lakes and waterbodies where there may be a direct hydraulic connection.
Agricultural Sources
Except for concentrated animal feeding operations, agricultural discharges are exempt from NPDES permitting pursuant to Federal law. However, several types of agricultural operations which alter hydrology are permitted by the WMDs. In Florida, agricultural sources are primarily the responsibility of the Depar tment of Agriculture and Consumer Affairs (DACS), an agency that has been working with FDEP for a number of years to increase agricultural pollution control. The document “Florida’s Agricultural Water Policy” (FDACS, July 2003) defines the policy of the state regarding water quality: “Agricultural production practices should be protective of surface and ground water quality and employ as many appropriate BMPs as are economically and technically feasible.” The Florida Watershed Restoration Act continues the “nonregulatory” approach to BMP implementation. However, the Act requires DACS to adopt, by rule, BMPs to reduce agricultural NPS pollution. If DEP verifies the BMPs are effective in reducing pollution, a farmer that has submitted a notice of intent to be covered by the DACS BMP rule and that has implemented the required BMPs will receive a presumption of compliance similar to that received by an urban developer who obtains a ERP permit. In addition, the legislature funded FDACS to research and implement BMP strategies. To date, FDACS and FDEP have produced a number of BMP manuals for specific agricultural programs including Citrus , Cow-Calf Programs, Agrichemical Handling, and Blended Fertilizer Plants. The BMP documents generally describe methods to control irrigation, fertilization (for nutrient load reduction as appropriate) and other land management practices to reduce pollutant lo ading. The documents also provide basic information about the agricultural practices to aid in the understanding of the pollution loading potential. Documents are available through FDACS ( www.floridaagwaterpolicy.com/publications.com ) or FDEP ( www.dep.state.fl.us/water/ nonpoint/pubs.htm ). Furthermore, DACS has adopted some of the BMP manuals and their associated checklists and record keeping requirements ( http://www.floridaagwaterpolicy.com/rules.html ).

Diffuse Sources
Three other types of sources are diffuse in nature, with no confined point of discharge: atmospheric groundwater and sediment/legacy sources.
Atmospheric deposition sources refer to pollutants that are contributed via dry deposition (e.g., leaf litter, airborne particles, etc.) and wet (i.e., via rainfall) pollutants. For both wet and dry deposition, pollutants are deposited on land and open water. The pollutants delivered to

3-40Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### land contribute to the parameter loads and concentrations in runoff measured in the field. There are studies in Florida on the expected pollutant concentrations of wet- and dry-fall (e.g., “Tampa Bay Atmospheric Deposition Study: Final Interim Report”, June 2000, TBNEP); however, a more precise set of data may need to be collected in the local area as rainfall and its pollutant load vary within Florida, especially where power plants, incinerators, or other industrial air discharges may occur. Section 6 provides additional information on wet-and dry-fall loads in the absence of locally collected data.

Groundwater sources refer to the influence of spring water or shallow aquifer water flowing diffusely into rivers, streams, lakes and estuaries. Groundwater and surface water flows in Florida are often interconnected and may be indistinguishable. Consideration of these sources was provided in subsections 3.2 and 3.3
Sediment/Legacy sources refer to the pollutant loading from bottom sediments in a stream, river, lake or estuarine sediments as a legacy of sedimentation from the past. While sedimentation and settling of particulates ar e natural phenomena, water bodies with higher particulate pollution loading may have a greater legacy of pollutants associated with the sediments. In general, the slower the velocities and/or the less flushing a system experiences, the greater the potential for sediment/legacy sources to be a significant percentage of the overall pollutant loading to the system. Therefore, information on the history of pollutant loading to the system, the net downstream velocity or flushing rate of the waterbody and the nature of the sediments are important to the characterization of the potential for pollutant loading of such sources. These sediment sources can cause SOD, nutrient cycling, and other potential adverse impacts.
As noted above, diffuse sources can be difficult to quantify for a particular waterbody. In the absence of local data, it is strongly recommended that a pollutant loading balance may be completed as part of the screening portion of the TMDL study. For this balance, an estimate for all possible pollutant inputs and outputs, plus storage, may be provided to determine significant sources, as illustrated in Figure 3.10 from the document “Charting the Course” produced by the Tampa Bay National Estuary Program (TBNEP, December 1996).

3-41Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Figure 3.10 Existing Annual Nitrogen Loadings to Tampa Bay by Bay Segment (1992-1994 Average)

3-42Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# SECTION 3 REFERENCES

American Society for Testing and Materials. 1997a. D 3978- 80: Standard practice for algal growth potential testing With Selenastrum capricornutum : West Conshohocken, Pa., Annual Book of ASTM Standards, v. 11.05, p. 29–33.

American Society for Testing and Materials. 1997b. E 1295-89: Standard guide for conducting three-brood, renewal toxicity tests with Ceriodaphnia dubia : West Conshohocken, Pa., Annual Book of ASTM Standards, v. 11.05, p. 626–644.

American Society for Testing and Materials. 1997c. E 1706-95b: Standard test methods for measuring the toxicity of sediment-associated contaminants with fresh water invertebrates: West Conshohocken, Pa., Annual Book of ASTM Standards, v. 11.05, p. 1138–1220.

Bedient, P.B. and W.C. Huber. 1992. Hydrology and Floodplain Analysis

. Brown, D.A., and Parsons, T.R. 1978. Relati onship between cytoplasmic distribution of mercury and toxic effects to zooplankton and chum salmon, Oncorhynchus keta , exposed to mercury in a controlled ecosystem: Journal of the Fisheries Research Board of Canada, v. 35, p. 880–884.

Buchanan, T.J. and W. Somers. 1968. “Stage measurement at gaging stations.” USGSTWRI Book 3. Chapter A7.

Buchanan, T.J. and W. Somers. 1969. “Discharge measurements at gaging stations.” USGS-TWRI Book 3 . Chapter A8.

Carlson, R. E. 1977. A trophic state index for lakes. Limnology and Oceanography 22:361:369.

Carlson, R. E. 1980. More complications in the chlorophyll-Secchi disk relationship. Limnology and Oceanography 25:378:382.

Carlson, R. E. 1983. Discussion on “Using di fferences among Carlson’s trophic state index values in regional water quality assessment”, by Richard A. Osgood. Water Resources Bulletin. 19:307-309.

Carter, R.W. and J. Davidian. 1968. “General procedure for gaging streams.” USGS-TWRI Book 3 . Chapter A6.

CDM. 1989. City of Daytona Beach Stormwater Master Plan.

CDM. 1991. SWMM RUNOFF, TRANSPORT, and EXTRAN Applications.

CDM. 1992. City of Jacksonville Master Stormwater Management Plan.

CDM. 1994. Watershed Management Model.

CDM. 1995. Tomoka River Watershed Management Plan for Volusia County.

3-43Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Couch, J.A. 1975. Histopathological effects of pesticides and related chemicals on the livers of fishes, in Ribelin, W.E., and Migaki, G., eds., Pathology of Fishes: Madison, Wis., University of Wisconsin Press, p. 559–584.

Cuffney, T.F., Gurtz, M.E., and Meador, M.R. 1993. Guidelines for the processing andquality assurance of benthic invertebrate samples collected as part of the National WaterQuality Assessment Program: U.S. Geological Survey Open-File Report 93-407, 80 p.

EPA. 1983. Nationwide Urban Runoff Program.

EPA. 1985. Rates Constants, and Kinetics Formulations in Surface Water Quality Modeling (Second Edition).

EPA. 1986. “Forecasting onsite soil adsorption failure rates.” EPA/600/2-86/060.

ERD. 2003. Evaluation of Alternative Stormwater Regulations for Southwest Florida.

ERD. 2006. Evaluation of Current Stormwater Design Criteria within the State of Florida.

Finger, S.E., and Bulak, J.S. 1988. Toxicity of water from three South Carolina rivers to striped bass: Transactions of the American Fisheries Society, v. 117, p. 521–528.

Harper, H. 1992. Estimation of Stormwater Loading Rate Parameters for Central and South Florida.

Health and Rehabilitative Services. 1989. City of Jacksonville, Storm Water Improvement Management (SWIM) Program.

Huber, W and R. Dickinson. 1992. US EPA SWMM Users Manual.

Huckins, J.N., Manuweera, G.K., Petty, J.D., Mackay, Donald, and Lebo, J.A. 1993. Lipidcontaining semipermeable membrane devices for monitoring organic contaminants in water: Environmental Science and Technology, v. 27, p. 2489–2496.

Kaiser, K.L.E., and Palabrica, V.S. 1991. Photobacterium phosphoreum toxicity data index: Water Pollution Research Journal of Canada, v. 26, p. 361–431.

Karr, J.R. 1981. Assessment of biotic integrity using fish communities: Fisheries, v. 6, p. 21–
27.

Maidment, D.R. 1993. Handbook of Hydrology.
Meador, M.R., Cuffney, T.F., and Gurtz, M.E. 1993. Methods for sampling fish communitiesas part of the National Water Quality Assessment Program: U.S. Geological Survey OpenFile Report 93-104, 40 p.

National Resource Conservation Service (NRCS, formerly SCS). 1985. National Engineering Handbook. Section 4 Hydrology.

3-44Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Naumann, E. 1929. The scope and chief problems of regional limnology. Int. Revue ges. Hydrobiol. 21:423.

Novotny, V. 2004. “Simplified Databased Total Maximum Daily Loads, or the World is LogNormal.” ASCE Journal of Environmental Engineering , 130(6), pp. 674-683.

Porter, S.D., Cuffney, T.F., Gurtz, M.E., and Meador, M.R. 1993. Methods for collecting algal samples as part of the National Water-Quality Assessment Program: U.S. Geological Survey Open-File Report 93-409, 39 p.

Rutledge, A.T. 1998. Computer programs for describing the recession of ground-water discharge and for estimating mean ground-water recharge and discharge from streamflow records—Update. USGS Water-Resources Investigations Report 98–4148. U.S. Geological Survey.

SFWMD. 2004. Environmental Resource Permit Information Manual. Volume IV.

SJRWMD. 1988. A Guide to SCS Runoff Procedures. TP 85-5.

Snedecor, G.W. and W. Cochran. 1973. Statistical Methods

.
Stegeman, J.J., Brouwer, M., Di Giuilo, R.T., Förlin, Lars, Fowler, B.A., Sanders, B.M., and van Veld, P.A. 1992. Molecular responses to environmental contamination: Enzyme and protein systems as indicators of chemical exposure and effect, in Huggett, R.J., Kimerle, R.A., Mehrle, P.M., Jr., and Bergman, H.L., eds., Biomarkers:

Thomas, J.A.; Bovee, K.D. 1993: Application and testing of a procedure to evaluate transferability of habitat suitability criteria. Regulated Rivers: Research and Management 8 : 285–294.

Thomas, P. 1990. Teleost model for studying the effects of chemicals on female reproductive endocrine function: Journal of Experimental Zoology, v. 4, p. 126–128.

United States Department of the Interior - Bureau of Reclamation. 2001. Water Measurement Manual

.

USGS and U.S. Atomic Energy Commission . 1967. Techniques of Water Resources Investigations of the United States Geological Survey.

USGS. 1996. Estimation of evapotranspiration in the Rainbow Springs and Silver Springs Basins in North-Central Florida. USGS WRI 96-4024.

USGS. 1996. Evapotranspiration from successional vegetation in a deforested area of the Lake Wales Ridge, Florida. USGS Water-Resources Investigations Report 96-4244.

Note: A number of Internet addresses are identified for data sources in the section and in Appendix 3A.

3-45Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



###   

3-46Appendix 3ADATA TABLETable 3A: FDEP TMDL Protocol: Example of Inventory Data TableData CategoryDataSourceDate orFormatOriginPeriod of RecordBiologyHabitat Suitability Curvehttp://www.swfwmd.state.fl.us/documents/reports/files/peace%20river%20review2.pdf,http://www.doc.govt.nz/Publications/004~Science-andResearch/Science-for-Conservation/PDF/sfc231.pdfVariesTestReportTrophic State Indexhttp://dipin.kent.edu/tsi.htmVariesTextReportBiological Assessment Techniqueshttp://www.epa.gov/owow/monitoring/rbp/wp61pdf/ch_02.pdf,http://ma.water.usgs.gov/fhwa/products/ofr99-240.pdf,http://www.nmfs.noaa.gov/habitat/ecosystem/habitatdocs/efhwkshpdoc.PDFVariesTextReportClimate and MeteorologyRainfallhttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7; http://www.noaa.org/;http://www.ncdc.noaa.gov/oa/ncdc.htmlVariesTextNational Climatic Data Center; National Oceanic and AtmosphericAdministration;Northwest Florida Water Management District; Suwannee River WaterManagement District; St. Johns River Water Management District; Southwest FloridaWater Management District; South Florida Water Management DistrictTemperaturehttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7; http://www.noaa.org/;http://www.ncdc.noaa.gov/oa/ncdc.htmlVariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictSolar Radiationhttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7; http://www.noaa.org/;http://www.ncdc.noaa.gov/oa/ncdc.htmlVariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictWind Speedhttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7; http://www.noaa.org/;http://www.ncdc.noaa.gov/oa/ncdc.htmlVariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictQuestions/CommentsPage 7, D:\My Documents 2\msword\TMDL Protocol Document\Appendix_3A.xls, 7/25/2006Appendix 3ADATA TABLETable 3A: FDEP TMDL Protocol: Example of Inventory Data TableData CategoryDataSourceDate orFormatOriginPeriod of RecordQuestions/CommentsPan evaporationhttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7; http://www.noaa.org/;http://www.ncdc.noaa.gov/oa/ncdc.htmlVariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictGroundwater Models and DataSink Holeftp://ftp.dep.state.fl.us/pub/gis/data/--Point shape file, UTM meterNoneGroundwater wellshttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictPotentiometric Surfacehttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictRechargeftp://ftp.dep.state.fl.us/pub/gis/data/; http://sjr.state.fl.us--Point shape file, UTM meterSpatial Distribution of Recharge in Surficial AquiferReport on Floridan AquiferUSGS #1403-G, Frederick W. Meyer,http://sofia.usgs.gov/publications/papers/pp1403g--htmlReportPage 7, D:\My Documents 2\msword\TMDL Protocol Document\Appendix_3A.xls, 7/25/2006Appendix 3ADATA TABLETable 3A: FDEP TMDL Protocol: Example of Inventory Data TableData CategoryDataSourceDate orFormatOriginPeriod of RecordQuestions/CommentsHydrologyHydrographic basinftp://ftp.dep.state.fl.us/pub/gis/data/;http://www.usgs.gov/;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7;2003Polygon shape file, UTM meterNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictBathymetryftp://ftp.dep.state.fl.us/pub/gis/data/;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7;--Polygon and point shape file,UTM meterLine and areas.Land UseLanduseftp://ftp.dep.state.fl.us/pub/gis/data/; http://www.sfwmd.gov;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7;--Polygon shape file, UTM meterExisting and Future Landuse; Northwest Florida Water Management District;Suwannee River Water Management District; St. Johns River Water ManagementDistrict; Southwest Florida Water Management District; South Florida WaterManagement DistrictRoadsftp://ftp.dep.state.fl.us/pub/gis/data/;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7;2003Arc shape file, UTM meterNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictAerial Photogrametryhttp://data.labins.org/2003/MappingData/DOQQ/doqq.cfm;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7;1999Mr. Sid1-meter by 1-meter resolution; Northwest Florida Water Management District;Suwannee River Water Management District; St. Johns River Water ManagementDistrict; Southwest Florida Water Management District; South Florida WaterManagement DistrictNon-Point Source PollutionAgriculturehttp://www.dep.state.fl.us/water/nonpoint/VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictPage 7, D:\My Documents 2\msword\TMDL Protocol Document\Appendix_3A.xls, 7/25/2006Appendix 3ADATA TABLETable 3A: FDEP TMDL Protocol: Example of Inventory Data TableData CategoryDataSourceDate orFormatOriginPeriod of RecordQuestions/CommentsBest Management Practiceshttp://www.dep.state.fl.us/water/nonpoint/VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictPermitGroundwater/Surfacewater/Stormwater/Wetlandhttp://www.dep.state.fl.us/secretary/info/permitting.htm;http://www.srwmd.state.fl.us/services/permitting/default1.htm;https://permitting.sjrwmd.com/epermitting/jsp/start.jsp;http://www.swfwmd.state.fl.us/permits/;http://www.sfwmd.gov/site/index.php?id=25VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictPoint-Source PollutionPublic Facilities (Wastewater/Water TreatmentFacilities)http://www.dep.state.fl.us/secretary/info/permitting.htm;http://www.srwmd.state.fl.us/services/permitting/default1.htm;https://permitting.sjrwmd.com/epermitting/jsp/start.jsp;http://www.swfwmd.state.fl.us/permits/;http://www.sfwmd.gov/site/index.php?id=25VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictIndustrial Facilitieshttp://www.dep.state.fl.us/secretary/info/permitting.htm;http://www.srwmd.state.fl.us/services/permitting/default1.htm;https://permitting.sjrwmd.com/epermitting/jsp/start.jsp;http://www.swfwmd.state.fl.us/permits/;http://www.sfwmd.gov/site/index.php?id=25VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictSeptic Tankhttp://www.dep.state.fl.us/secretary/info/permitting.htm;http://www.srwmd.state.fl.us/services/permitting/default1.htm;https://permitting.sjrwmd.com/epermitting/jsp/start.jsp;http://www.swfwmd.state.fl.us/permits/;http://www.sfwmd.gov/site/index.php?id=25VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictBest Management Practiceshttp://www.dep.state.fl.us/water/;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictPage 7, D:\My Documents 2\msword\TMDL Protocol Document\Appendix_3A.xls, 7/25/2006Appendix 3ADATA TABLETable 3A: FDEP TMDL Protocol: Example of Inventory Data TableData CategoryDataSourceDate orFormatOriginPeriod of RecordQuestions/CommentsSoils/GeotechnicalSoils Seriesftp://ftp.dep.state.fl.us/pub/gis/data/;http://www.nrcs.usda.gov/2003Polygon shape file, UTM meterSoil Series given by the National Soil Conservation ServiceSurface Water Models and DataFloodplainftp://ftp.dep.state.fl.us/pub/gis/data/; http://www.fema.gov/VariesPoint shape file, UTM meterNoneFlowhttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictSurface Waterftp://ftp.dep.state.fl.us/pub/gis/data/;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7VariesPolygon shape file, UTM meterDelineation of surface water classesGaging stationsftp://ftp.dep.state.fl.us/pub/gis/data/;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7VariesPoint shape file, UTM meterNoneWetlandsftp://ftp.dep.state.fl.us/pub/gis/data/;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7;http://www.nwi.fws.gov/VariesPoint shape file, UTM meterNonePage 7, D:\My Documents 2\msword\TMDL Protocol Document\Appendix_3A.xls, 7/25/2006Appendix 3ADATA TABLETable 3A: FDEP TMDL Protocol: Example of Inventory Data TableData CategoryDataSourceDate orFormatOriginPeriod of RecordQuestions/CommentsStructure(s)http://www.usace.army.mil/;http://www.dot.state.fl.us/rddesign/;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7VariesVariesBridges, Drainage.Stagehttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management District; Southwest Florida WaterManagement District; South Florida Water Management DistrictTopographyTopography/Surveyhttp://data.labins.org/2003/MappingData/USGS_Download/quad.cfm?quad=2402;http://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html; http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7Variestif5-ft contourWater Quality Models and DataPesticide leaching potential in aquifersftp://ftp.dep.state.fl.us/pub/gis/data/Not AvailablePoint shape file, UTM meterNoneImpaired Water 303dftp://ftp.dep.state.fl.us/pub/gis/data/1998Polygon shape file, UTM meterNoneOutstanding Florida Waterftp://ftp.dep.state.fl.us/pub/gis/data/Not AvailablePolygon shape file, UTM meterNonePage 7, D:\My Documents 2\msword\TMDL Protocol Document\Appendix_3A.xls, 7/25/2006Appendix 3ADATA TABLETable 3A: FDEP TMDL Protocol: Example of Inventory Data TableData CategoryDataSourceDate orFormatOriginPeriod of RecordQuestions/CommentsWater Qualityhttp://www.state.fl.us/nwfwmd/isb/isb.htm;http://www.srwmd.state.fl.us/;http://sjr.state.fl.us/programs/plan_monitor/gis/docs/themes.html;http://www.swfwmd.state.fl.us/data/;http://www.sfwmd.gov/site/index.php?id=7;http://www.epa.gov/storet/VariesTextNorthwest Florida Water Management District; Suwannee River Water ManagementDistrict; St. Johns River Water Management F21District; Southwest Florida WaterManagement District; South Florida Water Management DistrictNotes:1This table provides an overview of typical data considered for TMDL evaluations. It is meant as a guide but not an exhaustive list of all data and sources.2Local county, city, and water control district data should also be considered to augment data.3Other local and anecdotal data (citizen input and public meetings) should also be considered.7/25/2006 15:03D:\My Documents 2\msword\TMDL Protocol Document\[Appendix_3A.xls]InventoryPage 7, D:\My Documents 2\msword\TMDL Protocol Document\Appendix_3A.xls, 7/25/2006Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Appendix 3B

TIDAL PRISM CALCULATIONS

3B-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Tidal Prism Calculation Method

Flushing may be analyzed by either of the following methods:

A. The Fraction of Freshwater Method (EPA, 1985) is a six-step method as follows:

1. Graph the estuarine salinity profile by constructing a graph showing salinity on the yaxis and the distance from the head of the estuary on the x-axis.

2. On the graph, divide the estuary into segments. The segmentation should be such that in areas where there are steep salinity gradients, the segments will be smaller; and in areas where salinity is constant, the segments may be longer.

3. Calculate each segment’s fraction of freshwater by:

f i 

### = (S s 

### – S i 

### )/ S s;



### where f i 

### is the fraction of freshwater in segment i, S s 

### is the salinity of local seawater, and S i 

### is the mean salinity for segment i.

4. Calculate the quantity of freshwater in each segment by:

W I 

### = f i 

### x V i 

### ;

where W i 

### is the quantity of freshwater in segment i, and V i 

### is total volume of segment i at mean tide.

5. Calculate the exchange time (flushing time) for each segment by:

T i 

### = W i 

### / R;

where T i 

### is the segment flushing time in tidal cycles, and R is the river discharge over one tidal cycle.

6. Calculate the entire estuary flushing time by summing the exchange times for the individual segments:

T f 

### = Σ T i 

### , i=1 to n;

where T f 

### is the estuary flushing time, in tidal cycles, and n is the number of segments.

B. The Tidal Prism method does not require knowledge of the salinity distribution. The method uses the volume of water in the estuary at low tide, the volume of water in the estuary at high tide, and the volume of freshwater flowing into the estuary over one tidal cycle to compute the flushing time, as follows:

3B-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### 1. Use streamflow data to estimate the volume of freshwater (V f 

### ) flowing into the estuary during a tidal cycle (one rising tide and one falling tide).

2. Use tide charts and physical dimensions to estimate the difference in volume of water (V p 

### , the prism) in the estuary between high and low tide.

3. Calculate the flushing time as:

T f 

### = T x V /(V t 

### + V r 

### );

where T is the time of the tidal cycle (typically 12.5 or 25 hours), V is the total volume of water in the estuary, V t 

### is the difference in estuarine volume between high and low tide, and V r 

### is the volume of freshwater inflow (streamflow rate x T).

3B-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Appendix 3C

BACTERIA CHARACTERIZATION

3C-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Appendix 3C Fecal Coliform Bacteria Characterization and Evaluation

3.C.1 Background

Monitoring of ambient waters for microbial pathogens (microorganisms that cause disease in humans) in Florida and across the United States is conducted to assess the suitability of the waters to support a variety of beneficial uses as described in the federal Clean Water Act of 1972 (CWA). In the State of Florida, surface waters are classified as one of the following:

(i) Class I (Potable Water Supply);

(ii) Class II ( Shellfish Propagation or Harvesting );

(iii) Class III ( Recreation, Fish, and Wildlife) ;

(iv) Class IV (Agricultural Water Supplies); and

(v) Class V (Navigation, Utility and Industrial Use) – Although there are no waters currently classified as Class V in Florida.

In addition, the classification of Outstanding Florida Waters (OFW) is designated for water quality protection.

For practical reasons, regulatory agencies throughout most of the United States, including the FDEP, have historically used and continue to use fecal coliform bacteria (FC) as an indicator to assess the potential of the existence of pathogenic microorganisms (bacteria and viruses) in those waters. FC exists in the intestinal tracts of all warm-blooded animals, including humans, and is discharged in their feces in large numbers. However, the presence of FC bacteria does not definitely prove the presence of pathogenic microorganisms, but it does provide an indication of the probability that such pathogens might be present. Elevated levels of FC in surface waters may trigger the regulatory agencies to close recreational beaches to avoid human contact with the suspect waters and to close shellfish harvesting areas to avoid consumption of pathogens, thereby reducing the possibility of exposure to a waterborne disease. FC data are commonly available in most databases (e.g., STORET).

Other indicators have been and are being investigated by agencies including US EPA, Food and Drug Administration (FDA), and the USGS. These other indicators are documented in example references and include:



### 3C-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Escherichia Coliform (E. coli)

 

### Fecal Streptococci (FS)

 

### Atypical Coliform (AC)

 

### Total Coliform (TC)

 

### Enterococci

For Class I and Class III waters, the applicable State of Florida water quality standard with respect to FC is a 30-day geometric mean of 200 MPN/100 ml (based upon a minimum of 5 to 10 ambient water samples in a 30-day period), and any single sample is not to exceed 800 MPN/100 ml. The term “MPN” is the abbreviation for “most probable number”. In addition, no more than 10 percent of the samples can exceed 400 MPN/100 ml. The Class II limits are more restrictive, with a maximum geometric mean of 14 MDN/100 ml, and no more than 10 percent of samples can exceed 43 MPN/100 ml. Exceedance of applicable ambient water quality standards for FC is an issue for ambient waters throughout the entire Unites States (US) (CDM, 2001), and in Florida approximately 17 percent of impaired waters are listed for pathogens(www.dep.state.fl.us/water). WBIDs defined as impaired in Florida are either “partiallysupporting” or “not-supporting” designated uses per Section 305(b) of the CWA. Ambient water bodies classified as “impaired” are su bject to development and implementation of a Total Maximum Daily Load (TMDL) for each pollutant listed as the cause of the impairment.

This FC Bacteria Characterization and Evaluation Appendix focuses on the characterization and evaluation of FC bacteria. It is necessary to identify potential sources of FC for an accurate TMDL and for a cost-effective implementation. Typically, point sources are representative of municipal wastewater treatment facilities, while nonpoint sources are often representative of stormwater runoff (urban, rural, and agricultural), septic tank seepage, and sanitary sewer overflows (SSOs). In order to limit or reduce FC levels and comply with the applicable FC water quality standard, the TMDL data evaluation may need to include data coordinated with field and laboratory investigations to identify and characterize FC sources and locations. The investigations may also include processes to differentiate human from non-human FC sources, as well as differentiation between types of animals.



## 3.C.2 Goals

The goals of this appendix are to:

 

### Summarize the types of microorganisms ty pically measured in laboratory analyses as indicators of pathogenicity and provide references.

 

### Summarize alternative methods used for identifying general sources of FC, such as: failing septic tanks, SSOs, illicit connections, illegal discharges (e.g., “blue water” dumping), agricultural practices, and domesticated animals (horses, chickens, pigs, cows), pet waste, and wildlife (ducks, geese, raccoons, etc.).

 

### Summarize alternative biological and chemical methods used to track potential FC

sources.



### 3C-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Document this information for a potential protocol to assist in FC source identification.

 

### Identify modeling issues for consideration.



## 3.C.3 Sources and Magnitudes

Monitoring programs throughout the Unites States have documented the high variability of FC levels in ambient water samples, even at the same monitoring location from one sampling period to another. Numerous factors are responsible for this, including wet weather variations in stormwater runoff, antecedent moisture conditions, sewer infiltration and inflow, and septic tank performance and maintenance.

Pitt (2004) published a report with urban stormwater runoff statistics from the NPDES MS4 monitoring programs. The report summarizes measured runoff concentrations from 10 years of monitoring in 66 urban areas within 17 states. For FC, Pitt reports a median value band of 8,000 to 11,000 MPN/100 ml for residential land use, and 4,300 to 5,000 MPN/ml for commercial land use.

Other sources have reported mean (average) FC levels for stormwater runoff in urban areas. The mean values are higher than the m edian or geometric mean values because they are skewed by the highest measured values.

Pitt (1998) reported a mean 1 

### count of 20,000 MPN/100ml using the results of the Nationwide Urban Runoff Program (NURP) completed in the 1980s by the EPA (1983). Under the NURP, more than 2,220 storm events were monitored at 28 urban locations across the U.S. Pitt (1998) reported on 25 st udies conducted since the NURP evaluation and reported a mean coliform concentration of 20,000 MPN/100ml. In Florida, Tampa was a NURP site and the mean value for 15 samples was 24,400 MPN/100 ml. The Center for Watershed Protection (Schueler, 1999) evaluated 34 urban monitoring programs and reported a mean of 15,000 MPN/100ml.

There are numerous sources of FC in urbanized and rural watersheds. Human sources may include SSOs, illicit connections, illegal dumping, septic systems, landfills, marinas, pumpout facilities, and inadequately treated direct discharges. Examples of non-human sources include waterfowl, pets, livestock (including small farms), rats, raccoons, pigeons, gulls, otters, beavers, and other animals commonly found along urban and rural
streams. Table 1 compares the daily discharge rate of FC for humans and typical urban/domesticated animals.

1 It should be noted that coliform data are not nor mally distributed. Consequently, mean values are frequently quite different from the median, or the geometric mean. Unfortunately, most authors cite only one summary statistic maki ng inter-study comparisons difficult.



### 3C-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 1 Daily Discharge of Fecal Coliform (Counts/day/individual)

Waterfowl 3.97E+09 Dog 3.34E+09
Duck 2.25E+09
Human 2.07E+09

Cow 1.61E+09
Cat 5.38E+08
Rat 5.81E+06

Source: Geldrich et al., 1962; Godfrey, 1992; Pitt, 1998)



### Two studies (Bannerman et al, 1993. Steuer et al., 1997) indicated that residential lawns, driveways and streets are a major source of bacteria in runoff. Both studies also indicated that end-of-pipe concentrations were an order of magnitude higher than the runoff source, suggesting that either illicit connections from sanitary sewer lines are a major contributor to the problem, or the st ormwater conveyance system itself was a major source.

Genetic studies (Alderiso et al., 1996; Trial et al., 1993) for some areas have indicated that large percentages of FC in stormwater was from non-human sources, further suggesting that the conveyance system itself may be a significant contributor. Indeed, studies by Burton et al. (1987) and Marino and Gannon (1991) have confirmed that FC bacteria can both survive and reproduce in the highly organic sediments frequently found in stormwater ditches and retention ponds, and growth in closed stormwater systems (dark, warm water, nutrients) has been documented for some Best Management Practice (BMP) evaluations.

Recent evidence also indicates that FC c an survive and even multiply in the sediments after runoff events. Surcharged stream c onveyance systems that cause streambed erosion may actually re-suspend coloni es deposited during previous events.



## 3.C.4 Source Investigation Process

The objectives of the source investigation process are first to identify locations, land uses, and/or specific discharges of FC bacteria; second to differentiate human sources from non-human sources; and third to identify the specific animal species responsible for the FC, if necessary.

Some sources may be present in runoff during storm events, while others may be present in both runoff and dry weather baseflow. A hydrograph separation technique is are presented in Section 3 of the TMDL Protocol if the practitioner needs to evaluate the FC data versus flow conditions. Examples of runoff FC can include SSOs, pet waste in parks, and/or farm pastures. An example of a source which would be present in both runoff and baseflow is a continuous illicit discharge. While the initial effort should focus on the elimination of human sources, “winds hield” and sometimes marine (boat) surveys



### 3C-5Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### should be conducted early in the source identification program to identify obvious human and non-human sources. These obvious sources should be eliminated when identified, if possible (e.g., buildup of pet wastes at or near bathing beaches, apparent septic tank seepage). Non-human sources should be investigated after the human sources have been identified and eliminated, if possible, al though some sources may be from natural fauna and cannot be eliminated. Use of existing data can help focus field work by prioritizing high probability source areas.

Although some sources will also contribute during dry weather, the protocol is intended primarily for identification of significant urban sources contributing during wet weather and runoff events. The purpose of the initial survey is to identify probable major sources prior to resorting to additional sampling involving one or more chemical or biological
tracers.

One source that may be particularly difficult to isolate is the re-suspension of FC that survive and reproduce in the sediments of the stormwater conveyance system and treatment ponds. Areas of high sediment deposition may be suspect, and measurement of coliform in the sediment instead of the water column may be required to isolate this

source.

To assist in this investigation, a number of procedures and methods are currently in use. Some are basic and complementary to progressively more complex investigations, and others provide an alternative mechanism to identifying specific sources of FC. The following process is suggested.

Step 1 - Compile Data : The source investigation should begin by compiling available watershed and receiving water specific coli form data (e.g., FDEP, STORET, USGS, and local programs) and cataloging the data into dry and wet weather data. Geometric means should be developed for each station (or subbasin) and the results entered into a GIS database or plotted on a map of the sub-basins. Geographic areas where either wet or dry weather bacteria concentrations are unusually high should be targeted for further inspection. The initial effort should be identification of the human sources.

Step 2 - Evaluate Domestic Wastewater Treatment Systems : The second step should be to perform a detailed evaluation of domestic wastewater treatment systems. Sub-basin characteristics such as know n data on septic tanks and permits, streams (hydrography) and wetlands, land use and/or aerial photography (different time periods can be correlated to data trends), SSO records for overflows, WWTP outfalls, and if necessary sanitary system pipes and pump stations, maintenance (for both regional sewer and septic tanks), suitability of soils for septic systems, and proximity to waterbodies should be evaluated for potential sources and compared to the coliform database. If available, pump-out records for septic systems and/or complaints about malfunctioning septic systems should be investigated although these are rarely available. GIS applications can assist in locating and prioritizing the number of potential sources and focusing the source investigation. Areas which exhibit both a high source potential and high historical coliform counts should be targeted for additional windshield surveys and/or follow-up FC sampling.



### 3C-6Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Step 3 - Identify Non-Human Sources : After identifying the more apparent human sources, the source identification should target the remaining areas of elevated FC counts using the same basic methodology. Farms, kennels, and equestrian centers should be identified and mapped. Waterbodies with high known densities of waterfowl should be identified. Public parks should be evaluated for density of urban wildlife and the intensity of use as pet walks. Animal control authorities may be able to identify areas of high animal density, and pet waste ordinance enforcement may assist with specific WBIDs.

Step 4 - Design a Follow-up Monitoring Program : If necessary, the next step is to design a follow-up monitoring program to confirm the source(s) of FC bacteria. The monitoring plan can be designed to isolate a source by progressively sampling at upstream locations until the source is identified. The follow-up program will likely involve sample collection and lab analyses of addition al tracer chemicals that are discussed below.



## 3.C.5 Indicators, Tracers, and Differentiators

A variety of chemical and biological methods may be used to indicate, trace, and/or differentiate bacteria and sources. While most tracers detect the presence of either treated water or “used” potable water (targeting a parameter that would only be present in wastewater), some are direct measures of FC bacteria as described below. Examples of direct evidence wastewater tracers include caffeine and pharmaceutical drugs. Currently there is no tracer that will directly distinguish between a septic tank source and wastewater treatment facility, although Pitt (2004) has identified potential indicators such as the ammonia to potassium ratio (NH 3 

### /K).



### 3.C.5.1 Biological Methods

Microbial Source Tracking (MST) Collectively referred to as “microbial source tracking” (MST), the fundamental premises of these methods are that:

(1) FC of ambient waters can be traced back to the originating source;

(2) These sources can further be characterized as being either human or animal; and

(3) Identification of the specific animal species is possible.

Currently, MST is being applied at the international, national, regional, state, and local level, with research continuing in the development of more reliable, faster, practical, and cost-effective methods. All current MST methods, which are generally classified as microbiological, genotypic, or phenotypic have the common goal of characterizing groups of microorganisms that can be used as FC indicator organisms and can further lead to identification of a specific source species. Specifically, the methods are designed to detect a specific microorganism “signature” in an effort to distinguish and identify its originating source (for example, human, dog, goose, duck, deer, raccoon, etc.). Microorganisms under consideration include specific FC bacteria (e.g., Escherichia coli,



### 3C-7Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Citrobacter freundi, Enterobacter aerogenes, Klebsialla pneumonia), fecal streptococci (e.g., Enterococcus avium, Enterococcus faecalis, Enterococcus faecium, Enterococcus gallinarum, Streptococcus bovis, Streptococcus equines), animal specific bacteriophage (e.g., male bacteriophage), human entero viruses (e.g., enteroviruses, adenoviruses), and bacteroides-Prevotella.

Biochemical approaches attempt to identify unique characteristics of different microorganisms and the methods based on these approaches are called “phenotypic’ (Vikas et al, 2004; Meays et al, 2004). The more popular phenotypic MST methods include: antibiotic resistance analysis (ARA) (Wiggins, 1996; Harwood et al., 2000; Hagedorn et al., 1999; Geary and Davies, 2003), carbon source utilization (CSU) (Griffith et al., 2003); F + 

### coliphage serotyping (Messer, 2004), host-specific indicators (for example, Enterococcus avium) (Kuntz et al., 2004); and bacteriophage indicators (Burkhardt et al., 1998; Noble et al., 2003).

AC/TC Ratio Rationale : Atypical coliform bacteria have been identified by several researchers as an additional indicator. Brion (2003) “has ident ified a relatively inexpensive tool for indicating microbial quality in watersheds utilizing the conventional total coliform test, comparing the relative concentration of different colonies that form on a membrane filter fed by m-Endo media. These bacterial colonies can be classified into 3 types: typical (TC), atypical (AC), and background. The ratio of the concentrations of AC colonies to those of TC is related to water quality, fecal loadings, and fecal age. The AC/TC ratio relies upon shifts in populations between indigenous and introduced bacteria, with the indigenous bacteria providing a baseline against which the concentrations of the introduced are evaluated. When the AC/TC ratio is low (<5), fresh fecal material is in the water and pathogen risk can be expected to be higher. As time passes, the AC/TC ratio increases (>20) and can be related to healthier water quality conditions. Different types of runoff have different AC/TC values with human sewage at the lowest end of the spectrum with a value of 1.5 under normal conditions.”

FC/FS Ratio Rationale : Traditionally, the ratio of FC to fecal streptococci (FS) had been used to assess whether the source is likely to be human or animal (APHA, 1998). However, guidance in the form of testing methods has been unclear on this point and water resources managers have been discontinuing the use of this ratio. Feachem (1975) reports that the ratio is constantly changing with time due to differing rates of die-off between the two bacterial groups. If the source is human, the ratio will start out high and decrease with time. In contrast, a non-human source begins with a low ratio, which increases with time.

As a result, testing results are only valid if taken within 24 hours following deposition of feces. Consequently, the limitations of test ing prevent practical application to storm water monitoring field studies.

Coprostanol Rationale : Coprostanol is a fecal sterol that exists in human and animal wastes. It exists as a series of chemical isomers. The ratio of certain isomers is relatively specific for



### 3C-8Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### humans. Because of coprostanol’s affinity for particulates, coprostanol measurements are typically performed on sediments. Coprosta nol is more persistent in sediments than other indicators such as Linear Alkylbenze Sulfonates (LAS). Sediment concentrations in excess of 0.1 mg/kg and containing the specific mix of isomers indicate human sewage

sources.

Lab Issues : Coprostanol is not commonly analyzed by commercial environmental laboratories, although several universities and research organizations do conduct this
test.

DNA and RNA Rationale : More definitive source identification can be obtained by matching the genetic code of coliform bacteria found in stormwater or baseflow. Coliform bacteria are filtered from the suspect water source and incubated (Coastlines, 1998). A DNA pattern is obtained from ribosomal RNA of each isolate and compared to the DNA patterns of various sources. Large libraries of isolates have been developed for the scat of urban animals (pets, raccoons, beaver, migrating fowl etc.) and marine mammals. The similarity of the DNA patterns is used to assess the likelihood and variety of the source.

To some extent, the patterns remain consistent from region to region for a given source (Dr. Samadpour, personal communication). Therefore, within limitations, it is possible to use the DNA ribotype of a raccoon isolate from Florida, for example, to suggest a source of raccoon coliform in waters elsewhere.

Lab Issues : Once the candidate sources have been short-listed, local specimens can be collected and used to refine the testing. The cost of incubating coliform and preparing an RNA fingerprint from a local source is about $150 to $200 per coliform and higher. For a typical urban evaluation, approximately 200-400 coliform cells are isolated, incubated and their RNA mapped. Only a handful of research laboratories are capable of providing this type of analysis. The USGS began RNA ribotyping in metropolitan Atlanta in early 2000 (USGS, 1999-present).

Previous Studies : Genotypic or molecular methods are designed to obtain a specific microorganism’s DNA genetic sequence (commonly referred to as “DNA fingerprint”). These methods include host-specific 16S ribosomal DNA genetic markers (Bernhard and Field, 2000a), repetitive extragenic palindr omic-polymerase chain reaction or repPCR (Carson et al., 2003), ribotyping (Hartel et al., 2002), length heterogeneity-PCR or LH-PCR (Bernhard and Field, 2000b), terminal restriction fragment length polymorphism or T-RFLP (Bernhard and Field, 2000b), and pulse-filed gel electrophoresis or PFGE (Parveen et al., 2001).

Enteric Virus Rationale : Enteric viruses and pathogens have also been used as direct evidence of contamination with sanitary wastewater. Organisms such as coliphage and bacteroides that reproduce only in bacteria found in the human digestive system can be used as definitive tracers. FDA (Burkhardt et al., 1998) has identified male bacteriophage as a cost-effective indicator for human versus non-human sources.



### 3C-9Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Lab Issues: Specialized laboratories provide analysis of enteric viruses.

ARA The ARA uses the scat from the variety of animals along with a number of antibodies to identify a characteristic resistance pattern by animal type (Harwood, 2000; CDM, 2001).

Previous Studies : The ARA has been successfully applied in Atlanta (CDM, 2001), Denver (CDM, 2003), and other locations to identify potential human and nonhuman sources. In Atlanta, human, cat, dog, chicken, pig, cow, horse and wild animal scat samples were used with the antibodies to characterize sources for management plan controls. The resultant data were consistent with land use, animal types by area, soils and stream conditions, and age of septic and sani tary systems. Consideration for future enhancement included adding one or two more antibodies to improve confidence intervals, taking human samples from a stadi um where only human waste is expected, and potential differentiation for wild animals.



### 3.C.5.2 Chemical Methods

Surfactants Rationale : Surfactants are widely used in both domestic and industrial detergents and are commonly measured as Methylene-Blue Ac tive Substances (MBAS). However, the MBAS test is not specific to the LAS, the predominant class of anionic surfactants.

Lab Issues : MBAS is a commonly measured water quality parameter and is a useful tracer in the absence of naturally occurring in terferences. Direct measurement of LAS is a more complex analysis requiring infrared spectroscopy or gas chromatographic techniques and is not commonly analyzed by commercial environmental laboratories.

Previous Studies : In studies of the Mississippi River (Barber et al., 1995), interference from naturally occurring MBAS substances (e.g. humic acids) resulted in poor correlation between MBAS and direct measurement of LAS. Thus, direct testing for LAS is preferred over the more common MBAS measurement of surfactants. LAS degrades easily under aerobic conditions and can be measured in either aqueous or sediment samples. Results of the Mississippi River studies indicate aqueous concentrations ranging from 0.01 to 0.00005 mg/l and sediment concentrations ranging from 0.1 to 1 mg/kg downstream of major urban centers. Surfactants are present in domestic wastewater in the range of 1-20 mg/l (Standard Methods, 18 th 

### Edition). As with all of the non-specific tracers, the presence of LAS alone is not confirmatory for domestic sources, but is more likely with proximity to either a domestic or industrial wastewater source.

Caffeine Rationale : Caffeine is naturally present in coffee and is an additive in many soft drinks and food products, which makes caffeine a fairly specific tracer of domestic wastewater. Concentrations in municipal wastewater range from 20-300 ug/l.

Lab Issues : The USGS (NWQL, 1997) has modified the standard GC/MS technique developed for priority pollutants to achieve a method detection limit (MDL) of 0.02 ug/l



### 3C-10Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### for caffeine. The USGS is currently monitoring caffeine in the Atlanta area as part of their wastewater tracer study. Initial sampling showed caffeine in most samples.

EDTA Rationale : EDTA (ethylene diamine tetra-acetic acid) is widely used in domestic and industrial applications to solublize metals. Uses include bleaching agents in domestic laundry soaps and prevention of boiler scale in industry. It is also an additive to many food products. Like LAS and other non-specific tracers, its presence is suggestive of anthropogenic sources, but cannot differentiate sanitary wastewater from other types of

sources.

Fluoride Rationale : In some circumstances, fluoride may be a useful tracer. The American Dental Association recommends a concentration range of 0.7-1.2 mg/l in potable water for dental health and many communities add fluoride to potable water. Where potable water is fluoridated and where ambient fluoride concentrations are low, the presence of elevated fluoride values may be used to assist in identifying waters of anthropogenic origin. However, it should be noted that fluoride levels will also be elevated in grey water, car wash water and other non-sanitary sources.

Lab Issues : Fluoride is an inexpensive analysis commonly provided by commercial laboratories.

Previous Studies : Typical values for Birmingham, Alabama ranged from 0.8-1.0 mg/ for potable water, sanitary wastewater and septic tank effluent, compared to 0.031 mg/l for spring water. Industrial sources can be much higher, however, ranging from 12 mg/l for car wash water to 150 mg/l for radiator flush water in Birmingham.

Ammonia/Potassium Ratio Rationale : Dry-weather stormwater outfall flows typically indicate a non-stormwater source and water samples from these outfalls can be laboratory analyzed to confirm the identity of the source. If tests indicate that the water samples contain compounds commonly found in detergents, then the ratio of ammonia to potassium can be used as an indicator of sanitary wastewater contamination. Ratios of ammonia concentrations to potassium concentrations greater than 0.60 likely indicate the presence of sanitary wastewater (Pitt, 2001).

Lab Issues : Both ammonia and potassium are inexpensive analyses commonly provided by environmental laboratories.

Previous Studies : A search of EPA’s STORET database indicates Tracer concentration studies conducted in Birmingham, Alabama (Pi tt et al., 1993; Lalor, 1994) that included the ammonia/potassium ratio found that the mean ratio values for sanitary wastewater, septic effluent, and laundry wastewater were 1.7, 5.2, and 0.24, respectively. The mean ratios for spring water, treated potable water, and car wash water were 0.011, 0.018, and 0.006, respectively.



### 3C-11Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### 3C-12 Brighteners Rationale : Brightening agents used in laundry products have also been used as tracers for the detection of failing septic systems. These compounds fluoresce under ultravioletlight and can be detected in the field with portable fluorometers. However, other nonsanitary sources (such as laundries and car washing facilities) may introduce significant quantities of brighteners.

Lab Issues : There is no EPA approved methodology for the analysis of brighteners, and commercial environmental laboratories do not commonly provide this test. However, the fluorometric technique is expected to have a low per-sample cost. It has the added advantage that it can be conducted in the field, providing immediate results if a field fluorometer is available.

Isotopes Rationale : Although not widely used, the enrichment of isotope ratios of nitrogen (N 15 

### /N 14 

### ) and oxygen (O 18 

### /O 16 

### ) over a standard ratio have also been used (Aravena et al. 1993) to characterize the source of nitrogen. The ratio of heavier isotopes changes as nitrogen passes through trophic levels. Thus, it is possible to differentiate between “new” atmospheric nitrogen and nitrogen from fertilizer, or nitrogen from wastewater sources.

Lab Issues Commercial laboratories do not commonly provide this type of isotope analysis

.
Multiple Chemical Tracers The analytical cost of tracing the source of FC varies widely, although combining simple
tracers can result in an effective met hodology based on the “body of evidence”. One such protocol involving analysis of det ergents, ammonia and potassium was developed by Pitt (2004) and is reproduced as Figure 1 . This protocol is primarily for source identification of baseflow contamination measured at the end-of-pipe. A similar protocol could be developed depending on the ambient levels of fluoride, potassium, and ammonia and whether natural MBAS interferences exist.Florida Department of Environmental ProtectionJune 2006TMDL ProtocolVersion 6.0Task Assignment 003.03/05-0033C-13StartLand useIndustrial orindustrial/commercialResidentialUse industrial/commercial checklist(Pitt 1993)Check for dry-weather flowFlow?Recheck per permitrequirementsDetergent>0.25 mg/Lor Boron>0.35 mg/LFluorescence>25 mg/LFluoride>0.6 mg/LE.coli >12,000MPN/100mLor Enterococci>5,000MPN/100mLLikely naturalwater sourceLikely tapwater sourcePossiblewashwatercontaminationPossible sanitarywastewatercontaminationLikely irrigationwater sourceResultAmmonia/potassiumratio >1.0Fluoride>0.25mg/LYesNoYesNoNoNoNoNoYesYesYesYesYesNoFigure 1 Flow Chart for Identifying Base Flow Components Adapted from Pitt (2004)Parameter CheckFlow CheckLand UseFlorida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## 3.C.6 Modeling Issues for Consideration

Dry Weather : Dry weather or baseflow quantities (concentrations) can be estimated by evaluating the water quality data in conjunction with flow (or stage) and rainfall. These can also be varied seasonally (e.g., dry weather period during the wet season).

Wet Weather : Wet weather sources can vary from pet waste washoff from lawns and parks to SSOs and agricultural discharges. These are often variable, as is rainfall, and sensitivity analyses are recommended since SSO records are rarely available and the other sources can have great variability.

Decay and Transformation Coefficient : Often a “first-order loss” coefficient is applied to account for the cumulative loss over time of bacteria levels in receiving waters. It is important to note that this coefficient includes decay (die-off), transformation (e.g., FC to AC), and re-growth. Table 2 lists ranges for these first order loss rates.

Table 2 Typical First Order Loss Rates for Bacteria Modeling

Range of First-Order Loss Rates Coliform Type (1/day) Comments Source

Total coliform 1.0 - 5.5 Freshwater Thomann and Mueller, 1987

0.7 - 3.0 Seawater Thomann and Mueller, 1987

0.2 - 2.5 Lombardo, 1972

Fecal coliform 0.2 - 3.1 Lombardo, 1972

E Coli 0.08 - 2.0 Seawater Thomann and Mueller, 1987

Septic Tanks : Due to voluntary participation and cost, septic tanks often remain in service along lakes, wetlands, and creeks even when areas are sewered. Therefore, either WBID specific field reconnaissance for septic tanks should be completed and/or a sensitivity analysis should be performed using the WBID perimeter as septic tank coverage (i.e., all homes and buildings along th e stream or lake are on septic tanks). Failure rates are referenced in Section 3 of the TMDL Protocol.

SSOs : SSO data are often sparse and difficult to quantify. SSOs can be a major contribution during wet weather conditions and these loads can be a calibration parameter.

Animal Sources : Animal sources can be diffuse and random and/or concentrated and persistent (urban ducks and geese). Therefore, field confirmation is often important to define this input.



### 3C-14Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## 3.C.7 Conclusions

A source identification process based on the ev aluation of existing FC data coupled with development of GIS layer(s) to map probable sources has been presented. Other considerations for indicators of human and non-human sources have also been referenced. If the source(s) cannot be determined with existing data or through simple field inspections, it is recommended that simple and inexpensive chemical and biological tracers be measured to assist in identifying the source during dry and wet weather conditions.

An array of potential tracers was presented which may be used to identify the sources of FC bacteria and differentiators, and an example flow chart used by Pitt (2004) in Birmingham has been presented. A pilot study could be conducted to confirm the validity of the source investigation protocol by correlating the coliform counts with the concentrations of the tracer compounds. In the event that the simple tracers do not provide the source identification needed, then the more complex and expensive MST methods may be used. These have been used in a va riety of evaluations to identify likely

sources.

TMDL implementation plans should identify cost-effective practices and BMPs based on the magnitude and source of the FC indicator causing impairment. Often this is a plan to reduce human and controllable animal waste.



## 3.C.8 References

APHA, 1998. Standard Methods for the Examination of Water and Wastewater. 20 th


### Edition. American Public Health Association.

Bannerman, R., D. Owens, R. Dodds, and N. Hornewer. 1993. Sources of pollutants in Wisconsin stormwater. Water Science and Technology 28(3-5):241-259.

Barber, L.B., II, Leenheer, J.A., Pereira, W.E., Noyes, T.I., Brown G.K., Tabor, C.F., and Writer, J.H., 1995. Organic Contaminants in the Mississippi River from Municipal and Industrial Wastewater in Contaminants in the Mississippi River. USGS Circular 1133. Edited by R.H. Meade.

Brion, G.M. 2003. The AC/TC Bacterial Ratio: A Tool for Watershed Quality Management.

Burkhardt, W., III, K.R. Calci, W.D. Watkins, S.R. Rippey. 1998. Decay of Microbial Indicators in Estuarial Waters.

Burkhardt, W., III, K.R. Calci, W.D. Watkins, S.R. Rippey. 1998. Occurrence of MaleSpecific Bacteriophage in Feral and Domestic Animal Wastes, Human Feces, and Human-Associated Wastewater.



### 3C-15Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Burton, A., D. Gunnison and G. Lanza. 1987. Survival of pathogenic bacteria in various freshwater sediments. Applicant and Environmental Microbiology 53(4) 633-638.

CDM. 2001. Big Creek Water Resource Management Plan. Fulton County, Georgia.

CDM. 2003. Rouge River National Wet Weather Demonstration Project.

CDM. 2005. Merrimack River Water Assessment Study.

Coastline, Spring 1998 Issue 8.2. Pinning Down Sources of Coliform Bacteria. Pg. 4-5.

Feacham, R. 1975. An improved role for faecal coliform to faecal streptococci ratios in the differentiation between human and non-human pollution sources. Water Res. 9:689.

Geary, P.M. and Davies, C.M. (2003).”Bacterial source tracking and shellfish contamination in a coastal catchment”, Water Sci. Technol ., 47(7-8),95-100.

Geldrich, E., C. Boreen, C. Huff, H. Clark, P. Kabler. 1962. Type distribution of coliform bacteria in the feces of warm-blooded animals. Journal Water Pollution Control Federation (34):295.

Godfrey, A. 1992. Sources and fate of microbial contaminants. In Recreational Water Quality Management Volume 2: Freshwaters . eds. D. Kay and R. Hanbury. Ellis Horwood, New York NY, pp.137-154

Griffith,J. F., et al. (2003). “Evaluation of microbial source tracking methods using mixed fecal sources of aqueous test samples”, J. Water Health , 4(1), 141-151.

Hagedorn, C. et al. (1999). “Determining sources of fecal pollution in a rural Virginia watershed with antibiotic resistance patterns in fecal streptococci”, Appl. Environ. Microbiolog ., 65(12), 5522-5531.

Harwood, V.J. et al. (2000). “Classification of antibiotic resistance patterns of indicator bacteria by discriminant analysis: use in predic ting the source of fecal contamination in subtropical waters”, Appl. Environ. Microbiol., 66(9), 3698-3704.

Kuntz, R. L. et al. (2004). “Presence of Enterococcus faecalis in broiler litter and wild bird feces for bacterial source tracking”, Water Res ., 38, 3551-3557.

Lalor, M. 1994. Assessment of non-stormwater discharges to storm drainage systems in residential and commercial land use areas. Ph.D. dissertation. Dept. of Environmental and Water Resources Engineering. Vanderbilt Univ. Nashville, TN. 256 pp. ( Watershed Protection Techniques 3(1): Page 591.).

Lalor, M and R. Pitt. 1999. Use of Tracers to Identify Sources of Contamination in Dry Weather Flow. Wat. Prot. Techniques. 3(1): page 585-592.



### 3C-16Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Marino, R. and J. Gannon. 1991. Survival of fecal coliforms and fecal streptococci in storm drain sediment. Water Resources 25(9): 1089-1098.

Messer, D.F. (2004). Microbial source tracking: a review of current methods and recommendations , Technical Memorandum sent to Amin Kazemi, City of Stockton. Meays, C. L. et al. (2004). “Source tracking fecal bacteria in water: a critical review of current methods, J. Environ. Manage ., 73, 71-79.

Noble, R. T. et al. (2003). “Use of viral pathogens and indicators to differentiate between human and non-human fecal contamination in a microbial source tracking comparison study”, J. Water Health , 4(1), 195-207.

NWQL, 1997. National Water Quality Laboratory Newsletter. Vol. 5, No. 1. U.S. Dept. Interior/USGS.

Parveen, S. et al. (2001). “Phenotypic and genotypic characterization of human and nonhuman Escherichia coli’, Water Res., 35(2),379-386

.
Pitt, R., et al. (1993). A User’s Guide for the Assessment of Non-Stormwater Discharges into Separate Storm Drainage Systems. Jointly published by the center of Environmental Research Information, US EPA, and the Urban Waste Management & Research Center. EPA/600/R-92/238. PB93-131472. Cincinnati, Ohio.

Pitt, R. 1998. Epidemiology and Stormwater Management. In Stormwater Quality Management . CRC/Lewis Publishers. New York, NY.

Pitt, R. 2001. Source Tracking of Inappropriate Discharges to Storm Drainage systems. NWRI National Urban Conference, Costa Mesa, California. October 17-19.

Pitt, R., et al. (2004). The National Stormwater Quality Database (NSQD, Version 1.1)

. Dept. of Civil and Environmental Engineering, University of Alabama, Tuscaloosa, AL.

Samadapour, M.. Dept. Env. Health. Univ. of Washington. Seattle, WA. (206-543-5120). Telephone interview. 1999.

Schueler, T.R. 1999. Microbes and Urban Watersheds. II. Concentrations, Sources, and Pathways. Watershed Protection Techniques. 3(1): page 554.

Schueler, T.R. 1999. Microbes and Urban Watersheds. IV. Implications for Watershed Managers. Watershed Protection Techniques. 3(1): page 581.

Steuer, J., W. Selbig, N. Hornewer and J. Prey. 1997. Sources of contamination in an urban basin in Marquette, Michigan and an analysis of concentrations, loads and date quality. USGS Water Resources Investigation Report 97-4242. Middleton, MI. 26 pp.

USGS Chattahoochee River National Recreation Area Monitoring Program (1999 – present ga.water.usgs.gov/projects/chatm/publications.html)



### 3C-17Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Vikas G.S., Dunstan, H. and Geary, P.M. (2004) Application of Emerging Bacterial Source Tracking (BST) Methods to Detect and Distinguish Sources of Fecal Pollution inWaters, In Proceedings of International Conference on Emerging Technologies (ICET2004), Eds D.K. Mishra and P.N. Ramachandranan, December 22-24, Bhubaneswar, India,117-126, (ISBN 81 7764 727 X).

Watershed Protection Techniques. Volume 3, No. 1. Pages 551- 596.

Wiggins, B. A.. (1996). “Discriminant analysis of antibiotic resistance patterns in fecal streptococci, a method to differentiate human and animal sources of fecal pollution in natural waters”, Appl. Environ. Microbiol., 62(11), 3997-4002



### 3C-18County Animal Feeding Operation Concentrated
Animal Feeding Operation Concrete Batch GP Industrial
Wastewater Petroleum Cleanup GP (long term) Total

Alachua 2 6 8 16
Baker 1 1 2 Bay 8 10 4 22
Bradford 1 3 4
Brevard 10 43 2 55
Broward 13 25 38
Calhoun 1 4 5
Charlotte 8 16 24
Citrus 5 15 20 Clay 1 7 14 22
Collier 9 13 5 27
Columbia 2 10 1 13
Desoto 1 7 8
Dixie 1 1
Duval 20 57 6 83
Escambia 5 28 6 39 Flagler 3 1 4
Franklin 1 1
Gadsden 3 9 4 16
Gilchrist 3 1 1 5
Glades 1 3 4
Gulf 4 4
Hamilton 5 1 6
Hardee 1 1 7 9 Hendry 2 9 1 12
Hernando 3 9 12 Highlands 4 1 5 7 1 18 Hillsborough 2 22 83 6 113
Indian River 4 26 30
Jackson 12 12
Jefferson 1 1 1 3 Lafayette 2 2
Lake 8 35 2 45
Lee 18 19 4 41
Leon 4 11 15 Levy 4 5 9 Liberty 3 3
Madison 1 2 3
Manatee 7 11 18
Marion 11 37 48 Table 3D.2 TMDL Model Development Protocol Summary of NPDES-Regulated Facilities Number of Industrial NPDES Facilities by County in Florida

Table 3D-2 NPDES WW Sources.xlsCounty Animal Feeding Operation Concentrated
Animal Feeding Operation Concrete Batch GP Industrial
Wastewater Petroleum Cleanup GP (long term) Total Table 3D.2 TMDL Model Development Protocol Summary of NPDES-Regulated Facilities Number of Industrial NPDES Facilities by County in Florida

Martin 1 3 15 3 22
Miami-Dade 20 22 2 44
Monroe 23 23
Nassau 3 5 1 9
Okaloosa 6 4 10
Okeechobee 10 7 1 8 1 27 Orange 21 64 4 89
Osceola 6 5 2 13
Palm Beach 11 37 1 49
Pasco 3 13 19 2 37
Pinellas 10 13 6 29
Polk 3 22 93 5 123
Putnam 2 17 3 22
Santa Rosa 5 10 3 18
Sarasota 7 24 3 34
Seminole 5 8 1 14
St. Johns 4 4 8
St. Lucie 1 2 26 2 31
Sumter 1 3 10 14
Suwannee 1 4 1 6 Taylor 1 8 9
Union 2 2
Volusia 7 24 2 33
Wakulla 1 6 7
Walton 3 9 12 Washington 3 3
Totals 32 9 356 1,017 86 1,500

Table 3D-2 NPDES WW Sources.xlsCounty Domestic
WWTP Residuals Application

Facility Residuals/ Septage Management Facility Reuse/
Distribution

System Total

Alachua 30 10 1 41
Baker 4 7 11 Bay 16 16
Bradford 6 4 10
Brevard 66 5 71
Broward 19 19
Calhoun 1 1
Charlotte 35 3 38
Citrus 77 7 1 85 Clay 27 2 29
Collier 27 1 28
Columbia 22 7 29
Desoto 21 9 1 31
Dixie 3 1 4
Duval 42 10 3 55
Escambia 12 4 16 Flagler 15 4 1 20
Franklin 12 12
Gadsden 11 8 19
Gilchrist 5 3 8
Glades 25 25
Gulf 5 2 7
Hamilton 11 4 15
Hardee 17 4 21 Hendry 15 22 37
Hernando 39 8 3 50 Highlands 69 7 76 Hillsborough 140 2 142
Holmes 4 5 9
Indian River 14 3 17
Jackson 9 3 12
Jefferson 5 2 7 Lafayette 2 2 4
Lake 122 10 132
Lee 90 13 103
Leon 15 2 17 Levy 14 4 18 Liberty 3 3
Madison 8 6 14
Manatee 10 15 3 28 Table 3D.1 TMDL Model Development Protocol Summary of NPDES-Regulated Facilities
Number of Domestic Wastewater Permited Facilities in Florida

Table 3D-1 NPDES WW Sources.xlsCounty Domestic
WWTP Residuals Application

Facility Residuals/ Septage Management Facility Reuse/
Distribution

System Total Table 3D.1 TMDL Model Development Protocol Summary of NPDES-Regulated Facilities
Number of Domestic Wastewater Permited Facilities in Florida

Marion 132 18 1 151
Martin 51 51
Miami-Dade 27 27
Monroe 297 1 298
Nassau 20 2 22
Okaloosa 18 2 20
Okeechobee 24 2 1 27 Orange 73 2 75
Osceola 42 9 51
Palm Beach 67 1 1 69
Pasco 84 1 1 1 87
Pinellas 26 2 28
Polk 177 23 5 205
Putnam 30 8 1 39
Santa Rosa 11 1 12
Sarasota 61 2 63
Seminole 28 5 33
St. Johns 34 3 37
St. Lucie 42 12 1 55
Sumter 41 5 46
Suwannee 12 3 15 Taylor 7 2 9
Union 1 2 1 4
Volusia 124 13 2 139
Wakulla 7 7
Walton 10 5 15 Washington 6 6
Total 2,520 316 30 5 2,871

Table 3D-1 NPDES WW Sources.xlsCounty Constrution SW GP Individual SW MSGP MS4 Totals

Alachua 70 40 110
Baker 10 6 16 Bay 86 65 151
Bradford 4 6 10
Brevard 238 119 357
Broward 336 2 188 3 529
Calhoun 3 3 6
Charlotte 51 12 63
Citrus 16 4 20 Clay 87 1 27 115
Collier 254 40 294
Columbia 15 1 15 31
Desoto 6 3 9
Dixie 3 4 7
Duval 748 2 222 3 975
Escambia 145 54 1 200 Flagler 41 6 47
Franklin 15 15
Gadsden 18 18 36
Gilchrist 3 3
Glades 6 6
Gulf 19 5 24
Hamilton 6 3 9
Hardee 14 2 16 Hendry 9 15 24
Hernando 33 4 37 Highlands 29 16 45 Hillsborough 1,000 2 230 3 1,235
Holmes 7 2 9
Indian River 82 33 115
Jackson 18 10 28
Jefferson 7 1 8 Lafayette 4 1 5
Lake 111 23 134
Lee 765 113 1 879
Leon 185 28 2 215 Levy 6 2 8 Liberty 7 2 9
Madison 8 7 15
Manatee 275 1 46 2 324
Marion 48 31 79 Table 3D.3 TMDL Model Development Protocol Summary of NPDES-Regulated Stormwater Facilities Number of Regulated Facilities by County

Table 3D-3 NPDES WW Sources.xlsCounty Constrution SW GP Individual SW MSGP MS4 Totals Table 3D.3 TMDL Model Development Protocol Summary of NPDES-Regulated Stormwater Facilities Number of Regulated Facilities by County

Martin 68 40 108
Miami-Dade 125 114 3 242
Monroe 6 24 30
Nassau 51 10 61
None 408 3 411
Okaloosa 105 27 132
Okeechobee 14 10 24 Orange 1,202 208 3 1,413
Osceola 191 27 218
Palm Beach 536 121 1 658
Pasco 282 21 1 304
Pinellas 304 109 2 415
Polk 579 2 139 1 721
Putnam 19 17 36
Santa Rosa 69 8 77
Sarasota 446 65 1 512
Seminole 342 40 1 383
St. Johns 150 23 173
St. Lucie 104 29 133
Sumter 18 6 24
Suwannee 6 6 Taylor 8 3 11
Union 5 10 15
Volusia 151 52 203
Wakulla 13 1 3 17
Walton 48 9 57 Washington 26 3 29

Totals 10,064 12 2,527 28 12,631

Table 3D-3 NPDES WW Sources.xlsFlorida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Section 4 MODEL EVALUATION AND SELECTION

Notes:

1. Preparation, verification, calibration, and validation (PVCV) Tech Memo PVCV of Current Conditions

FDEP
A cceptance C/L/S Meeting

No

TARC
Review Current Conditions
Watershed Model Tech Memo

Review Comments 12

13

14 Current Conditions Receiving Water

Model, TMDL, Uncertainty, and Recommendations PVCV of Current Conditions Receiving Water Model 1

Yes 11 TMDL Modeling Tech Memo Refinement of TMDL Objectives

10

Definition of

Conditions Design and Simulation Conditions Design and Simulation 9 Tech Memo

Restatement of TMDL Modeling

Objectives



### 4-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# 4.1 INTRODUCTION

This section of the protocol discusses the methods to be used for selecting the modeling tools to evaluate flows and loads, to define the total allowable load, and evaluate the benefits (e.g., load reduction) to be obtained from the implementation of BMPs. This section provides guidance on model selection based on the available data and models, processes being modeled, level of complexity, and the temporal and spatial scales. Figure 1.2 shows the overall flowchart for a TMDL project.



# 4.2 MODEL EVALUATION AND SELECTION METHODOLOGY

A variety of models and related tools may be used for TMDL analyses. The following process can be considered for model evaluation and selection. It should also be noted that some tasks can be performed in parallel with others.

Task 1: Consider Classification of the Selected Receiving Water Body

From the 303(d) list of impaired watersheds, the user should consider the classification of the type of receiving water body for model selection:

 

### Lake;

 

### River, canal, stream, or ditch;

 

### Estuary;

 

### Sink hole; and/or

 

### Wetland.

This will assist with the decisions for level of detail, necessary model features, and temporal scale. For many TMDLs, multiple classifications may be necessary (e.g., river with lakes and wetland flow ways).

Task 2: Define Parameters and Processes

From the 303(d) list of impaired water bodies, the user will need to evaluate one or more parameter(s) associated with the impaired watershed. The grouping of parameters may include:

 

### Oxygen demand in various forms, including 5-day biochemical oxygen demand (BOD 5 

### ), ultimate BOD, carbonaceous oxygen demand (CBOD), nitrogenous oxygen demand (NOD), plant dark cycle respiration, and sediment oxygen demand (SOD);

 

### Nutrients and related parameters, including nitrogen (total nitrogen - TN, nitrite - NO 2 

### , nitrate - NO 3 

### , total Kjeldahl nitrogen - 

### TKN, ammonia - NH 3 

### , also called unionized ammonia, ammonium - NH 4 

### ) and phosphorous (total - TP and orthophosphate - PO 4 

### );

4-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Pathogens and Bacteria, including fecal and total coliform, atypical coliform, enterococci, streptococcus, and others;

 

### Toxics, which may include priority pollutants; and

 

### Sediments, including sands (coarse, medium, fine), silts, and clays.

The hydrological, physical, c hemical, and geological processes related to the impairment should be considered to define necessary model features, capabilities, and associated data. Multi-dimensional needs for estuaries, lakes, and/or large rivers; wetlands (empirical wetland equations and data); and other special cases should be identified to assist in model selection and data refinements. For example, it may be necessary to model and/or estimate processes such as groundwater interactions using integrated or coupled surface and groundwater models of sinkholes in Karst regions of central Florida or highly permeable aquifers such as the Biscayne in southeast Florida.

Task 3: Determination of Temporal and Spatial Scales

As part of the model selection process, it is important to identify the temporal and spatial scales of the water quality or biological impairment to be evaluated. The temporal scale refers to two related issues: the time over which measurable water quality or quantity changes occur in the environment and the associated time step for which the simulation model is best suited. For example, a steady-state model may be useful for TMDL application in simulations of very slowly changing environm ental conditions in a large lake or estuary (annual or seasonal); a continuous simulation model may be useful for TMDL application requirements for assessment of streams in urban nonpoint sources (time scales of seconds, minutes, or hours); and an estuarine model should consider tidal variation (hours).

Water quality based problems that occur during a low-flow period may require a different assessment approach than waters where longer-term loadings are of concern. Therefore, it is important to identify the time scale of the water quality problem prior to selecting the appropriate TMDL assessment tool. For instance, examining a water quality problem that occurs only at low-flow periods may be based upon gaging station records or a simplified analysis of contributing sources. Low-flow conditions are often dominated by point source discharges, septic tank seepage, and baseflow sources (e.g., groundwater). For low-flow conditions, source loadings may be quantified by a combination of in-stream monitoring and point source discharge records instead of more detailed water quality modeling. If the problem is a result of longer-term pollutant loadings, then it may be appropriate to estimate loads on a monthly, seasonal, and/or annual basis. Techniques appropriate for these situations include unit-load rating calculations and use of simple model methods (e.g., spreadsheet-based loading estimates). For waterbodies that have relatively short residence times, consideration of a series of individual storms or a continuous (hourly or daily) simulation of the loading processes may be warranted. Interpretation of time variable loads can be used to examine the frequency and magnitude of the loading.

Water quality model time scale and time steps can greatly affect simulation times. Some models run in a few minutes and others require hours or days for long-term continuous simulations. To accurately represent watershed hydrology, time steps should be less than,

4-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### and ideally an integer multiple of, the rainfall interval. Time steps should be less than overland flow, conduit, and WBID reach travel times to maintain continuity (i.e., conservation of mass) for each model process. Table 4.1 shows a general characterization of the time scale necessary for the noted application.

Table 4.1 Time Scale Examples
Application Type Residence or Travel Time Time Scale

Tributary Model Short (<24 hours) Minutes, Hours

Watershed Model Medium (24 hours to 7 days) Hours, Days, Weeks

Receiving Water Model Long (days to months) Days, Months, Seasons

The term “spatial scale” refers to the suitable watershed size and/or levels of detail for discretization for model applications. Certain models (e.g., P8 and SLAMM) are appropriate for use in many applications (e.g., simulati ons of development sites and small watersheds), but they may not be appropriate for simulations of large watersheds because they do not directly account for instream flow routing and pollutant parameter transformation and decay. Other models can generally be applied to watersheds ranging in size from small to large, as would be required for the watershed planning studies. Therefore, it is important to account for the spatial scale of the problem during the model selection and preparation processes. The level of detail incorporated into the model will affect computer simulation times and the amounts of data that need to be processed, explained, and documented.

Task 4: Screening Analysis

This task can assist the TMDL practitioner in the selection of appropriate modeling tools based on the available spatial data for the watershed as well as on their respective scales. Data gaps and needs also can be identified at this stage. Data priorities can be established using sensitivity analysis guidelines described in Section 3 and model testing for sensitivity described in Section 5.

After the data evaluation, the screening analysis involves identifying and obtaining existing model(s) for the subject watershed. The uncertainty or range of parameter variation for existing models may also be defined. Depending upon the outcome of this check, three options are available to the practitioner:

 

### Option 1: A previously prepared model exists with the necessary features and pertinent input data at the correct resolution. The practitioner should perform a peer review of the model input as well as the verification, calibration, and validation. If the model is not verified, calibrated, or validated, then the practitioner should perform these tasks.

 

### Option 2: A previously prepared model exists with the necessary features, but there is an input data deficiency or limitation in model scale (detail) and/or accuracy. As a result, the

4-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### practitioner may need to collect more data and refine the model before starting the TMDL analysis. The uncertainty analysis and necessary levels of detail help define data needs. The peer review described in Option 1 should be performed.

 

### Option 3: There is no previously prepared model. Therefore, the practitioner would need to select the model for preparation.

Task 5: Model Selection

In this task, the practitioner selects an appropriate modeling tool. Using the results of the screening analysis, the practitioner can select from a wide range of tools to provide the necessary features and capabilities. A number of sources exist to assist in this effort, including the Water Environment Research Foundation Water Quality Selection Tool (WERF, 2001) and EPA documents. Table 4.2 presents the capabilities and relative complexity of more than 40 watershed models as listed by EPA in the Compendium of Tools for Watershed Development and TMDL Development (EPA, 1997). Table 4.3 presents the same information for over 30 receiving water models. If the practitioner is faced with a data deficiency for the selected model, further input data may have to be collected or another model may need to be considered. Existing hydrologic and hydraulic models may also be used to define flows for a water quality model.



# 4.3 SELECTION EXAMPLE: LOWER HILLSBOROUGH RIVER

The model selection decision process has been applied to the Lower Hillsborough River in Tampa, Florida. The various water bodies have been selected for TMDL evaluation because they are on the verified 303(d) list for water quality impacts to:

 

### Nutrients

 

### DO

 

### Ammonia (unionized)

 

### Bacteria

Task 1: Identify the Receiving Water Body Type For the Hillsborough River, two principal receiving water body types are present: a lake (Lake Thonotosassa) and river reaches (e.g., Flint and Baker Creeks and Lower Hillsborough River). Several of the models listed in Table 4.3 are capable of water quality simulation of these two water body types with one model (e.g., AESOP, CE-QUAL-ICM, WASP) and several models can be used to generate the watershed loads (e.g., SWMM, BASINS-HSPF, WAM, SWAT, SLAMM). The wate rshed also contains many wetlands and significant groundwater inflows and withdrawals in the northwest, so the selected watershed model must address these related processes.

4-5Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Task 2: Define Parameter(s) and Processes For the seven WBIDs that comprise the Lower Hillsborough River, nutrients, dissolved oxygen, unionized ammonia, and bacteria have been identified as parameters of concern. Table 4.4 associates each of the WBIDs within the Lower Hillsborough River as well as other basin information with parameters of concern. It was decided by FDEP and EPA that bacteria would be modeled by EPA as part of this TMDL evaluation.

Table 4.4 Available Data for the Lower Hillsborough River TMDL Model Selection

Water Segment Type Miles Parameters of Concern Hydraulic Model (Yes/No) Flow Data Water Quality

Data
Baker Creek River 2.3 DO, nutrients Y (SWMM EXTRAN) Y Y

Cow House Creek River 3 DO Y (SWMM EXTRAN) Y Y

Flint Creek River 2.3 DO, nutrients Y (SWMM EXTRAN) N Y

Upper Hillsborough River River 6 DO Y (HEC-RAS) Y Y

Lower Hillsborough River River 5 Nutrients Y (UNET, HEC-1, FLDWAV) Inlet only Y

Lake Thonotosassa Lake 1.3 Unionized ammonia Y (SWMM EXTRAN) Y Y

Sparkman Branch River 5.4 DO N N Y



### In order to evaluate these parameters, pr ocesses for oxygen demand (e.g., BOD, SOD), nutrient cycles, and algal growth and decay will be required.

Task 3: Determination of Temporal and Spatial Scales Because the parameters of concern in the Lower Hillsborough River are expected to change within a daily time-step, the selected model must be able to simulate hourly or shorter time steps. Existing hydraulic models were available for the majority of the study area, allowing a finer discretization of the hydraulics of the primary reaches within the WBIDs. Sufficient water quality monitoring data were available to observe in-stream water quality processes at the reach scale. Within the 7 WBIDs, there are approximately 9 miles of primary reaches and 16 miles of tributaries.

Task 4: Screening Analysis For the Lower Hillsborough River, relevant data such as hydrologic, water quality monitoring, point source discharge locations and loads (NPDES data), and existing hydraulic model data were compiled and evaluated for relevance to the specific WBID TMDL evaluations.

4-6Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### As discussed in Section 3, a variety of data analysis tasks were performed, including: USGS flow gages evaluation, USGS water quality monitoring stations summaries for period of record, number of sample events available per parameter of concern, minimum, maximum, and average result values; and point sources identification. The selection of viable points of comparison for model results prior to preparation of the model itself is required. The impaired reach lengths and spatial distribution of instream data points are important determinants of the appropriate level of model resolution.

In previous work, a WAM had been prepared for the Hillsborough River watershed for flows and loads. The majority of the study area is also represented in UNET, HEC-RAS, and SWMM EXTRAN hydraulic models. These m odels were used to define system crosssections, volumes, and hydraulics for the WAM application of the Lower Hillsborough TMDL models.
Other critical factors for model analyses include budgetary constraints and schedule constraints. In this case, schedule constraints did not allow any additional data collection beyond what was readily available. Associated uncertainty was quantitatively defined for data gaps and limitations.

Task 5: Model Selection The chosen simulation models for the Lower Hillsborough River were WAM and WASP because they best met the criteria to evaluate the impaired reaches and related parameters. A WAM application was already established at an appropriate level of detail, and it was refined with the best available data to improve its accuracy. WASP was chosen because it can simulate the necessary water quality processes (oxygen demands, nutrient cycles, and algal growth and decay) with continuous simulation to address the parameters of concern (DO, nutrients, and unionized ammonia).

4-7Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### 4-8 

# SECTION 4 REFERENCES

EPA. 1986. Forecasting onsite soil adsorption failure rates . EPA/600/2-86/060.

EPA. 1997. Co mpendium of Tools for Watershed Assessment and TMDL Development

. EPA841-B-97-006.

Water Environment Research Foundation. 2001. Water Quality Models: A Survey and Assessment . Project 99-WSM-5.Florida Department of Environmental ProtectionJune 2006TMDL ProtocolVersion 6.0Task Assignment 003.03/05-003Table 4.2Florida TMDL ProtocolWatershed Models and PackagesTime ScalePollutantsComplexityIndexShort NameFull-Name Events Continuous Annual / Seasonal Sediments Nutrients Other Chemicals Level of Effort Data Requirements1AGNPS-98AGricultural Non Pollution - Source Model 98999999MM2ANSWERSAreal Non-point Source Watershed Environment ResponseSimulation999999MM3APEXAutomatic Parameter Estimation eXrention999999MH4BASINS (HSPF)Better Assessment Science Integrating point and Non-pointSource999999MH5BASINS (SWAT)Better Assessment Science Integrating point and Non-pointSource999999MH6CREAMSChemicals, Run-off, Erosion,from Agricultural ManagementSystems999999MM7DR3M-QUALDistributed RoutingRunoff Rainfall Model - Quality999999MH8EPICErosion Productivity Impact Calculator999999MH9ETDEnhanced Trickle-Down9999LL10FHWANot Available9999LL11GISPLMGeographical InformationSystem Phosphorous LoadingModel9999MH12GLEAMSGroundwater Loading Effect of Agricultural ManagementSystems999999MM13GWLFGeneralized Watershed Loading Function999999LL14HEC-1/HMSHydrologic Engineering Center-1/Hydrologic Modeling System99MM15HSPFHydrologic Simulation Program-Fortran999999MH16HUMUSHydrologic Unit Modelfor the United States999999MH4-1Florida Department of Environmental ProtectionJune 2006TMDL ProtocolVersion 6.0Task Assignment 003.03/05-00317KINEROSKINEmatic Runoff and erOSion Model9999MM18LSPCLoading Simulation Program in C++99999MM19LWWMLinked Watershed/Waterbody Model999999HH20MAGICModel of Acidification of Groundwater In Catchments999LL21NAPRANational Agricutural Pesticide Risk Assessment999999MM22NLEAPNitrate Leaching and Economic Analysis Package9999LL23OpusOpus999999HH24P8-UCM (P8)Urban Catchment Model999999MM25PRMSPrecipitation Runoff Modeling System9999MM26PRMS/ANNIEPrecipitation Runoff Modeling System999MH27PRZM-3Pesticide Root Zone Model-3999999MH28SLAMMSource Loading And Management Model999999MH29SLOSS-PHOSPHNot Available9999LL30SLURPSimple Lumped Reservoir Parameter999MH31SPUR-91Simulation of Productionand Utilization ofRangelands99999MM32SSARRStreamflow Synthesis and Reservoir Regulation999MH33STORMStorage Treatment Overflow Runoff Model999999LL34SWATSoil and Water Assessment Tool999999MH35SWMMStormwater Management Model (RUNOFF and EXTRAN)999999MM36SWRRBWQSimulation for Water Resource in Rural Basin Water Quality999999MM37TR-55/20Technical Release 559LL38USGSREGRUnited States Geological Survey REGRession99999LL39UTM-TOX-WHTMUnified Transport Model for Toxic Materials999999HH40WAMWatershed Assessment Model99999HH41WATERSHEDWATERSHED9999MH42WEPPWater Erosion Prediction Program9999MH43WMMWatershed Management Model9999LL44WSTTWatershed Screening and Targeting Tool999999LL(Source - EPA 1997 Compendium of Tools for Watershed Assessment and TMDL Development)(EPA841-B-97-006)4-2Florida Department of Environmental ProtectionJune 2006TMDL ProtocolVersion 6.0Task Assignment 003.03/05-003Table 4.3Florida TMDL ProtocolReceiving Water ModelsTime ScaleDimensionsTypePollutantsComplexityIndexShort NameFull-Name Steady-State Time-variable 1-D 2-D 3-D Reservoir/Lake Stream/River Estuary Pathogens BOD/DO Eutrophication Sediments Chemical Fate Level of Effort Data Requirements1ADCIRCADvanced CIRculation Model9999999MM2AESOPNot Available999999999999HH3BATHTUBBATHTUB9999ML4BranchBranch-Network Dynamic Flow Model99999MM5CE-QUAL-ICMCorps of Engineer-Quality-IntegratedCompartment Model999999999HH6CE-QUAL-R1Corps of Engineer-Quality-Reservoir 19999999MM7CE-QUALRIV1Corps of Engineer-Quality-River 19999999HH8CE-QUAL-W2Corps of Engineer-Quality-Water 2999999MH9CH3D-WESCurvilinear Hydrodynamicsin 3-Dimensions -Waterways Experiment Station9999MH10CONCEPTSCONservational Channel Evolution andPollutants Transport System11CORMIXCORnell MIXing zone expert system9999999ML12DYNHYD5DYNHYD59999HM13EFDCEnvironmental Fluid Dynamics Code9999999999999HH14EPDRiv1A Dynamic One-Dimensional Model ofHydrodynamics and Water Quality9999999MM15EUTROMODEUTROphication MODel9999LL16FESWMS-2DHFinite Element Surface-Water ModelingSystem:Two-Dimensional Flow in a Horizontal99999MM4-3Florida Department of Environmental ProtectionJune 2006TMDL ProtocolVersion 6.0Task Assignment 003.03/05-003Plane17HEC-5QHydrologic Engineering Center 5 Q99999MM18HEC-6Hydrologic Engineering Center - 69999MM19HEC-RASHydrologic Engineering Center - RiverAnalysis System999HM20HEM-1DHydrodynamic Eutrophication Model 1-D99999999MH21HEM-2DHydrodynamic Eutrophication Model 2-D9999MH22HEM-3DHydrodynamic Eutrophication Model 3-D99999MH23HSPFRCHRESHydrologic Simulation Program-Fortran9999999999MH24MECCANot Available99999HH25PHOSMODPHOSphorous MODel9999MM26POMPrinceton Ocean Model9999999MH27QUAL2EEnhanced Water Quality 2999999MM28RIVMOD-HRIVer MODel-H99999ML29RMA-10Resource Management Associates 1099999999LL30RMA2-WESResource Management Associates 2 -Waterways Experiment Station9999999MM31SWMMStormwater Management Model (Transport)999999999MM32TWQMTail Water Quality Model99999999MM33WASPWater Quality Analysis Simulation Program999999999999HH(Source - EPA 1997 Compendium of Tools for Watershed Assessmentand TMDL Development)(EPA841-B-97-006)4-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Section 5 MODEL PREPARATION, VERIFICATION, CALIBRATION, AND VALIDATION

Notes:

1. Preparation, verification, calibration, and validation (PVCV) Tech Memo PVCV of Current Conditions Watershed Model 1

Yes FDEP
A cceptance C/L/S Meeting

TARC
Review 12

13

14 PVCV of Current Conditions

Receiving Water Model 1

No Current Conditions
Watershed Model Tech Memo

Review Comments Current Conditions

Receiving Water

Model, TMDL, Uncertainty, and Recommendations

TMDL Modeling

Tech Memo Refinement of TMDL Objectives

Definition of

Conditions Design and Simulation Conditions Design and Simulation

11 10 9 Tech Memo

Restatement of TMDL Modeling

Objectives



### 5-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# 5.1 INTRODUCTION

As described in Section 1, the TMDL process includes the identification of impaired waters, followed by the analysis and development of t he TMDL. For Florida, the development and allocation of a TMDL is part of a five-element process (see flow chart on cover of this section), in which the second element process leads to the definition of the allowable load. This section of the report discusses the protocols for developing the preparation, verification, calibration, and validation of the chosen watershed and/or impaired waterbody-specific models to define the total allowable loads and associated water quality and hydrologic statistics.



# 5.2 MODEL SETUP AND DATA INPUT

After the model selection process, the selected model(s) need to be prepared (setup). In this process, care must be taken to prepare the model at an appropriate level of detail, giving consideration to the features of the study area and the resolution necessary to understand the nature of the water quality problem (i.e., parameters, sources, and magnitudes) and to evaluate reduction measures (e.g., BMPs) with in available data limitations. For example, subbasin and stream reach delineation should consider factors such as variability of rainfall, land use, topography, potential pollutant sources, coverages and efficiencies of BMPs, locations of monitoring stations, water control structures, stream crossings, municipal and state jurisdictions, the time scale associated with the pollutant(s) of concern (e.g., minutes, hours, days, months, years), and other local conditions that contribute to the water quality impairment and listing. There is often a tradeoff between model detail and model run times as well as the resultant data processing. This data refinement consistent with the discretization of model(s) is often an iterative process coordinated with the data evaluations in Section 3.

Model numerical (or mathematical) stability should be considered in the model preparation, verification, calibration, and application. The time step for each model should be chosen to maintain conservation of mass (continuity) for rainfall, runoff, and routing through short, medium, and long systems (e.g., ditches and channels, culverts and bridges, and rivers, respectively). Short reaches often tend to be bridges or culverts which may have limited flow restriction for 90 percent of rainfall events or greater, and in many cases may be neglected for these long-term water quality simulations or may be combined with adjacent conduits to maintain overall system length. Some models provide warning messages or other indicators of model instability in the model output. For example, SWMM output provides a continuity warning in the form of an error value that the model generates by comparing the sum of the system's initial water volume and water inflow to the sum of the system's final water volume and total outflow. Thus, it indicates the extent to which the model is calculating a net gain or net loss of water during the simulation period. Some models like SWMM EXTRAN provide warning messages regarding "short" reaches wher e numerical instabilities are most likely to occur. Besides model output messages, graphical plots of flow, stage, concentration, and/or load results should be reviewed to look for "spikes" or rapid variations that may indicate model instability. Another method of evaluating m odel stability is to conduct a model run in which a conservative parameter is modeled, assigning all initial concentrations, inflow concentrations, and boundary concentrations with a constant concentration. If the model is

5-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### stable, the concentration in the entire system should stay equal to the same constant concentration, and mass should be conserved (water and conservative parameters).



## 5.2.1 Model Discretization
The model(s) should be discretized so that each model segment represents a part of the receiving waterbody and/or watershed having similar physical, chemical, and biological characteristics, although parameter variation is a necessity in some cases (e.g., Manning n roughness variation between main channel and overbanks). For hydrologic routing, the discretization should account for major changes in slope, cross-sectional geometry, depth, and other physical characteristics. In addition, the discretization should be fine enough to allow spatial differences in concentrations of water quality parameters to be calculated, especially for impaired segments. The time step should be consistent with the expected or necessary travel time of a unit flow volume passing through the segment control volume. In many cases, the receiving water may be a rive r that is fairly well-mixed laterally and vertically, and the receiving water can be r epresented as a 1-dimensional system with concentration differences only in the longitudi nal direction. However, in larger rivers, tributary inflows or point source discharges may tend to “hug the shore” or the surface in tidal estuaries and not get dispersed or become “well mixed”. In such cases, it may be necessary to apply a 2-dimensional model to better define the lateral mixing downstream of the inflow. In lakes and estuaries, it is possible that both lateral and vertical differences (e.g., stratification) need to be defined by a 3-dimensional model.

The discretization of the receiving water tributary area into subbasins should go hand-inhand with the discretization (segmentation) of the receiving water. Figure 5.1a and Figure 5.1b show examples of the tributary watershed discretization and segmentation levels of detail for the lower Hillsborough River. The tributary area should be identified for each of the receiving water segments, and flows and loads would be calculated from each tributary area. If these tributary areas are large enough to have travel times greater than 12 to 24 hours, the watershed model should consider the attenuation and the reduction of total load due to instream processes (e.g., settling, first-order decay).



## 5.2.2 Boundary Conditions
Information regarding boundary conditions is required by most surface water and ground water hydraulic and water quality models. Boundary conditions define hydrologic conditions (e.g., flow, stage) and water quality conditions (e.g., concentrations) at locations where external system flows enter or exit the watershed and/or receiving water model.

5-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Figure 5.1a Subbasins and Reaches for the Lower Hillsborough River

5-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003Figure 5.1.b Receiving Water Segmentation for the Lower Hillsborough River



### 5-5Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### As an example, the surface water hydraulic boundary condition at the downstream end of a receiving water body can be a free discharge point or a fixed stage, or the boundary condition can follow tidal fluctuations. Modelers can define boundary conditions based on tidal data from NOAA or normal water levels from USGS or WMD data. Normal water surface elevations are often used as the boundary conditions for large lakes that respond very slowly to rainfall events. For smaller lakes, a statistical analysis may be conducted (as data permit) to estimate stages for various recurrence intervals, which can be used as a fixed boundary condition. In all cases, the models selected for watershed analyses should be capable of representing the boundary condition for the study area using the appropriate time scale for the analysis.

Water quality boundary concentrations are required as model inflows for water quality loads that are not calculated in the receiving wate r TMDL model. For example, downstream water quality concentrations need to be defined for tidal receiving waters, where the tidal inflow and associated boundary concentration will determine the mass of constituent entering the receiving water with the incoming tide. Boundary concentrations also need to be set for constituents that are not calculated by the watershed model. Constituents that may not necessarily be evaluated using a watershed loading model could include DO and chlorophyll-a, which are often responses in a receiving water that are dependent upon watershed stream network characteristics, surface runoff and loads, and baseflow loads.



## 5.2.3 Model Coefficients

Model coefficients come in various forms that differ from model to model. For watershed hydrologic models, coefficients can range from a single Rational Method runoff coefficient (“C” value) to a set of coefficients that fully represent the hydrologic cycle (e.g., surface storage and runoff, infiltration, evapotranspiration, groundwater outflow). Watershed load model parameters can be as simple as constant concentrations associated with runoff and baseflow, or models can include buildup and washoff coefficients that are used to calculate runoff concentrations as a function of runoff intensity and antecedent surface mass load. Receiving water quality models can range in complexity from simple mixing and dilution models, to models with complex sets of coeffici ents that characterize the physical, chemical, and biological process that affect the concentration of constituents in the receiving water. Coefficient choices and sensitivity analyses should be documented.

Coefficient values are initially based on measurement or are assigned a value within a reasonable range of values. Subsequent model calibration may involve coefficient adjustments such that the model accurately represents measurements from the study area. Literature sources may provide the coefficient values used in the model. Potential sources include: U.S. EPA documents (e.g., Rates, Constants and Kinetic Formulations in Surface Water Quality Modeling ), the respective model User's Manual, and previous studies. It may be especially useful to compile coefficient values used in previous model applications to have a database of typical values that can be used to set initial coefficient values in future studies. Table 5.1 shows an example of a HSPF data set with ranges of values for the Upper St. Johns River.

5-6Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 5.1 Example Subset of HSPF Hydrologic Parameters for Agricultural Land Uses

Typical Values Possible Values 1 Values by Land Use

Parameter Description Units Minimum Maximum Minimum Maximum Citrus 2 Pasture 2 Row Crop 2

LZSN Lower zone nominal soil moisture storage inches 3.0 8.0 2.0 15.0 4.0 6.5 4.0

INFILT Index to infiltration capacity in/hr 0.01 0.25 0.001 0.5 0.05 0.05 0.05

LSUR Length of overland flow feet 200 500 100 700 300 300 300

SLSUR Slope of overland flow plane ft/ft 0.01 0.15 0.001 0.30 0.001 0.001 0.001

UZSN Upper zone nominal soil moisture storage inches 0.10 1.00 0.05 2.00 0.40 0.65 0.40

1 Values published in BASINS Technical Note # 6.

2 Upper St. Johns River calibrated values (CDM, 2003)



## 5.2.4 Initial Conditions
Information regarding initial conditions is required to define hydrologic and hydraulic conditions (e.g., watershed antecedent moisture conditions for soils, initial water levels for wetlands and waters, receiving water flows and stages) and water quality conditions (e.g., concentrations of pollutants) in receiving water segments. Measured data, if available, can be used to establish initial conditions. If measured data are not available, an initial model run can be conducted for a period prior to the period of interest, such that the model itself calculates the initial conditions at the beginning of the period of interest. This can range from weeks to months (and occasionally years) dep ending on the model, size of the system, and processes affecting impairment. Sensitivity analyses can be used to identify data needs and/or determine a starting point (average or conservative value). For the antecedent moisture condition (AMC) in a hydrologic model, a 2- to 4-week period in advance of the simulation period has often been shown to adequately allow for the model simulation to come to equilibrium for the actual AMC at the start of the simulation, although some systems may require months or even years to establish appropriate conditions (e.g., large wetland systems such as the Tomoka River). Therefore estimates of initial soil and surface water levels are important to reduce the antecedent simulation period required.



# 5.3 MODEL OUTPUT

Typical continuous simulation model outputs will include time series of flows and concentrations, and associated characteristics (e.g., velocity, stage, depth), as well as mass balances and flow balances that identify total flow volumes and constituent loads. Outputs may also include average and maximum values for hydraulic parameters (e.g., flow, depth, velocity) and flow-weighted concentrations.

5-7Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### For both hydrologic/hydraulic and water qualit y models, the overall flow and mass balance should be evaluated to compare model inflow s to model outflows for model elements (conduits, reaches, junctions). Table 5.2 shows an example mass balance for a lake.

Output data from hydrologic and hydraulic modeling should be evaluated to determine whether the results are reasonable. For high-flow conditions in streams, measured flow values can be compared to modeled peak flows in the segment corresponding to the flow gage location. In the absence of measured flow values, unit peak flow values (i.e., discharge rates in cfs per square mile) can be compared to local or regional unit peak flow values. Modeled peak velocities can be evaluated with respect to literature values to assess potential for erosion (generally less than 2.5 to 3.0 feet per second; Chow, 1959), and limited field reconnaissance and/or anecdotal evidence can be used to validate model velocity values for areas with known streambank erosion problems. This can help to define potential TSS loads from scour. For continuous simulation periods including low-flow and high-flow conditions, it is appropriate to evaluate the relative contributions of stormwater runoff and baseflow, and the general distribution of flows in streams. If there are measured streamflows, baseflow separation techniques referenced in Section 3 can be applied to calculate the relative measured quantities of runoff and baseflow, which can be compared to modeled streamflows (using the same baseflow separation techniques) and/or the distribution of runoff and baseflow calculated by the hydrologic watershed model.

Similarly, the calculated watershed model loads and receiving water model concentrations should be evaluated to determine if the results are reasonable. In many cases, the comparison of measured and modeled concentrations in streams cannot be as rigorous as the comparison for hydrology and hydraulics (s tages and flows) due to data limitations. Measured streamflow data generally reflect continuous monitoring, but water quality monitoring data are often developed by analyzing “grab samples” at pre-determined time intervals (e.g., monthly, weekly) and/or defined flow conditions. Consequently, the monitoring data may not reflect the full range of concentrations that are simulated by the model. However, the general distribution of concentrations calculated by the model may be similar to the distribution of concentrations from grab sampling, particularly if the period of sampling is relatively long and samples are collected relatively frequently and randomly (e.g., wet weather and dry weather conditions). It is most appropriate to compare measured concentrations with modeled concentrations that correspond to the times when the samples were taken, rather than the entire simulation period. It may also be useful to analyze measured concentrations with respect to local rainfall and streamflow records to determine whether the samples were collected during a period when streamflow consisted entirely of baseflow, were a combination of baseflow and runoff, or were primarily runoff, as shown in Figure 5.2

.

5-8Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Table 5.2 Example of Long Term Yearly Water Budget Analysis for a Lake

Inflows Outflows Change in Storage

Annual Lake Area= 359

acres
Pervious Impervious Direct Lake Outlet Seepage Net

Inflow Inflow Rainfall Evaporation Outflow Outflow Flow Seepage Outflow

Year (ac-ft) (ac-ft) (ac-ft) (ac-ft) (ac-ft) (ac-ft) (ac-ft) Rough Estimate in inches

1961 462 438 1,448 1,503 1,180 97 -432 3.2 3.3

1962 248 431 1,311 1,263 806 157 -235 5.2 1.9

1963 144 331 943 1,203 469 171 -426 5.7 1.1

1964 1,276 781 2,209 1,339 1,397 216 1,314 7.2 9.9

1965 1,441 630 2,116 1,554 2,627 201 -194 6.7 10.6

1966 971 533 1,799 1,505 1,899 150 -251 5.0 7.2

1967 523 518 1,576 1,461 1,098 187 -130 6.3 4.0

1968 470 493 1,388 1,292 852 288 -80 9.6 3.5

1969 538 492 1,484 1,268 861 294 90 9.8 4.2

1970 1,364 600 1,970 1,536 2,197 215 -14 7.2 10.1

1971 291 432 1,385 1,331 845 241 -309 8.1 2.2

1972 1,228 705 2,105 1,458 1,539 238 804 7.9 9.3

1973 813 478 1,639 1,523 1,780 182 -554 6.1 6.1

1974 370 472 1,383 1,297 829 218 -119 7.3 2.8

1975 381 461 1,391 1,278 772 294 -112 9.8 3.1

1976 381 454 1,252 1,195 630 384 -122 12.8 2.7

1977 161 294 787 1,163 247 397 -565 13.3 1.1

1978 288 466 1,159 1,274 219 291 127 9.7 2.1

1979 399 574 1,491 1,202 445 254 562 8.5 3.0

1980 448 360 1,153 1,323 787 235 -385 7.9 3.3



### 5-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

1981 41 326 856 1,104 137 251 -269 8.4 0.3

1982 705 596 1,602 1,178 700 240 786 8.0 5.3

1983 1,185 641 2,099 1,462 1,598 157 708 5.2 9.3

1984 444 347 1,222 1,508 1,322 75 -892 2.5 2.9

1985 273 460 1,315 1,222 622 109 96 3.6 2.2

1986 589 493 1,512 1,331 950 94 219 3.1 4.6

1987 704 435 1,411 1,401 1,284 97 -231 3.2 5.0

1988 750 618 1,807 1,401 1,155 141 478 4.7 5.6

1989 273 415 1,270 1,352 862 202 -459 6.8 2.1

1990 361 441 1,256 1,353 703 327 -325 10.9 2.6

1991 416 427 1,294 1,297 663 290 -113 9.7 3.1

1992 549 556 1,507 1,217 540 289 566 9.7 4.1

1993 421 413 1,223 1,281 809 295 -328 9.8 3.2

1994 986 598 1,844 1,299 1,037 238 854 7.9 7.5

1995 990 517 1,812 1,440 1,833 170 -124 5.7 7.3

1996 658 495 1,648 1,465 1,223 144 -31 4.8 5.0

1997 1,121 688 2,164 1,513 1,531 185 745 6.2 8.7

1998 1,042 501 1,660 1,485 2,573 40 -896 1.4 7.5

1999 383 414 1,325 1,322 1,053 154 -407 5.1 2.9

2000 364 473 1,306 1,297 677 289 -120 9.6 2.7

2001 185 357 992 1,161 380 333 -340 11.1 1.4

2002 147 433 1,172 1,207 123 362 61 12.1 1.4

Average 590 490 1,483 1,340 1,030 219 -25 7.3 4.4



### 5-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Figure 5.2 Measured and Modeled Streamflow and Total N



# 5.4 MODEL QUALITY MANAGEMENT

A modeling quality management process (also ca lled Quality Assurance and Control) is a key component of successful model application. It is important that quality assurance reviews occur throughout the project including model input data, verification, calibration, and validation points. This process should include considerations and decisions such as the following:

 

### Screening/selecting the right model for the intended applications – As part of the model selection process, the project team should identify the factors causing impairment and identify the key stakeholders. This will provide a general understanding of the desired result of the application, which will help with model selection. Also, model

5-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### selection should consider time and cost constraints, data availability, and familiarity of the project team and model technical reviewer(s) with the model selected.

 

### Checking model parameter values – The person(s) responsible for technical review of the model preparation should verify that the model parameter input values used to run the model are within accepted ranges of values (literature or measured) or document reasons why values vary from accepted ranges. As part of this process, the sensitivity of the model results to changes in model parameters on the predicted results may also warrant investigation. Results can be used to determine confidence intervals and to identify where data refinements would be warranted (or even necessary). This was discussed in Section 3 and here in Section 5.

 

### Checking model results – Model results should first be checked for numerical stability and reasonableness. Figure 5.3 shows an example plot of model numerical instability. Instabilities, if not corrected, can lead to significant under- or overpredictions of flows, loads, and constituent concentrations. Stability checks should be done prior to using the model results to assess a problem or influence decisions, requirements, or actions. Continuity checks alone do not fully confirm model numerical stability. As an example, an instability that oscillates equally above and below zero can “cancel out” continuity error and cause the model to appear to be stable. Visual plots of flow and concentration versus time are commonly used as an additional check. It is also important to check the predicted model results for reasonableness (e.g., annual or seasonal hydrologic and water quality parameters mass balance checks), especially if the results will eventually be used for pollutant load allocations. This is often done through model calibration, verification, and validation as described later in this section.

5-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Figure 5.3 Example of Numerical Instability in Flow



## 5.4.1 Model Verification
As defined by EPA, model verification refers to the examination of the numerical technique in the computer code to ascertain that it represents the conceptual model with no inherent numerical problems. The models described pr eviously in Section 4 have gone through a verification process by the owning entities (e.g., EPA, USGS), in which solutions calculated by the model were compared with results calculated by the owning entities.

Verification steps for the practitioner can include examination of the “input echo” to confirm that input data is read correctly, comparisons of mass balance terms for chosen control volumes (e.g., entire model domain versus individual segments or reaches), continuity checks, routing connectivity, and detailed plots of flows and stages to confirm numerical stability. Water quality model verification could include test routings of a conservative parameter at a constant rate, as described in Section 5.2.



## 5.4.2 Model Calibration to Measured Data
The term model calibration refers to the adjustment of model parameters (within reasonable limits) so that the simulated response will approximate corresponding measured data. This exercise can serve as a reality check on model results and can help to define model reliability, credibility, and uncertainty. It is important during model calibration that parameter adjustments beyond normal limits are verified or documented with data to establish the basis for the parameter (see Table 5.1).

5-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### It is also important to make sure that land use, floodplain storage, and hydraulic (structures and gates) conditions in the model are applicable to the calibration period. As examples, long term simulations over many years may have significant changes in land use and impervious area, WWTP discharge location changes, and/or major hydraulic changes to a structure. Each of these may warrant modifications for the time periods as part of calibration such as varying impervious area by year (with model “hot starts”), changing WWTP discharge locations, or modifying hydraulics and flows for a structure change at the appropriate time period. Model calibration is a critical element of a detailed modeling process. It is also important to keep in mind the uncertainty of input data and comparative stage, flow, and water quality data during comparisons.

Several statistical analysis methods for data were presented in Section 3 and Appendix 3A. These sections present further details and methods to compare model results to data.



### 5.4.2.1 Water Quantity Model calibration for water quantity requires comparisons with measured data. Such data may be anecdotal or measured. Anecdotal data can include descriptive information obtained from the public or staff (or even news stories or photographs) regarding observed minimum low-flow levels or maximum high-flow levels that occurred on a certain date or following a specific storm event. Measured data may include surveys of high-water marks orcontinuously recorded data at monitoring stations (e.g., time-rainfall, time-stage, timevelocity) within the project area. In some instances, recording stations may be installed to collect rainfall, stage, and flow data for future model calibration if it is determined that detailed modeling is warranted.

Water quantity (hydrology) model calibration also can be time-scale dependant. Depending upon the nature of the problem being assessed, models may be calibrated to one or more discrete storm events, or to a longer period of record (e.g. weeks, months, years). Long-term model calibration is usually done for hydrologic models to support water quality models or for maximum and/or minimum flows and levels within a waterbody over the long term.

In general, the following types of data are needed and may be modified for hydrologic model calibration:

 

### Historical rainfall data (short-term or long-te rm) across the study area (hourly or daily) in adequate resolution to account for spatial and temporal changes;

 

### Evaporation/potential evapotranspiration (PET) data (daily or monthly);

 

### Antecedent moisture condition information (for both event and continuous simulations);

 

### Measured stream stages, velocities, and flows (hourly or daily);

 

### Measured or design event model boundary conditions (vary as necessary);

 

### Soils data in terms of infiltration, runoff potential, soil storage, and potential interflow;

 

### Land use data for the time periods of interest to estimate impervious area;

5-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Groundwater flow (daily or monthly);

 

### Baseflow (daily or hourly);

 

### Channel cross-sections and Manning n roughness values;

 

### Culvert and bridge geometries and properties; and

 

### Lake stage-area-storage-discharge relationship.

Data such as rainfall, evaporation, antecedent moisture conditions, and boundary conditions directly affect the amount of flow and stages that are generated in the study area receiving water network. Modeled stages and flows calc ulated by the model are compared to the measured values to evaluate the accuracy of the model.

There are a number of methods for comparing t he model results to measured flows, stages, and velocities. Several of the more common analysis techniques are described below.

Time series plots - Modeled results and measured data are plotted against time, to see how closely the modeled values match the measured values, and to see if the modeled values follow the upward or downward movement of the measured values (trends). Such comparisons would be appropriate for event or continuous simulations. For discrete events using a dynamic model, results might be printed every 5 to 20 minutes, but this would rarely be required. For a continuous simulation hydrologic model, results might be printed hourly, daily, or monthly. An example of comparative time series plots for a 4-year flow simulation is presented in Figure 5.4

.

Figure 5.4 Example Time Series Plot of Modeled and Measured Daily Streamflows

5-5Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Flow volume comparison

- Comparison of simulated and measured flow volumes for a range of durations can provide information on model performance over different time scales. The following comparisons of measured and modeled streamflow volume should be considered, and are typically reported in acre-ft and percent difference from measured data (volume error):

 

### Total simulation period

 

### Annual

 

### Seasonal (typically wet season vs. dry season for Florida)

 

### Monthly

 

### Daily

It is also recommended that minimum and maximum monthly flow volumes be evaluated. Potential outliers or questionable values in the data or model can be discovered by
evaluation of trends in volume.

Frequency-exceedance plots - The modeled and measured values are plotted against the percent of time the value is exceeded in th e dataset. This is appropriate for continuous simulation results. For streamflow, the plots can be used to see how well the model results represent the range of flows that were measured in the stream. This approach is also useful for comparing measured and modeled concentrations. Because water quality data are typically limited, it may be appropriate to plot model results for the full-modeled dataset, and for a model dataset that includes only results corresponding to the dates when the measured data were collected. Figure 5.5 shows an example frequency-exceedance plot for measured and modeled streamflow data.

5-6Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Figure 5.5 Example Flow Frequency Exceedance Plot of Modeled and Measured Streamflows

Plot of paired measured vs

. modeled data

- Paired values of measured data and corresponding model output data are plotted against one another. If the measured and modeled data were in perfect agreement, the plotted data would fall along a straight line with a slope of 1.0 and an intercept value of 0.0. This type of analysis would be appropriate for
continuous simulation efforts



### .
Linear regression analysis can be done in conjunction with plotting the paired measured and modeled data. A regression line can be drawn to determine the slope of the regression line, the intercept, and the coefficient of determination (R 2 

### ). The slope of the line indicates how well the model captures the trends of the recorded data. An R 2 

### of 0.8 to1.0 indicates close agreement between modeled and measured data, and an ideal match would be an R 2 

### of 1. The intercept can point out systematic errors in the model, and it should be as close to 0.0 as possible. The R 2 

### indicates the percent of variance in the recorded data that is explained by the model. Additional statistics can be calculated to test the hypotheses that (a) the slope of the line is significantly different than 1.0, and (b) the intercept is significantly different than 0.0. An example of a paired-point plot is presented in Figure 5.6 . In this example, approximately 91% of the variation is explained by the regression equation.

5-7Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

USJR at Christmas June 1996 - May 2000

y = 1.0765x - 27.748

R 2 = 0.9081

0 2000 4000 6000 8000 10000 12000

0 1000 2000 3000 4000 5000 6000 7000
Measured Streamflow (cfs)Modeled Streamflow (cfs)



### Figure 5.6 Paired-point Plot with Regression Analysis

Relative error

- This simple statistic is a direct comparison of the means for the measured and modeled datasets. A good starting point for evaluat ing this statistic is to estimate that the relative error should ideally be no greater than potential stream gauging errors, sampling errors and laboratory errors possible in the measured data. The USGS often rates the quality of its flow data, and laboratories can report error based on “blank” samples.

Root mean square error (RMS) - The RMS error measures the precision with which the model tracks measured data variations. As with relative error, the RMS error should ideally be no greater than potential gaging, sampling, and laboratory errors inherent in the measured data.

Nash-Sutcliffe Model Efficiency The Nash Sutcliffe score (Nash and Sutcliffe, 1970) is a measure of model efficiency typically used for evaluating rainfall-runoff models. It is the initial variance less the sum of squared errors, divided by the initial variance:

2 2
0
2
0 

### F F E F −

=

5-8Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Where

E = Nash-Sutcliffe score (dimensionless)


# ( ) 2 2
0 

### F QQ = −



# ∑ 

# ( ) 2 2 

### ˆ F Q = −



# ∑ Q

And

Q = observed flow in ft 3 

### /s or m 3 

### /s



### Q = average flow in ft 3 

### /s or m 3 

### /s

= predicted flow in ft 

### ˆ Q 3 

### /s or m 3 

### /s

It is analogous to the coefficient of determination (R 2 

### ), but there are important differences to be noted. The Nash Sutcliffe score (E) discriminates better than R 2 

### for systematic model bias, consequently reporting a lower score. The range of E is - ∞ < E > 1, but it is typically reported between 0 and 1, as is R 2 

### . A standard reporting scale for this diagnostic statistic is as follows:

> 0.8 very good

0.6 – 0.8 good

< 0.6 fair

0 model accuracy is no better than taking the average of all measured data

Nonparametric comparison of means and distributions - Measured flow data and concentration data generally exhibit skewed (i.e., non-normal) frequency distributions. Therefore, nonparametric tests (which assume no shape for the population distribution) are often used to compare measured data with model results. An example of a nonparametric test for comparing measured and modeled medians is the Wilcoxon Rank Sum Test (Scheaffer and McClave, 1984). The two-sided Kolmogorov-Smirnov (KS) Test (Maidment, 1993) is an example of a nonparametric test that can be used for comparing the distributions of measured and modeled dataset distributions. For both tests, the calculated test statistic value is used to determine if the measured and modeled medians or distributions are significantly different at a selected critical level-of-significance (e.g., 0.05).

Wilcoxon Rank Sum Test The Wilcoxon Rank Sum Test is a substitute of the parametric T-test used for median comparison between two paired samples (Wilcoxon, 1945). In this test, absolute differences

5-9Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### between the measured and the predicted values are ranked from the smallest to the largest before the signs are restored. Then the smallest sum between the negative and positive differences is compared to a theoretical distri bution at a given confidence level to check the null hypothesis of this test. The null hypothesis states that the medians of the measured and predicted values are identical. Readers interested in further details and examples are directed to Snedecor and Cochran (1967).

Two-Sided Kolmogorov-Smirnov Test The Two-Sided Kolmogorov-Smirnov (K-S) Test is a method for evaluating the difference between the distributions of the measured data and model results. Again, the populations of measured data and model results are combined and then arranged in ascending order. Each observation is assigned either a value of 1 or -1 depending on which population the observation is from, and the cumulative sum of the assigned values is calculated. Using the number of measured and modeled data observations, and the maximum absolute cumulative sum of assigned values, a statistical value can be calculated and used to determine the level of significance of the difference between the measured and modeled concentration distribution. If the level of significance is less than a defined critical level of significance (e.g., 0.05), then the conclusion is that the measured and modeled data have significantly different distributions.



### 5.4.2.2 Water Quality

Model calibration for water quality simulations also requires comparisons with measured data available for this purpose. Such data may be anecdotal or measured. Anecdotal data can include descriptive information obtained from the public or staff (or even news stories or photographs) regarding fish kills (low dissolv ed oxygen), observed eutrophication impacts (e.g., such as algae blooms), high levels of visible contaminants such as suspended solids, or a visible sheen from oil and grease. Measured data would include event and/or periodic samples at monitoring stations (i.e., time-rainfall, time-stage or time-flow) within the project area. In some instances, recording stations may be installed to collect rainfall data, flow data and water quality data (e.g., dissolved oxygen) for future model calibration if it is determined that detailed modeling is warranted.

Water quality model calibration also can be time-scale dependant. Depending upon the nature of the problem being assessed, models may be calibrated to one or more design conditions (e.g., 7-day, 10-year low-flow condition or first flush), or to longer periods of record (e.g., weeks, months, years). Long-term model calibration is sometimes done if the problem is more seasonal in nature (wet season water quality problem, or problems in lakes and estuaries with long residence times).

In general, the following types of data are needed for water quality model calibration in addition to those listed for the water quantity (hydrologic) model:

 

### Measured watershed concentrations or loads and receiving water concentrations of parameters of concern, as well as other relevant water quality data if available (i.e., DO may not be a parameter of concern, but would need to be modeled correctly to correctly represent nutrient dynamics in a system);

5-10Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Point source discharge flows and concentrations (daily or monthly);

 

### Load contributions from other intermittent sources such as failing septic tanks or sanitary sewer overflows (SSOs) (hourly or daily); and

 

### Measured or design event model boundary conditions (hourly or daily).

The concepts discussed previously regarding water quantity model calibration apply to water quality model calibration. Time series plots, frequency-exceedance plots, plots of paired values, and statistical tests as presented previously for data and model results are appropriate for evaluating the similarity of measured data and model results. In addition, seasonal or annual loads calculated by the model can be compared with loads estimated from flow data and concentration monitoring data.

In general, water quality calibration is more difficult than streamflow data or stage data calibration. There are several reasons for this:

 

### Measured water quality data are typically more limited and more costly to obtain than streamflow or stage data. Flow or stage data are routinely monitored on a continuous basis, but constituent concentrations are often collected as periodic grab samples. Thus, it is customary to compare measured data to modeled data only on the days corresponding to sample collection days. The statistical tests described in this section compare measured and modeled concentrations only on measured days.

 

### Models often have difficulty in replicating the natural variability in measured water quality due to data and/or model process limitations . For example, water quality models often specify a constant value for baseflow concentration, whereas measured baseflow concentrations could exhibit day-to-day variability due to a number of factors. For stormwater runoff quality, many models rely on mean runoff concentrations (EMCs) or simplified buildup-washoff relationships that do not account for the random factors that influence runoff concentrations. Other potential l oad sources such as failing septic tanks also represent highly variable sources that are difficult to account for on a day-to-day basis. For evaluations in Florida and Georgia (CDM, 2002 and 2001), it was found that sewered areas can have septic tanks, since residents are not always required to convert to sewer. It was also determined at public meetings that many residents did not know their house or business was on a septic tank, especially for homes that had been sold after the sewer project.

 

### Concentrations of sediment and other water quality constituents may increase or decrease in the receiving water network. The characterization of the processes that effect the increase (e.g., benthic release) or decrease (e.g., decay) of constituent concentration in the receiving water network should be considered.

As discussed, the methods previously documented for water quantity data and model results can be applied for water quality data model and results comparisons and evaluations. The following example of a box and whisker plot is provided for reference. This method can also be used for water quantity comparisons.

5-11Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Box and Whisker Plots - Figure 5-7 shows a typical Box and Whisker plot for total nitrogen (TN). The “box” shows the range of data between the 25 th 

### and 75 th 

### percentile, with the lower end of the box representing the 25 th 

### percentile and the top of the box representing the 75 th 

### percentile. The line inside the box shows the 50 th 

### percentile value. The “whiskers” show the range of values that fall within 1.5 times the “spread” of the high and low end of the box (where spread is defined as the difference between the 25 th 

### and 75 th 

### percentile values). Typically, values that are 1.5 to 3 times the spread from the upper or lower end of the box are called “outside values” and are plotted as points.

1 1.5

2 2.5

3 3.5

4TN (mg/l)



### TN (obs) TN (mod) HSPF RCHRES 66 5 - Total N

Figures 5-7 Example Box and Whisker Plot



## 5.4.3 Model Validation
Model validation refers to the comparison of the model results to measured data using a continuous simulation period that is completely independent of the event(s) or simulation period used for model calibration. This technique is often used to validate a “calibrated” model prior to its application to a known critic al design period or condition. For example, if a high flow period or condition is used for calibration, then a low flow period or condition could be used for validation, especially if the pollutant of concern is a problem during different periods, conditions, or seasons. In other words, the calibration and validation period should cover the potential “design conditions” that are pertinent to the pollutant(s) of concern.

Preferably, the combination of calibration and validation periods will include at least one “wet” year, one “average” year, and one “dry” year, and the water quality calibration and validation periods should ideally be the same as the water quantity calibration periods.

5-12Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### As previously discussed, anecdotal information can be used for limited model validation but should never be given a preference or priority over the use of model calibration using measured data. These types of data are more descriptive in nature and can be used to see if the predicted results approximate reported flooding problems. Examples of anecdotal information can include reported fish kills, algal blooms, turbidity problems, and low or high water marks or debris lines. Anecdotal information is often collected from the public, and therefore, validation of these data to the model results can often lead to public support of the predictive tool being used to address a problem. However, it should be noted that a model should never be considered fully cali brated based upon anecdotal data alone.

It may be necessary to repeat or refine calibration and validation if the validation process yields unsatisfactory results in terms of the water quality and/or water quantity models matching observed data. Uncertainty should be defined at this point.



## 5.4.4 Uncertainty Analysis and Margin of Safety
Based on EPA guidelines (40 CFR 130.2(I)), the calculation of the TMDL should contain an uncertainty allowance referred to as the “margin of safety” (MOS). The MOS allowance may be addressed using either “implicit” or “explicit” methods. For the implicit approach, the MOS is assumed to be embedded in the analyses. Examples would include selection of conservative parameter values for the wate r quality model used to develop the TMDL, or achieving a standard that is more stringent than the actual standard. For the explicit approach, the MOS is quantified (e.g., expressed as number of pound per year of pollutants). This value can be established as a percentage of the allowable load (say 10 percent to 20 percent) or by applying uncertainty analysis to the calibrated water quality model.



### 5.4.4.1 Implicit and Explicit Margins of Safety

Implicit Margin of Safety An implicit margin of safety is not expressly stated, but rather is implied and/or is inherent in the data and/or analyses performed for the TMDL. In many cases, practitioners “compound” implicit MOS by choosing “conservative” numbers for rainfall, soils, initial abstractions, ET, land use and impervious area, surface storage, groundwater flow, event mean concentration (EMC) or related pollutant load data, and BMP removal efficiencies.

Data, model limitations in processes, budget, and schedule can each constrain the practitioner’s ability to provide a very accurate result with a small band of uncertainty. As discussed in Sections 3, additional data or model refinements may be necessary in subsequent rounds of TMDL refinement and implementation. Where possible, the practitioner should document the data decisions on “conservative” choices (e.g. use 40 versus 30 percent impervious area due to variations in land use over a data collection or simulation period) in case explicit uncertainty and margin of safety must be estimated later in the TMDL implementation.

Sensitivity analyses can be performed with “c ompound” implicit MOS decisions to see the impact on the resultant flows, loads, and concentrations. It should be noted that compounding implicit conservatism can potentially lead to oversized treatment facilities (e.g.

5-13Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### BMPs) to achieve the PLRG from a “conservative” TMDL. When put in the context of “right sizing”, the more defined and explicit the MOS, the more public funds can be used for other programs to achieve state-wide water quality goals.

Explicit Margin of Safety The three most common methods for uncertainty analysis of the calibrated/validated TMDL model are as follows:

 

### Sensitivity Analysis

 

### First-Order Error Analysis (FOEA)

 

### Monte Carlo Simulations

Each of these methods is described below. The use of these uncertainty analyses to define the MOS allowance for the TMDL is described in Section 6.4.



### 5.4.4.2 Sensitivity Analysis

To conduct a sensitivity analysis, selected model input parameters are varied within a range of realistic values to evaluate the resulting change in modeled watershed and/or receiving water output response. Ultimately, these respon ses or variations in sensitivity may be used to determine the impact of model uncertainty on management plan (implementation strategy) decisions. The sensitivity analysis provides an understanding of how the model responds to changes in input parameters. In many cases, this could identify the need for better data to define the unknown parameters. Knowing the response and relative degree of sensitivity of individual parameters, a combination of model parameter changes can be tested as a means of achieving improved calib ration, less uncertainty, and greater model reliability. For many hydrologic applications in Florida, rainfall and tributary area are the most sensitive parameters for wet weather evaluations, followed by percent of DCIA, and subsequently by soils (CDM, 1992).

For sensitivity analysis and for model calibration, the range over which a parameter is adjusted should reflect how much confidence the practitioner has in their original parameter estimate. For example, some hydrologic par ameters may be empirical (e.g. curve number), theoretical and/or difficult to measure for full representation of the watershed, whereas many hydraulic parameters (e.g., structure geometry) can be accurately surveyed. As discussed, parameters in which the practitioners have the least confidence should be targeted for adjustment (e.g., decay coefficients). In many cases, the sensitivity analysis will identify parameters that have little effect on the system response; in which case, the confidence in estimating such parameters would be less important.

The TMDL model sensitivity analysis should result in a table of values for parameter sensitivity coefficients (S i 

### ) which represent the percentage change in the model output for a one percent change in input parameter values. Table 5.3 shows an example of a summary table of sensitivity parameters for a 30% adjustment of parameters for the Upper St Johns River. These sensitivity coefficients can be derived by performing multiple sensitivity simulations of the TMDL model (individual model runs for each parameter) and averaging the ratios of the output and parameter value changes, as illustrated in the example below for a calibrated instream rate coefficient.

5-14Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Sensitivity Model Run No. 1: 25 percent increase (or another range) in rate coefficient reduces output concentration by 5 percent (sensitivity coefficient = 5%/25% = 0.20)

 

### Sensitivity Model Run No. 2: 25 percent decrease in rate coefficient increases output concentration by 3 percent (sensitivity coefficient = 3%/25% = 0.12)

 

### Average Sensitivity Coefficient (S i 

### ) for Rate Coefficient: (0.20 + 0.12)/(2) = 0.16

Another similar approach would be to define an uncertainty “band” for input data and model results by varying parameters to the high and lo w extreme possible values, note sensitivity, and choose the parameter range to be used for simulation.

Table 5.3 Example Summary Table of Sensitivity Parameters and Results

Percent Change over Entire Simulation

6E Jane Green 6F Lake Washington 6G Lake Poinsett Parameter Adjustment

Total N Total P Total N Total P Total N Total P

+30% 28% 26% 17% 14% 19% 15% Land Based Loads (lbs)

-30% -30% -30% -16% -14% -20% -16%

+30% -1.3% -2.7% -0.1% -2.6% -1.0% -3.5% PHYSET: Phytoplankton settling (ft/hr)

-30% 1.3% 0.5% 2.0% 4.4% 1.0% 4.5%

+30% 1.4% 0.4% 1.5% 3.4% 0.8% 3.8% CMMP:MichaelisMenton Constant for Phosphorus -30% 0.8% -1.5% -0.3% -3.3% -1.3% -4.8%



### Those model input parameters which exhibit the greatest sensitivity factors for the calibrated/validated model should be screened by the practitioner to determine whether recalibration and/or the collection of additional back-up field data is justified. In many cases, recalibration and/or the collection of additional field data will not be necessary, assuming the calibrated parameter value is within the range of typical literature values and was selected by calibrating to a sufficient amount of observed water quality data. The sensitivity coefficient table of values can be used to perform the FOEA evaluations described below.

Listed below are the key variables which should be included in the sensitivity analysis of the calibrated/validated TMDL models (both water quantity models and water quality models):

5-15Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Quantity

 

### Rainfall and its temporal and spatial variation

 

### Tributary areas for flat interconnected systems

 

### Directly connected impervious areas

 

### Pervious and impervious area runoff coefficients

 

### Representation of overland flow and channel friction

 

### Soil infiltration rates and soil storage values

 

### Baseflow and groundwater inputs

 

### Channel cross-section data and values where detailed survey is not available

 

### Bathymetry of lakes and wetlands wher e detailed survey is not available

Water Quality - General

 

### Baseflow and groundwater concentrations

 

### Nonpoint sources (e.g., surface runoff, failing se ptic tanks, sanitary sewer overflows)

 

### Point source discharges and leaking sewers (e.g., stream crossings)

 

### Settling and stream scour rates

 

### General first-order decay rate or delivery ratio

Water Quality – Dissolved Oxygen/BOD

 

### Watershed BOD loads

 

### Reaeration coefficient (often calculated from modeled depth and velocity)

 

### CBOD decay rate

 

### NBOD decay rate

 

### Sediment Oxygen Demand (SOD)

 

### Algal growth and death rates, and oxygen-to-biomass ratios (if algal biomass is modeled)

 

### Water temperature (affects decay rates, saturated DO concentration)

5-16Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Water Quality – Nutrients

 

### Watershed nutrient loads and variability

 

### Net flux rate of nutrients between sediment and water column

 

### Atmospheric wet- and dry-fall

 

### Decay rates (e.g., breakdown of organic N and P, nitrification)

 

### Settling rates for particulate nutrients

 

### Algal growth and death rates, algal settling rates, and nutrient-to-biomass ratios (if algal biomass is modeled)

 

### Water color/light extinction (if algal biomass is modeled)

Water Quality - Pathogens

 

### Watershed pathogen loads (event and seasonal variability)

 

### Net first-order bacteria loss rate (base decay rate plus impacts due to light and temperature mortality, transformation and re-growth)

 

### Potential septic tank and SSO load contributions



### 5.4.4.3 First-Order Error Analysis (FOEA)

FOEA uses the first-order approximation to compute the overall variance for a multivariate model. First, the fraction of model output variance contributed by each key input parameter is determined. Next, a first-order approximati on is used to calculate the overall model variance from the variance and sensitivity coefficient for each model parameter.

The following steps in an FOEA for a TMDL study are outlined and demonstrated by Zhang and Yu (2004):

1. Determine the key input parameters in the calibrated/validated model: For the TMDL water quality model, these will typically include: rate coefficients for growth (algae), decay (BOD/DO), die-off (bacteria), and transformation to other forms (nitrification); temperature correction coefficients; settling rates; adsorption rates; and release rates (benthic).

2. Calculate the sensitivity coefficient (S i 

### ) for key input parameters: The table of values for the sensitivity coefficients derived by the sensitivity analysis (see Section 5.4.4.1) can serve as an approximation of the partial derivative of the model with respect to each parameter. The sensitivity coefficient for each input parameter is derived by dividing the percent change in model output (e.g., maximum or minimum instream concentration) by the percent change in the parameter value based on single parameter sensitivity runs of

5-17Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### the TMDL model). The sensitivity coefficient (S i 

### ) for each variable is expressed as a decimal fraction.

3. Estimate the Coefficient of Variation (COV) for each key model input parameter: The COV (ratio of standard deviation to the mean) for model parameters can be based on ranges reported in the general literature and the judgment of the TMDL modeler. Examples of COV ranges reported in the literature are as follows:

 

### Continuous simulation hydrologic model (early version of HSPF): COVs range from 0.1 to 0.5 for soil moisture parameters, with typical values in the range of 0.1 to 0.25 (Garen and Burges, 1981);

 

### Rate coefficients for QUAL2E model (Brown and Barnwell, 1987): COVs typically range from 0.02 to 0.25;

 

### Lake eutrophication model (Scavia, et al ., 1981): COVs range from 0.16 to 0.33 for algal growth rates and chlorophyll-a composition ratios and range from 0.1 to 0.4 for other model parameters.

4. Perform the FOEA analysis based on results of steps 1 through 3: Compute the overall variance of the TMDL model based upon the following approximation of the first-order expansion equation (Zhang and Yu, 2004):



## ( ) 

# [ ] ( ) 

# [ ] ( ) 2
i p

i 2
i 2 

### S*XCOV CCOV 

# ∑

=



### where COV(C) = The overall COV for the calibrated TMDL model’s simulation of the instream concentration “C” which is the focus of the TMDL study

COV (X i 

### ) = The COV for each key model parameter (ranging from “i” to “p” parameters)

S i 

### = The sensitivity coefficient for each key model parameter (ranging from “i” to “p”) as derived in Step 2

The COVs and the S i 

### values in the expansion equation are all expressed as decimal fractions.

The calculated COV(C) value for the TMDL model’s simulation of instream concentration provides a quantitative assessment of overall uncertainty associated with the TMDL model. A COV(C) value less than 0.1 is an indication of fairly low model uncertainty, whereas a value greater than 0.4 to 0.5 is an indication of fairly high model uncertainty. The COV(C) value calculated from the FOEA can be used to establish the Margin of Safety (MOS) for the TMDL, with larger values associated with a greater MOS and vice versa. Section 6.4 summarizes procedures for incorporating the FOEA analysis into the determination of the MOS allowance for the TMDL. Table 5.4 and Figure 5.8 present an example application from the Hillsborough River.

5-18Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 5.4 Summary of First-order Error Analysis for Lower Limit (-50%) on DO Variability (Flint Creek and Hillsborough River Below Lake T)

Below the Lake Com p onent of Variance

Input Variable Standard Dev. #6 #13 #16 #6 #13 #16

1st order BOD decay rate 0.175 0.036 0.017 0.185 0.1% 0.0% 2.2%

1st order nitrification rate 0.175 0.0219 0.000568 0.0155 0. 0% 0.0% 0.0%

Sediment Oxygen Demand 0.175 0. 934 0.412 0.819 46.4% 27.2% 43.4%

1st order reaeration rate 0.175 -0. 868 -0.611 -0.717 40. 1% 59.7% 33.3%

DO boundary concentration 0.175 -0. 078 -0.285 -0.482 0. 3% 13.0% 15.0%

Chl-a growth rate 0.175 -0.452 -0.018 -0.302 10.9% 0.1% 5.9%

Chl-a settling rate 0.175 0. 205 0.01 0.0461 2.2% 0.0% 0.1%

Coef. of Var. 2 0.058 0.019 0.047 100.0% 100.0% 100.0%

DO Median (mg/L) 4.609 5.832 4.668

DO Standard Deviation (mg/L) 1.106 0.807 1.015

0 1 2 3 4 5 6 7 8 9 10 11 12

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 .0 

### Cumulative DistributionDO less or equal to (mg/L) Cum. Dist. of predicted DO with high (+50% ) SOD at segment # 13 Cum. Dist. of predicted DO with average SOD at segment # 13 Cum. Dist. of M easured DO at Segment # 13 Cum. Dist. of predicted DO with low (-50% ) SOD at segment # 13 DO Water Quality Standard (5 mg/L)



### Figure 5.8 Effect of SOD on DO Distribution at Segment #13 (Below the Lake Model)

5-19Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### The calculated COV(C) value can be converted to a standard deviation (SD) for evaluations of error bounds for the TMDL model simulations. This conversion can be calculated by multiplying the model’s COV(C) value by the mean concentration ( 

### C ) for the TMDL model
simulations (i.e., SD = COV(C) * 

### C . For steady-state model applications where the TMDL model output matches the instream water quality standard (WQS), the SD can be calculated by multiplying the COV(C) by the WQS (i.e ., the maximum or minimum concentration limit) which is the basis of the TMDL. If the TMDL model’s simulation of the instream concentration is consistent with an approximately normal distribution, there is an 84 percent probability of complying with the TMDL water quality standard (WQS) if the TMDL is based on an allocated load which produces a mean concentration that is one SD less than the WQS (or one SD greater than the WQS for a minimum concentration standard). Similar error bounds can be developed for a safety factor based on other multiples of SD (e.g., 90 percent compliance probability for 1.3 SD and 95 percent for the 1.64 SD).



### 5.4.4.4 Monte Ca rlo Simulations Monte Carlo simulations can be used to develop uncertainty bands for assessments of the calibrated/validated TMDL model. The Monte Carlo simulation method relies upon statistics on the TMDL model’s input parameters (e.g., mean, SD) to develop a set of randomly sampled parameters for the TMDL model which is repeatedly executed with each new set of parameters. Following numerous model runs with the different parameter values (on the order of several hundred to several thousand model runs), the summary statistics are calculated for the simulated instream concentrations (mean, SD, COV). The summary statistics for the model output can be used to develop uncertainty bands for the TMDL model (e.g., plots of mean concentration plus or minus one SD). As discussed in Section 6.4, the uncertainty bands based upon the Monte Carlo simulations can also be used to develop an MOS for the TMDL study.

Monte Carlo simulations are repetitive runs to test a model over the full probability distribution of the input parameters. These distributions are either derived from field measurement or estimated by the modeler. A Monte Carlo simulation includes repetitive runs during which input parameter values are randomly selected from their distribution before the model calculation. As a result, each run is a unique representation of reality with its associated probability of occurring. By definition, extreme values have a low probability of occurring compared to central values. Model outputs from the large number of runs are ultimately analyzed to determine statistical moments of transport and flow characteristics (e.g., mean, standard deviation of resident concentration, water flux, and stream flow) and/or to estimate their frequency distribution.

Monte Carlo techniques are included in some models, such as QUAL2E and EUTROMOD, and provide the most robust estimate of uncertainty estimates. Such simulations should be included in the most complex of analyses if no other uncertainty elements are included and the results of the probability distribution should be included in the model documentation. The QUAL2E user’s manual (Brown, L.C. and T.O. Barnwell, 1987) provides an explanation of the calculations used by the model in conducting Monte Carlo simulation, as well as general ranges of expected variability for various model input parameters, and an example application using the model.

5-20Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Compared to FOEA methods, Monte Carlo simulations represent a more complex type of model uncertainty analysis. As discussed, pr evious studies which have compared these two uncertainty analysis methods have found that the FOEA method can produce similar results which are sufficiently accurate for assessments of overall model variance (Zhang and Yu, 2004; Warwick, 1997; Scavia, et al., 1981). Therefore, the simpler FOEA method should provide an adequate evaluation of uncertainty for most TMDL modeling applications.

5-21Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# SECTION 5 REFERENCES

Beven, K. J. 2001. Rainfall-Runoff Modelling: The Primer, Wiley, Chichester.

Brown, L.C. and T.O. Barnwell, The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Documentation and User Manual, EPA/600/3-87/007, May 1987.
CDM. 1992. City of Jacksonville Master Stormwater Management Plan.
CDM. 2001. Big Creek Water Resource Management Plan.
CDM. 2002. Evaluation of High Water Impacts to Stormwater Systems and Other Facilities on the Harris Chain of Lakes.
Chow, V.T. 1959. Open Channel Hydraulics. McGraw-Hill.
Garen, D.C. and Burges, S.J. 1981. “Approximate Error Bounds for Simulated Hydrographs.” ASCE Journal of Hydraulics Division, 107(11), pp. 1519-1534.

Maidment, D.R. 1993. Handbook of Hydrology.

Nash, J.E., and I.V. Sutcliffe. 1970. River Flow Forecasting through Conceptual Models. Journal of Hydrology. 273, 282-290.

Scavia, D. 1981. “Comparison of First-Order Error Analysis and Monte Carlo Simulation in Time-Dependent Lake Eutrophication Models.” Water Resources Research, 17(4), pp. 1051-1059.

Scheaffer, R.L. and J. McClave. 1994. Probability and Statistics for Engineers.

Snedecor, G. W. and W. Cochran. 1967. Statistical Methods, Sixth Edition, The Iowa State University Press, Iowa, USA.

Warwick, J.J. 1997. “Use of First-Order Uncertainty Analysis to Optimize Successful Stream Water Quality Simulation.” Journal of American Water Resources Association, 33(6), pp. 1173-1185.

Wilcoxon, F. 1945. Biometrics Bul., 1:80.

Zhang, H.X. and Yu, S.L. 2004. “Applying the First-Order Error Analysis in Determining the Margin of Safety for Total Maximum Daily Load Computations.” ASCE Journal of Environmental Engineering, 130(6), pp. 664-673.

  

5-22Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Section 6
MODEL APPLICATION

Notes:

1. Preparation, verification, calibration, and validation (PVCV) Tech Memo PVCV of Current Conditions

FDEP
A cceptance C/L/S Meeting

No

TARC
Review Current Conditions
Watershed Model Tech Memo

Review Comments TMDL Modeling

Tech Memo Refinement of TMDL Objectives

Definition of

Conditions Restatement of TMDL Modeling

Objectives Tech Memo 9

10

11

12

13

14 Design and Simulation Design and Simulation Conditions

Current Conditions

Receiving Water

Model, TMDL, Uncertainty, and Recommendations PVCV of Current Conditions Receiving Water Model 1

Yes



### 6-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# 6.1 INTRODUCTION

The previous sections presented examples of how data are collected and analyzed, appropriate model(s) are selected, the chosen model(s) are prepared for the specific parameters and conditions for the water body under study, and the model(s) are verified, calibrated and validated. The model(s) may now be used to simulate various conditions to provide estimates of the total amount of pollutants that can be discharged to the water body to meet water quality standards and to achieve the designated uses. The practitioner can use the model(s) to identify the critical loading(s) at which the designated use(s) would not be met (i.e., the level at which applicable standards would be exceeded), reduce the allowable loading to account for uncertainty and a margin of safety, and designate the reduced loading as the total maximum daily load (TMDL) allowed to be discharged by human and non-human or background sources. The identification of the process of determining the critical loading may require several model simulations to determine the maximum load. The purpose of this section is to describe the simulations that may be conducted for the TMDL analysis and definition.



# 6.2 SIMULATIONS OF DESIGN CONDITIONS AND PERIODS

Information from Section 3 (Data Acquisition and Assessment) and Section 5 (Model Preparation, Verification, Calibration, and Validation) may be used to identify the conditions under which the pollutant(s) of concern have t he greatest impacts. For example, stormwater sources generally have a greater impact on receiving water quality during high rainfall conditions, and WWTP point sources generally have a greater impact during extended dryweather, low-flow conditions. The design conditions and periods may also depend upon the type of receiving water body. Streams may have more short-term impacts in comparison with lakes and estuaries with extended residence times, where seasonal conditions may be more important. Therefore, the practitioner may identify critical loadings on an hourly, daily, monthly, seasonal, and/or annual basis for determination of a TMDL.

In general, design or critical time period conditions can be identified and considered by parameter as follows:

 

### Dissolved oxygen: For free-flowing streams, the design condition for dissolved oxygen and biochemical oxygen demand is generally during periods of high water temperature and low-flow conditions. Higher temperatures result in lower DO saturation, which in turn limits the rate of stream reaeration. Because reaeration is also a function of turbulence and velocity (reaeration increases as velocity increases), low-flow conditions may also limit the rate of reaeration. Concurrently, reaeration rates can increase to some degree as depth decreases due to an increase in the ratio of surface area to volume in a reach. High temperatures can also increase the rates of other processes (e.g., SOD, BOD, nitrification) which use oxygen in the stream, and SOD impacts tend to increase as the depth of water decreases. Low-flow conditions also limit the amount of dilution of point source loads, thus concentrations of oxygen-demanding substances from point sources in low flows will be high relative to stream concentrations under medium and high-flow conditions.

6-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Lake and estuary design conditions for DO/BOD analyses would also consider high temperature, low-flow conditions, but the focus is more likely to be monthly, seasonal, and/or annual due to the extended residence times in these types of water bodies. Because of the longer residence times, algae may be a concern and likely will be a necessary process to model. Though algae may provide a net increase in water body oxygen, these plants will also result in greater diurnal swings in DO concentration, and thus may result in exceedance of the minimum DO standard especially at night during the dark cycle, even when the average DO st andard is being met. Robust colonies of aquatic plants (e.g., hydrilla) can dramatically a ffect DO ranges. Anecdotal reports of fish kills from low DO can also be used as part of the validation process.

 

### Nutrients: For free-flowing streams with short travel times (<12 hours), instream nutrient concentrations in and of themselves may not be a concern. The exception would be the concentration of ammonia nitrogen, because the un-ionized fraction of ammonia nitrogen can be toxic to aquatic organisms. In such cases, low-flow conditions with less opportunity for point source dilution would be a critical design condition. The fraction of ammonia that is un-ionized also depends upon the water pH, with higher pH values yielding a higher fraction of un-ionized ammonia. Otherwise, nutrient loads in streams are generally of concern as they affect downstream lakes or estuaries.

Lake and estuary design conditions for nutrients would typically consider both high- and low-flow conditions. In many cases, the most critical design condition would be a wet period (with high flows discharging nutrients to lakes and estuaries) followed by an extended dry period with extended residence times providing the opportunity for excessive algal growth. The algal growth can raise the pH in the water, which in turn may result in higher nutrient releases from the sediments, further stimulating algal growth. In tidal estuaries, seasonal changes in tidal fluctuation can affect the tidal flushing, thus causing greater nutrient impacts during periods with less flushing.

 

### Pathogens: Pathogen concentrations can be high relative to typical standards, even in undeveloped areas. This suggests that natural background may be an important consideration (Schueler, 1999; Pitt, 1998; CDM, 2001). The geometric mean of pathogens in surface runoff (wet-weather conditions) is typically an order of magnitude higher than the geometric mean of baseflow (dry-weather) conditions. In addition, runoff concentration may vary significantly by season, with summer concentrations being an order of magnitude higher than winter concentrations based on data from the NURP study (USEPA, 1983) and select NPDES Phase II and other local monitoring data (CDM, 2001). This is offset to some degree by the fact that summer stream conditions also include higher water temperature, greater solar radiation and lower stream depth (greater light penetration), which would cause higher pathogen die-off rates relative to winter conditions.

For lakes and estuaries, the extended residence times are likely to result in significant potential for pathogen die-off and transformation. Lakes with residence times of weeks to months may remove or transform as mu ch as 60–90 percent of incoming pathogens. However, lakes may also have natural background loads (e.g., from warm-blooded aquatic wildlife) that raise pathogen concentrations. Estuaries generally have more

6-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### restrictive standards for pathogens due to potential shellfish and fish consumption, but also provide more opportunity for dilution due to tidal mixing. In both lakes and estuaries, the die-off of pathogens due to light mortality can be limited by algal growth that reduces light penetration. Atypical coliform bacteria may also be considered, as discussed in Section 3.

 

### Metals and Other Parameters: For parameters such as heavy metals and organic chemicals, both high- and low-flow conditions may be critical, since these pollutants can be discharged by both point and nonpoint sources. Since metals standards are hardness based, hardness may be evaluated or modeled if possible to correlate metals concentrations if necessary with published standards in order to consider potential bioaccumulation. Pesticides and herbicides can also dramatically affect water quality and biota. Discharges of these compounds can cause toxic reactions (e.g., fish kills) or in the case of herbicides, may artificially lower Chl-a levels.

Regardless of the design conditions pertinent to the pollutant(s) of concern, if necessary, the water segment may be simulated with and wit hout human impacts to identify the relative contributions of human impacts and natural background sources. For point sources, such simulations are relatively straightforward – the point source can simply be set to zero flow. For non-point sources, such as surface runoff from urban and agricultural development, this requires further analyses. A discussion of various methods to conduct such an analysis is provided below.



## 6.2.1 Natural Background Conditions
For the purposes of this protocol, the term natural background refers to the pollutant loading condition of the water segment in the absence of anthropogenic pollutant loads. For point sources, this condition can be evaluated by simulating the water segment with zero point source discharge. For nonpoint sources, the watershed model can be adjusted based on the condition that the study area was undeveloped (i.e., no urban or agricultural development).

Specific data on wildlife contributions (historic and current) may be difficult to obtain, but such loads can dominate a system (e.g., ducks, geese, wading birds). Local data are recommended for systems with significant wildlife interaction, especially for pathogens.

The discussion below focuses on suggested adjustments to watershed models and receiving water models. Many of the issues discussed below would have been considered in the initial model evaluations (e.g., preparation, verification, calibration, and validation), and therefore may be repetitive or iterative as refinements are made.

Watershed Baseflows : Baseflow rates from study area watersheds (or nearby areas) can be identified through analysis of gaged flow data using readily available baseflow separation techniques (Section 3). Such analyses would identify the portion of gaged flow that can be attributed to baseflow versus surface runoff. Analysis of data for a “critical” period would determine the baseflow quantities during that period, and long-term flow analysis would be used to estimate average annual and seasonal baseflow rates. If gaged flows are not available, a literature review may yield inform ation on long-term hydrologic information (e.g., annual average water budget of rainfall, evapotranspiration, runoff, and baseflow), and local

6-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### rainfall data may be used to designate wet-weather and dry-weather condition during a “critical” evaluation period. Some watershed models (e.g., WMM, SWMM) can accept baseflow quantity as input values or time series, whereas some other models (e.g., HSPF) would need to be calibrated to calculate the water balance (including baseflow discharge) on a continuous basis.

It should be noted that most models consider that baseflow is contributed only by pervious land surfaces in the study area. Consequently, measured baseflow rates may be evaluated with respect to the fraction of the study area t hat is pervious land. For example, in a study area that is 10 percent impervious and has a measured baseflow of 6.3 inches per year, the baseflow rate from a totally undeveloped (natural background) condition would be 7.0 inches (i.e., 6.3 divided by 90% perviousness).

Baseflow water quality is often estimated using instream water quality data because groundwater quality data are typically scarce. The instream data would be evaluated in conjunction with evaluation of baseflow rates and/or analysis of wet-weather/dry-weather periods. Ideally, instream water quality data would be separated into dry weather (baseflow) samples and wet weather samples (i.e., samples affected by storm water runoff and/or interflow). Dry-weather samples would be evaluated to establish appropriate baseflow concentrations for the pollutants of concern. The exception would be dissolved oxygen (DO), for which the baseflow concentration to the stream is often established as a percentage of saturation DO at the design water temperature.

The above discussion is based upon the condition that baseflow concentrations at the sampling location would not be affected by point s ource discharges. It is relatively simple to determine if point source discharges are contributing upstream of the sampling station, but their effect on instream concentrations requires evaluation. The practitioner may be able to factor out the point source discharge(s) from the baseflow quantity and quality if sufficient data regarding the point source discharge rate and quality are known. Another alternative would be to analyze water quality data from a “reference” site (i.e., site monitoring an area without point source discharges).

Even if conditions at the monitoring site are not affected by point source discharges, the water quality measured at the site may be affected by human impacts. For example, baseflow nitrogen and phosphorus concentrations in a residential area may be higher than in a forested area because fertilizers and other human impacts have raised local groundwater concentrations. Literature values may be useful to estimate how much one could expect groundwater concentrations of the constituent of interest to change due to development (Section 3). Again, a “reference” site in an undeveloped area may provide a suitable basis for estimating baseflow concentrations that have not been affected by human impacts.

Watershed Runoff : Runoff rates from study area watersheds (or nearby areas) can also be identified through analysis of gaged flow data using readily available baseflow separation techniques (Section 3). The portion of gaged flow that is not contributed by baseflow would be surface runoff and interflow. Data for a “critical” period would be analyzed to estimate the runoff quantities during that period, and long-term flow analysis would be used to estimate

6-5Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### long-term average annual and seasonal runoff rates. If data regarding gaged flows are not available, a literature review may yield inform ation on long-term hydrologic information (e.g., annual average water budget of rainfall, evapotranspiration, runoff, and baseflow) and local rainfall data may be used to designate wet-weather and dry-weather conditions during a “critical” evaluation period. Some watershed models (e.g., WMM) can accept runoff coefficients for pervious and impervious surface as an input value, whereas more complex models (e.g., HSPF) would need to be calibrated to calculate the water balance (including runoff and interflow discharge) on a continuous basis.

Because runoff is generated by both pervious and impervious land surfaces, measured runoff rates may be evaluated with respect to the fractions of the study area that are pervious and impervious land. For example, consider a study area that is 10 percent impervious and has a measured runoff quantity of 9.0 inches per year and is located in an area that receives 50 inches of rain. If it is expected that a high fraction (90-95 percent) of rainfall is converted to runoff for impervious areas; in this study area, the runoff due to impervious land would be 4.5 inches per year (50 inches of rain * 90 percent conversion of rainfall to runoff * 10 percent impervious area). The remaining runoff (9.0 – 4.5 = 4.5 inches per year) is attributed to pervious land area, and the unit runoff from pervious land would be 5.0 inches per year (4.5 inches / 90 percent of area = 5.0 inches).

Runoff quality is typical defined based on land use, using single land use monitoring data from sources such as the NURP study or NPDES Phase I and Phase II data collection. Unfortunately, monitoring data from such sources tends to reflect mainly urban land uses, and limited monitoring of undeveloped land is c onducted by most stormwater management programs, although data are being collected and analyzed as part of the Comprehensive Everglades Restoration Program (CERP). If there is a “reference” site in an area of little or no development, it may be possible to estimate runoff concentrations using instream water quality data (CDM, 2001). The instream data would be evaluated in conjunction with evaluation of runoff rates and/or analysis of wet-weather/dry-weather periods. Ideally, instream water quality data would be separated into dry-weather (baseflow) samples andwet-weather samples (samples affected by storm water runoff and interflow). Data from wetweather samples would be evaluated to establish appropriate runoff concentrations for the pollutants of concern. The exception would be dissolved oxygen (DO), for which the runoff concentration to the stream is often established as a percentage of saturation DO at the design water temperature.

Receiving Water : In general, the receiving water model prepared as discussed in Section 5 would be applied using watershed flows and loads with no development, as discussed above. However, some receiving water input values may be modified if natural background conditions are being used. Examples of these would include:

 

### Boundary conditions . Upstream, downstream, or lateral inflow boundary concentrations under existing conditions may reflect human impacts. It may be appropriate to reduce the boundary concentrations based on typical concentrations from a “reference” site;

 

### Sediment oxygen demand (SOD) . In many cases, existing SOD rates are in part dependent upon oxygen-demanding substances that in the past were generated due to

6-6Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### human impacts. It may be appropriate to re view literature values or measured SOD values from a “reference” site to determine whether background SOD values would be expected to be lower than existing values;

 

### Other sediment fluxes . Similarly, human impacts may have caused higher loads of nutrients, metals, or other compounds in the sediments, with resulting increases in flux from the sediment to the water column;

 

### Water temperature . Impervious cover tends to produce runoff of a higher temperature than pervious area (James, 1997). Consequently, stream receiving water temperatures may have risen due to urbanization. It would be difficult to quantify this without long-term data.

 

### Light extinction coefficient . The light extinction in a stream, lake or estuary generally is related to suspended solids and algae in the water. Therefore, the light extinction under existing conditions may be greater than under background conditions.

 

### Plant respiration . The respiration of submerged aquatic vegetation can cause large fluctuations in DO, especially at night.



## 6.2.2 Existing Conditions
For the purposes of this document, the term existing conditions refers to the pollutant loading condition of the water segment based on “permitted” discharges to receiving waters. This condition would include permitted discharge flows and water quality constituent concentrations, stormwater runoff flows and loads under existing land use and implemented water quality controls (BMPs), and baseflow quantity and quality based on existing land use. Existing conditions could vary over time due to changes in permitted discharges, land use, hydraulics, and other factors.

In general, analysis of existing conditions would use the models and approaches as described in Section 5. These models would have been calibrated and validated through comparison of measured and modeled flows and concentrations, and the practitioner would adjust model input parameters to provide an adequate match between measured data and model output data. For this analysis, however, the period of simulation would be based on the “critical” design conditions and/or time periods discussed earlier.

Potential differences between the input to the calibrated/validated model and the “existing conditions” model are discussed below:

 

### Point source discharges : The calibrated/validated model would typically use measured values of flow and concentration for the simulation. In contrast, the “existing conditions” model should use the maximum permitted flows and concentrations, which in most cases will provide a greater load than actual measured flows and concentrations.

 

### Meteorological data : If the designated critical design condition reflects a period other than the periods used for model calibration and validation, then meteorological data for the critical period needs to be used as model input. For continuous simulation,

6-7Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### metrological data that may be used for wate rshed and receiving water analysis includes rainfall and evapotranspiration for hydrologic analysis, and potentially solar radiation, wind and air temperature for water quality simulation. For steady-state conditions, it may be appropriate to establish a “design” value for the meteorological data based on analysis of historical data. For example, if the analysis is for a steady-state analysis for low flow conditions, the air temperature or solar radiation data can be established based on historical data for periods corresponding to the month(s) in which low flows most commonly occur. For a continuous simulation, a time period and associated meteorological dataset may be defined to reflect the full range of hydrologic and water quality variation (5 to 10 years or longer, such as 40 to 50 years).

 

### Water temperature data : If the designated critical design condition reflects a period other than the periods used for model calibration and validation, then water temperature data for the critical period need to be used as model input, unless water temperature is being modeled. In the absence of measured or modeled water temperature, a typical time series of water temperatures based on time of year can be developed from existing monitoring data. For steady state conditions, it would be appropriate to establish a “design” value for the meteorological data based on analysis of historical data.

 

### Land uses and BMPs : The existing conditions model would likely simulate the most current land use, imperviousness, and BMPs.

 

### Hydraulic features : Changes in bridges, culverts, structures and/or operation of structures may cause these conditions to be different for the existing conditions model(s).

Other model input parameters (e.g., first-order decay rates, temperature correction factors) should remain the same as the values developed in model calibration and validation unless specific variations are applicable for the simulation time period or condition.



# 6.3 CALCULATION OF THE TMDL

If the analysis of critical design conditions shows that receiving water quality standards would be exceeded under existing loading conditions, the model may be applied to determine the total maximum daily load (TMDL). The TMDL can be calculated by several methods depending on whether the parameter is conservative (e.g., freshwater, chloride, or atrazine) or non-conservative (e.g., DO or fecal coliform bacteria). The choice of design conditions and periods may include consideration of:

 

### Continuous longer term dynamic conditions (e .g., 20 to 50 years of hydrologic and water quality variability), and

 

### Discrete steady-state extreme conditions (e.g., 7-day 10-year low-flow).

This choice may include one or both of these conditions as appropriate for the parameter(s), watershed(s), and receiving water(s) in question.
As discussed previously in Section 3, long-term datasets for water quality and flow for conservative parameters may allow the calculation of the TMDL based on the water quality standard less the MOS times the long-term flow record divided by the critical time period(s).

6-8Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Also as discussed previously, consideration of changes in land uses and hydraulics and their effects on flows and loads may be factored into this data TMDL assessment (e.g., applicable land use, impervious area, bridge-culvert, and gate operations conditions), since many watersheds have developm ent and hydrologic-hydraulic changes occurring over the monitoring and modeling period which can significantly affect results.
In many cases, changes that result in significant variations in non-conservative parameters may require the application of long term continuous models to evaluate the TMDL by evaluating the pollutant load reduction goal options to determine the threshold at which the standard is met (e.g., reduce BOD by a range of amounts to meet a DO standard). The implicit MOS would be included in these results, and the explicit MOS would be calculated and subtracted from the resultant TMDL. Section 6.5 presents further discussion on MOS. Figure 6.1 shows an example frequency plot for daily load based on a water quality numerical standard (as applicable) and time series results for three model simulations which include the expected model parameters (most applicable dataset from calibration and validation) and both high and low ranges of compound implicit uncertainty simulations in order to define an uncertainty "band" and assist in the definition of MOS. Data and model refinements may also be identified at this point to reduce uncertainty. The TMDL would be calculated based on the load to meet the applicable standard minus the MOS.

Figure 6.1 Example Plot of Water Quality Standard, Monitored Data, and Model Results 

### 0 50 100 150 200 250

0% 20% 40% 60% 80% 100% Percentile Paramete r (lb/day) Water Quality Standard

Monitored Data and Flow

Model Simulation (Expected)

Model Simulation (High Band)

Model Simulation (Low Band)



### 6-9Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### The consideration of residence time and the potential for in-system response(s) may be considered in the time period for the load that is used to calculate the daily load estimate. For example, the TMDL could be a weekly (rive rs), monthly (lakes), seasonal (estuaries), and/or annual (very large systems) issue for the receiving water. The practitioner may consider the various potential time periods of interest and calculate the daily loads for several different time periods to evaluate the uncertainty of the calculation in order to better define and document the MOS.



# 6.4 EVALUATION OF LOAD REDUCTIONS AND ALLOCATIONS

The next step in the TMDL process is the evaluation of the pollutant load reduction required to achieve instream concentrations that meet the water quality standards with a margin of safety. The evaluations described in Section 6.1 reflect two options for scenarios in the study area: no human impacts (totally undeveloped) and existing human impacts. Model results for the two cases could be used as a comparison for the load reduction analysis, although in many cases, the analysis will identify allowable load and/or load reductions to meet the water quality standard.
If significant loads are contributed by both point sources and nonpoint sources, the load reductions need to be allocated between the two source types. The point sources would include domestic and industrial wastewater and NPDES MS4 discharges, and these sources would comprise the WLA as described in Section 1. The nonpoint sources would include flora and fauna, atmospheric, agricultural, and silvicultural discharges along with legacy sediment effects. These sources would comprise the load allocation (LA). Such an allocation may consider the relative contributions of each source type, and the impacted receiving water type. For example, if the receiving wate r is a stream that frequently does not meet DO standards during periods of extreme low-flow conditions, then a reduction of point source loads would likely be more appropriate than reduction of stormwater and/or nonpoint loads which would provide little or no oxygen-demand load under the critical low-flow design conditions. Conversely, it may be inappropriate to allocate load reductions to point sources that are already subject to very high levels of treatment. Comparative cost-benefit analyses could be performed to compare options.
To clarify potential cost-benefit questions about point source controls versus nonpoint source controls, the FDEP Allocation TAC (FDEP, 2001) has recommended that since domestic and industrial wastewater point sources already treat pollutants to a high degree, the first step in reducing loads should be a consideration of the impacts when 45% of nonpoint sources participate in current BMP requirements. The second step would consider 90% participation. If neither of these alternatives reduces loads to below impaired requirements, then load reduction requirements for both point and nonpoint sources may be considered. The practitioner could identify potential BMPs (Section 7) and coverages to model these load reduction scenarios.

6-10Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# 6.5 DETERMINATION OF MARGIN OF SAFETY (MOS) FOR TMDL STUDY
Based on EPA guidelines discussed in Section 5.4, the TMDL for each receiving water is supposed to include an MOS allowance which reflects the uncertainty in the TMDL determination and provides a safety factor for water quality protection. Simply stated, the MOS is the unallocated portion of the TMDL which is derived from the model applications described in Section 6.3. The MOS can be “explicitly” defined in the TMDL as unallocated assimilative capacity. Alternatively, the MOS can be “implicitly” factored into the TMDL through the use of conservative model input parameter values in the TMDL water quality model, as previously discussed in Section 5.
A National Research Council (NRC) evaluation of the scientific basis for the TMDL program found that, out of 172 completed TMDL studies, 70 percent specified an explicit MOS (almost all were based on fairly arbitrary selection of a safety factor), 23 percent relied upon an implicit MOS (none of which documented the degree of protection required), and 7 percent did not specify an MOS at all (Dilks and Freedman, 2004). Based on this review, the NRC TMDL report recommended that the practice of arbitrarily assigning a MOS should end and uncertainty analyses should be used as the basis for MOS determination (NRC, 2001).
Three methods for determining the MOS for a TMDL study are summarized below. 

## 6.5.1 Implicit Method
The implicit method is the simplest approach to addressing the MOS. As discussed in Section 5.4.4.1, it involves selecting TMDL model parameter values and other assumptions (e.g., TMDL flow conditions or loading characteri stics) which are sufficiently conservative to include an appropriate safety factor. Unfortunately, there is insufficient guidance on how the practitioner may select “sufficiently conservative” model input values. Therefore, the magnitude of the implicit MOS is difficult to quantify.

If the implicit method is used for a TMDL study, an approximate MOS may be backcalculated for the TMDL study reporting. For example, the TMDL water quality model could be rerun using less conservative input values which will produce a lower (or higher as appropriate) simulated instream concentration and a greater “allowable load” (Dilks and Freedman, 2004). The difference between the final TMDL simulations and the simulations with less conservative parameter values could then be used to back-calculate an MOS (in units of concentration or mass loadings) from the water quality standard which can be expressed as a percentage of the TMDL. Model sensitivity studies (Section 5.4.4.1) may suffice to define the changes in model output and associated uncertainty using less conservative parameter values. 

## 6.5.2 Intermediate Explicit Method: FOEA
The FOEA analysis described in Section 5.4.4.2 can be incorporated into a quantitative assessment of the MOS for the TMDL study.
This explicit method relates the MOS to the variance calculated for the TMDL model output using the FOEA analysis described in Section 5.4.4.2. The FOEA uncertainty analysis calculates the COV(C) value for the TMDL model output (e.g., instream concentration or daily load). The TMDL model’s COV(C) value is then converted to a standard deviation (SD)

6-11Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### based on the mean concentration ( 

### C ) for the TMDL model simulations (i.e., SD = COV(C) *



### C ). For steady-state TMDL model applications which vary the TMDL load until the instream concentration matches the instream water quality standard (WQS), the SD can be calculated from the WQS (i.e., SD = COV(C) * WQS).
The unallocated fraction (i.e., MOS) of the TMDL would then be based upon the percentage of the TMDL load associated with the selected model variance. Larger values for COV(C) and SD would result in a larger back-calculated MOS, and vice versa. The MOS can be expressed as the SD times a factor (Z) and back-calculated from the mean instream concentration simulated with the TMDL model. The factor “Z” is the SD multiplier from the standard normal distribution table.
Figure 6.2 illustrates this explicit method for back-calculating a probability-based MOS from the TMDL model output of instream concentration. For this example, the steady-state TMDL model simulates an instream concentration equal to the WQS. The instream concentration simulated for the TMDL is then broken down into the unallocated portion ( ∆ C MOS 

### ) and an allocated portion ( ∆ C ALL 

### ). The MOS fraction (in units of mg/L in Figure 6.2) is based upon the SD times the factor Z associated with the selected probability of WQS compliance based on a standard normal distribution.

Figure 6.2 Explicit Method for Back-calculating a MOS

6-12Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 6.1 summarizes the probability of compliance based on a MOS ranging from 1 to 2.33 SDs below (or above) the WQS:

Table 6.1 Probability of Compliance for Various Margins of Safety

TMDL Margin of Safety (Z * SD) Probability of Compliance with Water Quality Standard

1.0 SD 84%

1.3 SD 90%

1.64 SD 95%

2.33 SD 99%

These WQS compliance probabilities are based on a TMDL that is an allocated load (WLA + LA) which produces the mean instream concentration, C ALL 

### , plus an MOS allowance ( ∆ C MOS 

### ) equivalent to 1.0 to 2.33 SDs. For the published TMDL and allocation, the MOS based upon the instream concentration (Figure 6.2) should be converted to a mass load.

After quantifying potential MOS values based upon the FOEA statistics, the practitioner may compare the MOS load for alternate SD factors with the TMDL and the allocated loads (WLA + LA). Recognizing that an excessively large MOS may not be cost-effective, the selection of the MOS should balance factors such as increased compliance costs, required degree of protection, and acceptable risk. MOS factors reported in the general literature are typically equal to or less than 10 percent of the TMDL (Zhang and Yu, 2004).

It may be appropriate to use a MOS ranging from a safety factor of one SD below the WQS (or above the WQS for a minimum WQS limit) up to a percentage of the TMDL ( for a safety factor greater than one SD). For models exhi biting greater than average uncertainty, this percentage could range from 10 percent of the TMDL up to the percentage of model uncertainty about the applicable standard or critical loading causing impairment. Decisions about the need for greater MOS factors (i.e., greater than 10 percent of the TMDL) can be based on future post-audits which will benefit from a larger database on completed TMDL studies.



## 6.5.3 Advanced Explicit Method: Monte Carlo Simulation
The Monte Carlo simulation method described in Section 5.4.4.3 can also be incorporated into a quantitative assessment of the MOS, similar to the FOEA approach described above. As discussed in Section 5, Monte Carlo simulations represent a more complex analysis of TMDL model uncertainty compared to the FO EA method which produces similar results for most applications. Therefore, use of Monte Carlo simulation for MOS evaluations should probably be reserved for selected TMDL applications where a more complex approach is merited.

6-13Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### The determination of potential MOS allowances with Monte Carlo simulations follows the same steps outlined above for the FOEA method. The TMDL model is executed numerous times with a set of randomly sampled parameters developed by the Monte Carlo simulations. The summary statistics (mean, SD, COV) for the numerous TMDL model runs are used to develop the breakdown shown in Figure 6.2 for alternate MOS allowances (based on Z times SD for the assumed probability). The selection of the final MOS should balance compliance costs with degree of protection and risk.

The MOS range suggested above for the FOEA method should also be applicable to the Monte Carlo simulation method: from one SD below (or above) the WQS up to a maximum of 10 percent (for a safety factor greater than one SD).

6-14Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# SECTION 6 REFERENCES

CDM. 2001. Big Creek Water Resource Management Plan. Fulton County, GA.

Dilks, D.W. and Freedman, P.L. 2004. “Improved Consideration of the Margin of Safety in Total Maximum Daily Load Development.” ASCE Journal of Environmental Engineering. 130(6), pp. 690-694.

James, W. and M.K. Thompson. 1997. Contaminants from Four New Pervious and Impervious Pavements in a Parking Lot. Advances in Modeling the Management of Stormwater Impacts - Volume 5, CHI Publishers.

National Research Council. 2001. “Assessing the TMDL Approach to Water Quality Management.” Washington, D.C.

Pitt, R. 1998. Epidemiology and Stormwater Management . In Stormwater Quality Management. CRC/Lewis Publishers, New York, NY.

Rutledge, A.T. 1998. Computer programs for describing the recession of ground-water discharge and for estimating mean ground-water recharge and discharge from streamflow records—Update. USGS Water-Resources Investigations Report 98–4148. U.S. Geological Survey.

Schueler, T.R. 1999. Microbes and Urban Watersheds, II. Concentrations, Sources, and Pathways. Watershed Protection Techniques, 3(1): page 554.

Schueler, T.R. 1999. Microbes and Urban Watersheds, IV. Implications for Watershed Managers. Watershed Protection Techniques. 3(1): page 581.

USEPA. 1983. Results of the Nationwide Urban Runoff Program. Volume 1 - Final Report, Washington D.C.

Zhang, H.X. and Yu, S.L. 2004. “Applying the First-Order Error Analysis in Determining the Margin of Safety for Total Maximum Daily Load Computations.” ASCE Journal of Environmental Engineering, 130(6), pp. 664-673.

  

6-15Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



# Section 7 TREATMENT ALTERNATIVES AND BEST MANAGEMENT PRACTICES

Notes:

1. Preparation, verification, calibration, and validation (PVCV) Yes



### 7-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### This section describes treatment alternatives and best management practices (BMPs) that can be used to manage and reduce existing and future point and nonpoint source discharges to address the requirements of the TMDL process. BMPs are considered in the evaluation of existing loads (Element II), in the control of loads from new development (Element III), and in the evaluation of retrof it facilities to reduce loads and meet PLRGs (Element III). This section provides informati on regarding typical BMP treatment efficiencies and design parameters based on mass removal (load reduction) to be used for existing sources in the absence of sufficient monitoring data. Local BMP monitoring data should be used whenever possible. Concurrently with this Protocol, FDEP is developing a BMP Database.
The following discussion of sources and associated BMPs is divided into regulated point sources (Section 7.1) and nonpoint sources that are not regulated by a permit (Section 7.2)



# 7.1 REGULATED POINT SOURCES

As noted in the previous chapter, the regulated point sources in Florida consist of domestic wastewater, industrial wastewater, munici pal separate storm sewer systems (MS4s), industrial NPDES stormwater discharges, and construction site runoff. Not all of these sources discharge the types or amounts of pollutants that may cause impairments, so the discussion below addresses the major pollutants discharged by systems using standard treatment technologies. More specific data on pollutant mass removal and reductions of pollutant concentrations should be obtained from discharge monitoring reports, if available.



## 7.1.1 Domestic Wastewater
There are three basic ways domestic wastewater is treated in Florida: by onsite sewage treatment and disposal (i.e., septic tanks); by package plants; or by centralized wastewater treatment facilities. Roughly 2.3 million septic tanks in Florida treat approximately 0.4 billion gallons per day of domestic wastewater. Most of these facilities are privately owned and operated. The rest of the domestic wastewater, about 1.7 billion gallons per day (bgd) with a permitted flow of 2.3 bgd, is treated by approximately 2,700 centralized and package plant wastewater treatment facilities (WWTFs). Most of these are owned and operated by municipal agencies. According to FDEP, 90 percent of this daily volume is treated by WWTFs that have capacities of greater than 0.5 million gallons per day (mgd). About half of the facilities discharge their treated wastewater to surface waters, and the other half discharge to groundwater ( Figure 7.1 ). Therefore, for inland waters (e.g., lakes, rivers, streams), there are approximately 800 surface water Effluent Disposal in Florida

Surface Water

31%

Ocean Outfall

22% Deep Well Injection

24% Ponds, RIBs and Land Application

23%



### Figure 7.1 Effluent Disposal in Florida

7-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### WWTF discharges that must be considered in TMDL processes. Each of these facilities is required to provide quantitative discharge reports documenting discharge flow and quality. These discharge reports are generally the principle source of information regarding pollutant loads from point sources. WWTF discharge re cords representing existing flows and quality are generally appropriate to use when assessing actual existing conditions. However, the TMDL analysis should consider the WWTF’s maximum discharge capacity and permitted quality for alternatives analyses and for the process of distributing the total load among point, nonpoint, and background sources.



## 7.1.2 Industrial Wastewater
Although the State of Florida is not heavily indus trialized, there are industrial wastewater discharges to surface waters that can, and have, caused significant environmental concern. Industrial discharges range from the pulp and paper mills in northern Florida, to the phosphate mines in central Florida and the power plants and smaller facilities throughout the state. FDEP requires each industrial discharge to obtain a permit that explicitly prescribes conditions for allowable discharges of treated effluent, including monitoring and documentation of discharge flow and quality. It should be noted that discharge records document existing flows and quality for existing conditions. However, TMDL analyses should be based on each permitted facility’s maximum discharge capacity and permitted quality. A sensitivity analysis could be performed during t he TMDL analyses to determine the impact on critical parameter concentrations and loads from the permitted and actual WWTF flow rates and loads.



## 7.1.3 BMPs for Use in Municipal Separate Storm Sewer Systems (MS4s)
Municipal stormwater programs typically empl oy structural and nonstructural controls to manage flooding, erosion, and water quality degradation due to increased runoff and associated pollutants. As a class, methods to control stormwater runoff are called Best Management Practices, or BMPs. BMPs include techniques, approaches, devices, and constructed facilities that control runoff velocities, volumes, peak discharge rates, and/or pollutant loads. BMPs can be categorized as follows:

 

### Source controls reduce runoff and pollutant generation at or near the source.

 

### Treatment controls are constructed or manufactured facilities that control or reduce runoff and load at a downstream point.
BMPs can also be categorized as:

 

### Structural – constructed facilities such as detention ponds

 

### Non-structural – policies, programs, or ordinances

This section provides several information sheets on many of the more common BMPs that have been used in Florida and elsewhere in the United States. The intent of this section is to describe BMPs that are applicable to urban environments in Florida, providing information on benefits and limitations of their application.

7-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### The application of a specific BMP depends on site-specific conditions and objectives, such as water quality protection, flood control, aquifer recharge, and/or volume control. In many cases, there are multiple goals or needs for a given project. Therefore, BMPs can be "mixed and matched" to develop a "treatment train" (Florida Development Manual - FDER, 1988). The treatment train concept maximizes the use of available site conditions from the point of runoff generation to the receiving water discharge in order to maximize benefits associated with water quantity (flood control and stream channel protection), water quality (pollutant load reduction), aquifer recharge, and wetlands protection and enhancement. Figure 7.2 is an example schematic flowchart of the treatment train concept.

Figure 7.2 Treatment Train Concept



### Online versus Offline An important factor that can affect BMP effectiveness is whether the BMP is “online” or offline. An “online” BMP is configured so that all of the stormwater runoff is routed through the facility (i.e., no bypass). An “offline” BMP is typically configured such that a control structure diverts a design volume to the facility but not all runoff from larger storms is treated. Capture and treatment of smaller, coll oidal particles such as silts and clays may require offline facilities to avoid resuspension and flushing from large volume storm events. Whenever possible, pretreatment or offline treatment facilities should be considered and may be required (e.g., for OFW, Class I and Class II waters). Refer to local WMD and City/County requirements for offline treatment.

Reuse Stormwater reuse provides benefits of pollutant load and runoff volume reduction while reducing potable demand for irrigation. Reuse should be considered whenever possible (ref. Stormwater Management, M.P. Wanielista and Y.A. Yousef, 1993).

7-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### BMP Information Sheets The BMP Information Sheets provided in this section provide basic information on the benefits and limitations of a broad variety of BMPs that are in fairly common use, including applicable ranges of expected pollutant mass removal efficiencies. Table 7-1 is a list of the information sheets provided in this section for urban BMPs.

Table 7-1 Urban BMPs

Wet Detention Ponds

Dry Detention Basins

Exfiltration Trenches

Retention Basins and Swales

Conveyance Swales

Buffers and Filter Strips

Baffle Boxes

Alum Treatment

Hydrodynamic Separators

Pervious Pavement

Stormwater Wetlands and STAs



### 7-5Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Wet Detention Ponds – Information Sheet Detention refers to the temporary storage of excess runoff onsite prior to gradual release after the peak of the storm inflow has passed. Runoff is held for a period of time and is slowly released to a natural or manmade watercourse, usually at a rate no greater than the pre-development peak discharge rate (and often for multiple design storms). A wet detention system includes a permanent pool of water, a shallow littoral zone with aquatic plants, and the capacity to provide detention for an extended time necessary for the treatment of a required volume of runoff. Pollutant removal occurs by solids settling, algal and vegetative uptake, and adsorption primarily within a permanent pool during the period of time between storm events. They are typically sized to provide at least a 2-week residence time during the wet season.

Potential Benefits

 Reduction of downstream flooding problems by attenuating the peak rate of flow

 Reduction in pollutant loadings to receivi ng waters for dissolved and suspended pollutants

 Can be used in areas with high water tables and less permeable soils

 Low frequency of failure if properly maintained

 Reduction in cost for down stream conveyance facilities

 Creation of local wildlife habitat

 Possible higher property values as an aesthetic annuity for adjacent lots

 Creation of fill that can be used on site or sold

 Can be used for irrigation sources (reuse)

Potential Limitations

 Potential safety hazards if not designed & constr ucted properly (gradual sideslopes are desirable)

 Occasional nuisance problems such as odors, algae, debris, and mosquitoes

 Regular maintenance of the littoral zone required to prevent nuisance plant species

 Eventual need for sediment removal from the permanent pool or sediment forebay

Design Considerations

 Provide a live pool (volume and depth of 1.0 to 2.5 inches - refer to local WMD and FDEP guidelines)

 Storage recovery of first 1/2 inch of runoff is generally required in no less than 24 hours

 Provide a permanent pool with forebay (volume an d depth with hydraulic residence time of 14 to 21 days - refer to local WMD guidance)

 Prevent short circuiting with minimum 3:1 length:width ratio or use of baffles

 Maximum depth as per local WMD or fountains or aeration (depth > 12 ft.)

 Control structure above the average groundwater elevation

 Sideslopes (3H:1V or milder) with 6:1 littoral zone as per WMD and FDEP guidelines

 Skimmer for oil and trash at the outlet

 Open waters or wetlands Typical Mass Removal Efficiencies

BOD5 20%-40% COD 20%-40% TSS 80%-90% TDS 20%-40% Total-P 40%-60% Dissolved-P 30%-50% TKN 20%-30% NO2+NO3 30%-40% Lead 70%-80% Copper 60%-70% Zinc 40%-50% Cadmium 70%-80% Α



### 7-6Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Dry Detention Basins – Information Sheet

Dry detention ponds are primarily a flood prevention BMP which slows the stormw ater such that the allowable peak discharge rate is met. Dry detenti on has been used widely in the area served by the SFWMD. Additionally, the SJRWMD allows a modified form of dry detention for some small projects. Any treatment within a dry detention system is via infiltration or sedimentation.

Potential Benefits

 Reduction of downstream flooding problems by attenuating the peak rate of flow

 Limited removal of pollutant loadings to rece iving bodies of water for suspended pollutants

 Reduction in cost for down stream convey ance facilities

 Creation of local wildlife habitat

 Creation of fill that can be used on site or sold

 Low frequency of failure if properly maintained

Potential Limitations

 Very limited dissolved pollu tant removal (nutrients)

 Potential safety hazards if not designed and constructed properly

 No permanent pool to store sediment inflow

 Occasional nuisance problems such as debris and mosquitoes

 Regular maintenance required to prevent nuisance plant species and to remove accumulated sediments

 Must be off-line to be effective
Design Considerations

 Tributary areas: Generally, the dry pond is considered for areas smaller than 10 acres

 Pond volume and water quantity control requirements

 Runoff is directed to the pond and detained for 24 to 48 hours before discharge to downstream

 The first 0.5 to 1.0 in of runoff is ty pically detained for treatment and attenuation

 Detention time: The minimum detention time of 24 to 48 hours should be targeted

 Sideslopes (3H:1V or milder)

Typical Mass Removal Efficiencies

BOD5 20%-30% COD 20%-30% TSS 20%-80% TDS 0%-10% Total-P 10%-30% Dissolved-P 0%-10% TKN 10%-20% NO2+NO3 0%-10% Lead 30%-50% Copper 20%-40% Zinc 20%-40% Cadmium 20%-40%

Α



### 7-7Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Exfiltration Trenches – Information Sheet

An exfiltration trench is the onsite retention of stormwater accomplished through underground exfiltration. The trench should always be designed off-line to minimize clogging and failure. The subsurface retention facilities most commonly us ed are excavated trenches with perforated pipe backfilled with coarse graded aggregate. Exfiltration tr enches are used to retain the "first flush" of stormwater runoff. This promotes pollutant load reductions to rece iving waters, re duces the runoff volume and peak discharge rate from a site, filters suspended pollutants out of groundwater discharges, and promotes the recharge of groundwat er. Exfiltration trenches are practical in highly permeable soils (Hydrologic Group A or B) where t he subsoil is sufficiently permeable to provide a reasonable rate of infiltration, and where the water table is sufficiently lower than the design depth of the facility to allow for recovery of the storage prior to the next storm event (generally required in 72 hours).

Potential Benefits

 They mimic the natural groundwater recharge capabilities of the site

 Relatively easy to fit into the margins, perimeters, and other space constrained areas

 Can provide offline treatment fo r environmentally sensitive waters (e.g., Class I, Class II, or OFW)

 Can be used to retrofit already developed sites where space is limited

Potential Limitations

 Require highly permeable soils to function properly

 Difficulties in keeping sediment out of the structure during site construction

 Not recommended for clayey or highly erodible soils

 Have relative short life spans before replacem ent or extensive restor ation/maintenance is required

 Often more costly than other treatment alter natives, especially when O&M costs are considered
Design Considerations

 Tributary areas: Generally, exfiltration is considered for areas smaller than 10 acres

 Exfiltration volume of 0.5 to 1.0 inch ov er the tributary area (see local WMD guidelines)

 Groundwater table should be at least 2 to 4 feet below the bottom of the trench in the wet season (minimum 1.0 inch/hour using a safety factor of 2)

 Drain time should be no less than 24 hours and not greater than 72 hours

 Trench should be at least 100 ft from any drinking water supply

 Trench should be at least 10 ft downgradient and 100 ft upgradient from building foundations

 Trench is not feasible on sites with a slope greater than 20 percent
Typical Mass Removal Efficiencies

BOD5 80%-95% COD 80%-95% TSS 80%-95% TDS 80%-95% Total-P 80%-95% Dissolved-P 80%-95% TKN 80%-95% NO2+NO3 80%-95% Lead 80%-95% Copper 80%-95% Zinc 80%-95% Cadmium 80%-95%



### 7-8Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Conveyance Swales – Information Sheet

Shallow grassed swales are constructed shallow trenches shaped or gradually graded to required dimensions and established in suitable vegetation fo r the safe conveyance, storage, and treatment of runoff. Swales are normally used for conveyance systems to tr ansport runoff offsite or to a stormwater facility. They also may be used as pretre atment in the overall treatment train stormwater system. They are best suited at sites with soils of moderate-to-high infiltration capacity (usually Hydrologic Groups A or B). With slight modification (e.g., check dams, raised in lets, or swale blocks), swales can be used to add retentio n storage, control erosion, provide aquifer recharge, and/or reduce the pollutant load from concentrated stormwater runoff in urban areas and provide landscape amenities.

Potential Benefits

 Usually less expensive than installing curb and gutters

 Hardly noticeable if shallow swales (0.5 to 1.0 ft max depth) have gradual side slopes (4:1 to 6:1)

 Reduction in cost for downstream conv eyance facilities

 Can provide treatment for envir onmentally sensitive waters (e .g. Class I, Class II, or OFW)

 Can reduce peak rates of discharge by st oring, detaining, or attenuating flows

 Can be used in space constrained areas such as along lot lines, rear of lots, and along roadside

Potential Limitations

 Effective only as a conveyanc e system in unsuitable soils

 Possible nuisances such as odors, mosquitoes , or nuisance plant species can occur if not designed, constructed, or maintained properly

 Aesthetically unpleasing if impr operly designed and constructed

 May not be suitable or may require geotextile matti ng in areas that serve as vehicle parking areas

Design Considerations

 Typically designed to convey the runo ff from the 3-year, 1- hour storm

 Recovery time should not be greater than 72 hours

 Swale depth ranges from 0.5 to 2 ft. max with gradual side slopes (4:1 to 6:1)

 Swale slope should range from 2 percent to 6 percent to achieve average flow velocity of <0.5 ft/s

 Swale invert shall be at least 1-2 feet above the seasonal high water table

 Swales shall be grassed

Typical Mass Removal Efficiencies (Conveyance Swales)

BOD5 20%-40% COD 20%-40% TSS 70%-90% TDS 10%-20% Total-P 30%-50% Dissolved-P 10%-30% TKN 20%-40% NO2+NO3 10%-30% Lead 60%-90% Copper 40%-60% Zinc 40%-50% Cadmium 50%-80% Α

1. For retention swales, use retention efficiencies



### 7-9Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Retention Basins and Swales – Information Sheet A retention basin or swale is an infiltration system designed to retain stormwat er onsite, thus reducing pollution, recharging groundwater, and controlling flood waters. Typically, these basins have dry bottoms covered with native grasses. The site characteristics where retention basins function best are where soils are highly permeable and the seasonal hi gh water table is situated well below the soil surface (at least 2 to 3 feet below pond bottom). Infiltration controls are best suited for onsite applications (off-line from the primary stormwater management system) where the contributing area is limited to a single development site or subdivision (e.g ., 1 to 50 acres). To be most effective, retention controls must be an integral part of the initial design and construction of a site.

Potential Benefits

 Mimics the natural water balance of a site by promoting groundwater recharge

 Can provide offline or on-line infiltration treatment for environmentally s ensitive waters (Class I, Class II, or OFW)

 Online systems can reduce peak rate and volume of flood discharge by retaining water onsite

 Creation of fill that can be used on site or sold

 Reasonably cost-effective in comparison with other BMPs for both construction and maintenance
costs

Potential Limitations

 Require well-drained soils to function properly

 Soluble pollutants can be conveyed into groundwater

 Possible nuisances such as odors, mosquitoes , or nuisance plant species can occur if not designed, constructed, or maintained properly Design Considerations

 Pond volume and water quantity control requirements (first 0.5 to 1.0 in of runoff is typically detained for treatment and attenuation)

 Retention time: The maximum retention time of 72 hours

 Sideslopes (3H:1V or milder)

 Swales with check dams or raised outlets

Typical Mass Removal Efficiencies

BOD5 80%-95% COD 80%-95% TSS 80%-95% TDS 80%-95%
Total-P 80%-95%
Dissolved-P 80%-95%
TKN 80%-95% NO2+NO3 80%-95%
Lead 80%-95% Copper 80%-95%
Zinc 80%-95% Cadmium 80%-95% Α



### 7-10Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Buffers or Filter Strips – Information Sheet

Buffer strips or filter strips, consisting of gras s or other close-growing vegetation, are designed to accept overland flows of runoff. They are usually composed of dense vegetation such as high grasses, ground covers, or shrubs. Buffers can be combined with underlying stone layers to enhance infiltration. Buffers can be effective in slowi ng stormwater runoff rates and velocities, reducing downstream sediment loading by settling and physical entrapment. They can increase infiltration of stormwater and can provide some nutrient removal through uptake of plants. Buffer strips with berms or weirs are efficient for controlling roadway runoff discharges to sensitive surface waters.

Buffer strips are typically located between pollutant source areas and a downstream receiving water body. They also can be used as outlet or pretreatme nt devices for other stormwater control BMPs. A buffer strip is not a complete stormwater management system.

Potential Benefits

 Reduces sediment loading and pollutants associated with sediment load to receiving waterbody

 Contributes to groundwater recharge

 Prevents soil erosion

Potential Limitations

 Require routine maintenance (weed and pest control, mowing, fertilizing and irrigation) to ensure reliability and effectiveness

 Not considered a complete stormwater managemen t system – should be used as a component in the BMP treatment train.

 These systems are very vulnerable to large stor ms because the high-velocity flows can erode the vegetated cover
Design Considerations

 Buffer widths should increase as slope increase s and are typically a minimum of 15 feet wide for grassed buffer strips and a minimum of 35 to 50 feet wide for stream buffers

 Design should include a level spreader along the top edge of the buffer strip to prevent erosion channel formation

Typical Mass Removal Efficiencies

BOD5 0%-80% COD 0%-80% TSS 20%-80% TDS No Data Total-P 0%-60% Dissolved-P No Data TKN No Data NO2+NO3 0%-60% Lead 20%-80% Copper 20%-80% Zinc 20%-80% Cadmium 20%-80% Source: Modified from Metropolitan Government of Nashville and Davidson County, 2000. Stormwater

______ Management Manual.

S ource: SFWMD, 2002. Best Management Practices for South Florida Urban Stormwater Management Systems



### 7-11Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Baffle Boxes – Information Sheet Baffle boxes are BMP devices that are mainly used at the end of pipes in order to provide additional treatment of runoff. The original baffle box is sim ilar to a three chambered septic tank and is designed to treat sediment, TSS, large debris and oil and grease. The effectiveness of these devices at removing the individual pollutant depends upon the type of device used, the residence time, and whether the device is online or offline. Baffle boxes , when used in conjunction with pretreatment measures such as street sweeping, may be the most feasible water quality control device in areas where the other more traditional measures discuss ed previously may not be applicable due to various constraints.

Potential Benefits

 Provide primary treatment at outfalls where no other option exists

 Require very little space

 Baffle boxes are a modification of the existing st ormwater system, and therefore are typically less expensive as compared to other treatment methodologies

 Can have significant treatment benefits when offline

Potential Limitations

 Primarily most effective at removing suspe nded solids, although second generation models remove nutrients

 Require maintenance at least quarterly

 Do not achieve removal of most dissolved solids
Design Considerations

 Should be used based on settling velocities for expected particle sizes and flow rates for 80% capture on an annual basis

 Must incorporate easy vac uum truck accessibility (mul tiple manholes-cleanouts)

 Flow through velocity should be less than the se ttling velocity of the target material to ensure proper removal

 Offline systems are superior to online systems for removal

 Concrete box culverts can be used by bolting in aluminum or stainless steel weirs in series

Typical Mass Removal Efficiencies

BOD5 0%-50%
COD No data
TSS 70%-90%
TDS No data

Total-P 20%-40%

Dissolved-P 0%-20%

TKN 0%-10%
NO2+NO3 0%-20%
Lead 60%-80% Copper 40%-60%

Zinc 20%-40%
Cadmium 50%-70%

Α Exit pipe Sediment Chamber III Chamber II

Baffles

Chamber I Inlet pipe Access manholes for pumping out sediments



### 7-12Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Alum Treatment – Information Sheet
Aluminum sulfate, Al 2 (SO 4 ) 3 , commonly called alum, has been used extensively as a flocculating agent in the treatment of wastewater for over 100 years. The addition of alum to water results in the production of chemical precipitates which remove pollutants by two primary mechanisms. Removal of suspended solids, algae, phosphorus, heavy metals and bacteria occurs primarily by enmeshment and adsorption onto aluminum hydroxide precipit ate according to the following net reaction:

Al +3 + 6H 2 O → Al(OH) 3(s) + 3H 3 O + (1)

Removal of additional dissolved phosphorus occurs as a result of direct formation of AlPO 4 by:

Al +3 + HnPO 4 n-3 → AlPO 4(s) + nH + (2)

The aluminum hydroxide precipitate, Al(OH) 3 , is a gelatinous floc which attracts and adsorbs colloidal particles onto the growing floc, thus clarifying the water. Phosphorus removal or entrapment can occur by several mechanisms, depending on the solution pH. Inorganic phosphorus is also effectively removed by adsorption to the Al(OH) 3 floc. Removal of particulate phosphorus is most effective in the pH range of 6-8 where maximum floc occurs (Cooke and Kennedy, 1981).

Potential Benefits

 Provides very high levels of stormwat er pollutant removal except for nitrogen

 Requires very little space

 Construction costs for alum stormwater treat ment systems are largely independent of the watershed area to be treated and depend primarily upon the number of outfalls to be retrofitted

 Alum treatment of stormwater runoff is often substantially less expensive than other stormwater treatment retrofitting alternatives with respect to both initial capital construction costs and annual O&M costs.

Potential Limitations

 Require routine maintenance and trained maintenance staff

 Do not achieve high removal of some dissolved pollutants (especially nitrogen)

 Can create free aluminum ion which is potentially toxic

 Do not provide any flood c ontrol benefits (unless in association with wet pond)

 Creates sludge that should be removed regularly
Design Considerations

 Must maintain pH between 6.0 and 8.0 to minimize potential for aluminum toxicity

 Floc (sludge) must be captured and dispos ed of properly. Conical chambers can be used to collect sludge and it can be sent to wastewater treatment plant.

 Jar tests must be done to determine proper dosage of alum (typically 5 to 15 mg/l)

 Lightning protection for the controls and dosage equipment is recommended
Typical Mass Removal Efficiencies

BOD5 45% - 65% Total N 40% - 70%
COD 45% - 65% NO2+NO3 10% - 40%
TSS 80% - 99% Lead 60% - 95%
TDS 50% - 90% Copper 40% - 75%

Total-P 45% - 95% Zinc 40% - 75%

Dissolved-P 20% - 90% Cadmium 40% - 75%



### 7-13Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Hydrodynamic Separators – Information Sheet Hydrodynamic separators are flow -through structures with a settling or separation unit to remove sediments. The energy of the flowing water allows the sediments to efficiently separate so no outside power source is required. Depending on the type of unit, this separation may be by means of swirl action or indirect filtration.

Potential Benefits

 Provide primary treatment at outfalls where no other option exists

 Require very little space

 Typically a modification of the existing stormwater system, and therefore are typically less expensive as compared to other treatment methodologies

 Can have significant treatment benefits when offline

Potential Limitations

 Primarily most effective at removing suspended solids

 May export nutrients due to anaerobic conditions within them

 Require maintenance at least quarterly

 Do not achieve removal of most dissolved solids
Design Considerations

 Must incorporate easy vac uum truck accessibility (mul tiple manholes-cleanouts)

 Offline systems are superior to online systems for removal

Typical Mass Removal Efficiencies

BOD5 0%-20%
COD 0%
TSS 70%-90%
TDS 0%

Total-P 25%-45%

Dissolved-P 0%-20%

TKN 0%-10%
NO2+NO3 0%-20%

Lead 60%-85% Copper 40%-60%

Zinc 25%-45%
Cadmium 50%-70%

Source: Fenner and Tyack, 1997. OVERFLOW

CENTER

CONE

SOLIDS C HOPPER OLLECTION

O UNDERFLOW

UTLET PIPE SEPARATOR BODY INLET PIPE DIP PLATE CENTRAL SHAFT



### 7-14Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Pervious Pavement – Information Sheet
A pervious pavement generally consists of a laye r of porous or pervious concrete overlying an underground reservoir filled with stone aggregates. It is mainly designed to treat rainfall that falls on the pavement. After stormwater runoff infiltrates th rough the pavement, it is collected in reservoirs where it infiltrates into the subsoil. Pervious pave ment is typically used in the construction of parking lots as a built-in stormwater treatment device. The design of a pervious pavement can be modified to enable the system to accept runoff from surrounding areas and rooftops. This modification includes the installation of perforated inflow pipes to distribute the runoff throughout t he stone reservoir. In addition, a pr etreatment system is needed to remove trash, sediment, oil, and grease to prevent them from clogging the reservoir.

Potential Benefits

 Reduces effective impervious area

 Provides groundwater recharge

 Less need for curbing and storm sewers

Potential Limitations

 Need contractors certified in pervious concrete use

 Subject to clogging from sediments and therefore requires routine maintenance

 Not suitable for areas with high water tables

 Potential for introducing pollutants to groundwater
Design Considerations

 Pervious material mixture can be adjusted to achieve desired infiltration rate

 Traffic volume must be considered – not appropriate for high traffic volume

 Groundwater table should be at least 4 feet below the surface

 Installation should be avoided near drinking water supply
Typical Mass Removal Efficiencies

BOD5 No data COD 60%-90% TSS 60%-100% TDS No data Total-P 40%-90% Dissolved-P No data TKN 80%-95% NO2+NO3 40%-90% Lead 60%-90% Copper No data Zinc 60%-90% Cadmium No data

Source: Modified from Metropolitan Washington Council of Governments, 1987. Controlling Urban Runoff: A Practical Manual for Planning and Designing Urban BMPs. Undisturbed Soils with a Field Capacity > 0.27

Inches/Hour Preferably > 0.50 Inches/Hour Gravel Course or 6-Inch Sand

La y e r Pervious Pavement

Stone Reservoir Drains in 48-72 Hours Perforated Pipe Discharges Only When 2-Year Storage Volume Exceeded

Filter Fabric Lines Sides of Reservoir to Prevent Sediment Entry Overflow

Pi p e Berm Keeps Off-Site Runoff and Sediment Out, Provides Temporary Storage POSTED Sign Posted to Prevent Resurfacing and Use of Abrasives, and to Restrict Truck Parking Vacuum Swept, Followed by Jet Hosing to Keep Pores Open

References: 1. U.S. EPA, 1999. Stormwater Technology Fact Sheet – Porous Pavement 2. Wade, D., Janicki, A., Pribble, R. 1997. Watershed Management Model for Optimal Allocation of BMPs User’s Guide and

--

Case Study. Tampa Bay National Estuary Program Technical Publication No. 07-96.



### 7-15Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Stormwater Wetlands and STAs – Information Sheet Wetlands improve the quality of stormwater runoff, and ca n also control runoff rate and volume. They are one of the more reliable BMPs for removing pollutants and are adaptable to most locations where the hydrology supports wetlands. Wetlands remove pollutants from stormwater through physical, chemical, and biological processes. Chemical and physical assimilation mechanisms include sedimentation, adsorption, filtration, and volatiliz ation. In general, wetlands remove pollutants about as effectively as conventional pond systems and wetl ands can provide higher levels of treatment for nutrients, such as the stormwater treatment areas (S TAs) in South Florida which use combinations of emergent, submergent, and perip hyton systems to treat ur ban and agricultural runoff.

Wetlands used for stormwater treatment can be in cidental, natural, or constructed. Incidental wetlands are those that were created as a result of previous development or human activity. The use of natural wetlands for stormwater treatment is prohibited except as allowed by Florida statute and regulations.

Potential Benefits

 Opportunity to incorporate natural sy stems for water stormwater treatment

 Protection of downstream receiving waters

 Can provide wetland creation, restoration, or enhancement

 Can provide wildlife and waterfowl habitat if prio rity pollutants are below levels that would cause adverse impacts to the biota (e.g., very low co ncentrations, treating for TSS only, hydrologic regulation, and/or large wetland to tributary area ratio

 Can be used in areas with high water table and/or low permeable soils

Potential Limitations

 Area requirements may be significant

 May have limited application in urban setting due to available land limitations.

 Potential for short-circuiting, which can lead to poor performance

 Pre-treatment is required if natural wetlands are incorporated into the stormwater system

 May be a wildlife and waterfowl attractant, theref ore caution should be considered if priority pollutants are in the inflow to be treated

 Constructed wetlands, by themselves , do not provide flood control benefits
Design Considerations

 The BMP treatment train is essential to provide pretreatment

 Specific design and pretreatment requirements for wetland stormwater treatment systems are set forth in DEP stormwater rules and WMD environmental resource permitting rules Typical Mass Removal Efficiencies

Source: Modified from Metropolitan Washington Council of Governments, 1992. Design of Stormwater Wetland Systems

. Max storm elevation

normal water table Max storm elevation

Seasonal high water table D. Pocket Wetland C. Pond/Wetland System

wetland

pond normal pool elevation micropool normal pool elevation B. Extended Detention (ED) micropool forebay normal pool elevation A. Shallow Marsh BOD5 40%-60% COD 40%-60% TSS 60%-80% TDS No Data Total-P 20%-60% Dissolved-P No Data TKN No Data NO2+NO3 20%-40% Lead 30%-80% Copper 20%-60% Zinc 20%-60% Cadmium 20%-60%

Source: SFWMD, 2002. Best Management Practices for South Florida Urban Stormwater Management Systems

References:1. U.S. EPA, 1999. Stormwater Technology Fact Sheet – Storm Water Wetlands



### 7-16Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## 7.1.4 Nonstructural BMPs to Reduce Urban Stormwater Pollution
Land Use Planning
Land use planning and management presents an important opportunity to reduce and/or minimize pollutants in stormwater runoff and control flooding. A comprehensive planning process can be used to integrate municipal stormwater management (i.e. flood control and water quality improvement) goals into the development and redevelopment process. Management measures may include modification or restrictions of certain land use activities, control over the placement of certain land uses, and control over drainage patterns within the land area. Greater restrictions may be warranted where development can affect impaired, threatened, or significant water bodies. Increases in impervious cover from urban development typically result in increased pollutant loadings and flooding, land use planning practices than consider water quality impacts can be an effective control measure.
Public Information Program
Public information (PI) and participation programs can inform employees, the public, and businesses about the importance of protecting stormwater from improperly used, stored, and discarded pollutants. Many people do not realize that yard debris or trash thrown into ditches can worsen flooding and pollute surface waters. PI programs may be directed to training municipal employees, especially those that work in departments not directly related to stormwater but whose actions affect stormwater. PI programs can also increase public awareness about a variety of hazardous products used in the home whose improper use and disposal can pollute stormwater. Examples include improper disposal of oils, antifreeze, paints, and solvents that can end up in stre ams and lakes, poisoning fish and wildlife. Increased public awareness also facilitates public scrutiny of industrial and municipal activities and will likely increase public reporting of incidents. PI programs can help inform businesses, particularly smaller ones that may not be regulated by Federal, State, or local regulations, about ways to reduce their potential to pollute stormwater.
Examples of public information programs:
Florida Clean Marina Program
FDEP has designed the Florida Clean Marina program to introduce citizens to simple, innovative BMPs for boatyards. Other partici pating organizations include the University of Florida Sea Grant, Marine Industries Association (MIA) of Florida (including numerous local chapters), International Marine Institute, Marine Resource Council, Florida Marine Trades Association, Marina Operators Association of America, Marina Owner/Operators and Consultants. Guiding FDEP’s actions are the principles of ecosystem management, foremost of which is that all things are connected. Ecosystem management takes a holistic approach to environmental protection, where air, water, land and living things are all considered together, not in isolation.
The Clean Marina program applies to boatyards that repair and convert recreational and small commercial vessels for Florida’s waterways. U.S. shipyards are categorized as either first-tier or second-tier. This program addresses the second-tier that includes many small and medium-size businesses that construct and repair vessels smaller than 122 meters (383 feet).

7-17Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### The Clean Marina Program promotes hurricane preparations, petroleum control, boat cleaning, solid waste management, hazardous waste management, fish waste management and sewage management BMPs to prevent or reduce pollutant discharge.
Florida Yards and Neighborhoods Program
The Florida Yards & Neighborhoods Program were developed to address serious problems of pollution and disappearing habitats by enlisting citizens efforts and activities to save the natural environment. The program provides s pecial educational and outreach activities directed at the community to help residents reduce pollution and enhance their environment by improving home and landscape management.
Florida Green Industries BMP Program
The Florida Green Industries program has published a 60 page BMP manual developed jointly by the Florida Green Industries, FDEP, FDACS, DCA, water management districts, and the University of Florida (June 2002). The m anual provides information and guidance on turfgrass and landscape management practices for the purpose of conserving and protecting Florida’s water resources. Practices cover establishment of new turf and landscapes and the care of existing turf and landscapes, including construction activities, irrigation, nutrient management, and pest management.
Adopt a Pond Program
The Adopt a Pond Program is an educational program developed and implemented by Hillsborough County to improve proper operation and maintenance of stormwater systems. The restoration or rehabilitation of stormwater ponds can have a positive impact on water quality in the downstream health of our lakes, creeks, rivers and bays. The program requires all stormwater ponds to have a landscape design. This design is critical to the success of the pond. Aquatic vegetation used to stabilize a pond and to remove pollutants is a vital link that helps maintain water quality. Other amenities that a properly designed pond may have are increased wildlife habitat, recreation areas, and aesthetic vistas.
Stormwater Management Ordinance Requirements
In general, municipal stormwater management ordinance establish guidelines for the safe management and discharge of stormwater ru noff from developed areas. Ordinances are applicable to all new development, generally excluding single family dwellings, and require that all applications for building permits must contain a stormwater management plan. Such ordinances are necessary for the control of new development (to control future runoff) and significant redevelopment (to retrofit older developments to new standards).
Fertilizer Application Control
Fertilizer application control is a voluntary control mechanism by citizens who use fertilizer as part of their landscaping activities. Fertilizer application controls are implemented through a public information program by making the public aware of the principles of environmental landscape maintenance and the problems associated with overuse of fertilizers. Overuse of fertilizers can contribute to excessive runoff of nutrients to surface waters thereby wasting money for the homeowner and potentially degradi ng the receiving water body. Information programs should also be extended to professional fertilizer users.

7-18Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Pesticide Use Control
Pesticide use control is also a voluntary control by citizens who use pesticides as part of their housekeeping and lawn maintenance activities. Some pesticides include priority pollutants (e.g., Endrin, Lindane, and Silvex), which can be toxic. Overuse of these chemicals can cause excessive runoff to surface waters and entry into the food chain. Many professional applicators of pesticides are using approved pesticides in a safe and proper manner. An information program on pesticide use will help to reduce the amount of pesticides entering the stormwater system. In addition, two model landscaping ordinances are available on the DEP web site that can be incorporated into local land development regulations. These are Guidelines for Model Ordinance Language for Protection of Water Quality and Quantity Using Florida Friendly Lawns and Landscapes and Sample Florida Yards and Neighborhoods Ordinance

. Cisterns and Rainbarrels
Cisterns are underground storage tanks used to manage water from the rooftops and impervious drainage areas. On-lot storage and possible reuse of collected stormwater saves potable water and thus may reduce water utility costs. Cisterns are applicable to residential, commercial, and industrial low-impact development sites. Larger cisterns are needed at commercial and industrial sites due to the size of rooftops and the amount of impervious tributary area. Individual cisterns can be located beneath each downspout, or storage volume can be provided in one common cistern. Cisterns need be located where they are easily accessible for maintenance.
Rain barrels are low-cost, effective, and easily maintainable retention devices practical in both residential and commercial/industrial site applications. Rain barrels first retain a predetermined volume of rooftop runoff and then an overflow pipe provides some detention beyond the retention capacity of the rain barrel. Like cisterns, rain barrels can also store runoff for reuse in irrigation. To be aesthetically acceptable, rain barrels can be incorporated into the lot’s landscaping plans or patio or decking designs. Gutters and downspouts are used to convey water from rooftops to rain barrels. Filtration screens should be used ton gutters to prevent clogging of debris. Rain barrels should be designed so that complete draining of the system is possible. Rain barrels should also be equipped with a drain that has garden hose threading, suitable for connection to a drip irrigation system. An overflow adapter could be used to connect two or more barrels to divert surplus water away from foundations. An overflow outlet must be provid ed to bypass runoff from large storm events. Rain barrels must be designed with removable, child-resistant covers and mosquito screening on water entry holes. The size of the rain barrel will depend on the rooftop surface area that drains to the barrel and the amount of rainfall desired for retention storage.
Solid Waste Management
In some instances, problems can arise from trash and other debris flowing into, and obstructing, open channels, and culverts, and storm sewers. The public can be informed of the adverse impacts of littering and poor solid waste management. This can also include pet droppings and illegal dumping into storm drains, wooded areas, and ditches. Pet droppings can be a source of coliform bacteria and pathogens.

7-19Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Hazardous Material Management
A BMP promoting efficient and safe housekeeping practices including storage, use, and cleanup when handling potentially harmful materials and the use of less harmful and safe alternative products may be implemented to reduce discharge of pollutants to storm water. In some cases, safer alternative products exist for such household items as fertilizers, pesticides, cleaning solutions, paint products, automotive products, and swimming pool chemicals. Municipal employees working with potentially harmful materials should be trained in good housekeeping practices and use of safer alternative products.
Implementation of this BMP will also involve coordination of public education efforts focusing on the benefits of good housekeeping practices and use of safer alternative products. The cost for this BMP is very minimal. P ubic awareness will promote a willingness to try alternatives and to modify old behaviors. One limitation for this BMP may be that alternative products may not always be available, suitable, or effective in every case.
The discharge of pollutants to storm water from material delivery and storage can be reduced and prevented by storing materials inside or under cover on paved surfaces, minimizing storage and handling of hazardous materials on-site, utilizing secondary containment, conducting regular inspections, and training employees and subcontractors. The key to this BMP is to design and maintain material storage areas that reduce exposure to storm water. Accurate and up-to-date inventories need to be kept of all stored materials. A supply of spill cleanup materials needs to be kept near the storage area and the employees need to be well trained in proper material storage. Storage sheds are also required to meet building and fire code specifications.
Spill prevention should be part of a comprehensive BMP program to prevent runoff contamination. An important tool in preventing spills is a Spill Prevention Plan. A Spill Prevention Plan specifies materials handli ng procedures and storage requirements and identifies spill cleanup procedures for areas and processes in which spills may potentially occur. The plan standardizes process-operating procedures and employee training in an effort to minimize accidental pollutant releases that could contaminate stormwater runoff.
A Spill Prevention Plan is applicable to facilities that transport, transfer, and/or store hazardous materials, petroleum products, or fertilizers that can contaminate stormwater runoff. Most businesses and public agencies that generate hazardous water and/or produce transport, or store petroleum products are required by State and federal law to prepare spill control and cleanup plans. Existing plans should be reevaluated and revised to address stormwater management issues.
Street Sweeping
Street sweeping can be an effective method of improving street aesthetics in developed areas and, depending on the type of equipment used, can be an effective pretreatment method of water quality control. Special equipment vacuum or sweep debris and sediment accumulated from streets in urban environments. Curbs and gutters are required for street sweeping and it is common for such streets to be swept many times during the year. Sediment and debris are collected within the equipment and must be properly disposed. Recent developments in vacuum sweepers show increased removal efficiencies for smaller particles.

7-20Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### A recent study compared several different vacuum sweepers and indicated that TSS washoff reduction can range from a 20 percent reduction up to a 50 percent reduction, depending on the type of street sweeper used, for monthly street sweepings (Sutherland et al. 1997). In addition, the Sutherland study indicated that with increased street sweeping frequency, even higher reductions could potentia lly be achieved, ranging upwards to nearly 80 percent for the most efficient models for weekly street sweepings.

Vehicle Use Reduction
A BMP to reduce the discharge of pollutants to storm water from vehicles also exists. The amount of pollutant discharge to storm water may be greatly reduced by highlighting the storm water impacts, promoting the benefits of alternative transportation on storm water, and integrating initiatives with existing or emerging regulations and programs. Integration of this BMP practice with other efforts by governm ental agencies and businesses to reduce vehicle use and improve air quality can greatly enhance this BMP’s applicability, effectiveness and efficiency by avoiding possible redundant and/or conflicting programs. Establishing trip reduction programs at major employers can be a great staring point. Support efforts to pass reasonable regulations at the State and local level aimed at reducing vehicle use and developing transit-oriented communities is very critical in achieving the full potential benefits of this BMP. Also the public needs to understand that air pollution means water pollution and a public education program focusing on the water quality benefits of reduced vehicle use needs to be employed. Public participation in ride sharing programs can highly affect the success of this BMP.
There can be two possible limitations. Level of cooperation and integration between departments and programs may be challenging and the use of alternative transportation is highly dependent on its convenience and relative cost.
Directly Connected Impervious Area (DCIA) Minimization
Another nonstructural BMP option is to mi nimize the amount of directly connected impervious area (DCIA) on a site and to promote the use of green buffer zones around paved areas for infiltration. For example, roof runoff from structures can be directed to green buffer zones or shallow landscaped swales around houses. In addition, parking lots and driveways can be graded to landscaped/grassed areas or swales, reducing direct runoff to the storm drainage system. Also, commercial parking areas can be reduced by allowing parking lots to be sized for average use, not high attendance times (e.g., Christmas). Extra parking for such special occasions can be accommodated using pervious parking or other less permeable parking spaces.
Low Impact Development
Low impact development emphasizes a BMP tr eatment train and reduced land clearing in an environmentally sensitive design. Applying t he principles together, planners, developers, and local officials can measurably reduce impe rvious cover, conserve natural areas, and reduce the impacts of stormwater from new development while at the same time enhancing both the natural environment and community well being. The photograph below shows a house and landscaped lot that were designed to capture approximately 98 percent capture of annual rainfall volume with zero discharge in a coastal Florida application. Listed below are some examples of low impact development ideas:

7-21Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

 

### Clearing and grading of forested and native vegetation at a site should be limited to the minimum amount needed to build lots.

 

### Conserve trees and other vegetation at each site by planning additional vegetation, clustering tree areas, and promoting the use of native plants.

 

### Residential streets designed for the minimum required pavement width needed to support travel lanes, on-street parking, and emergency vehicle access.

 

### Reduction of residential street lengths by examining alternative street layouts.

 

### Minimization of the number of street culde-sacs and incorporate landscape areas to reduce their impervious cover.

 

### Where density, topography, soils and slope permit, vegetated open channels should be used in the street right-of-way to convey and treat runoff.

 

### Reduce excessive parking, minimize stall dimensions, encourage shared parking, and use pervious materials in spillover parking areas where possible.

 

### Provide stormwater treatment for parking lot runoff using bioretention areas, filter strips, and/or other practices that can be integrated into required landscaping areas and traffic islands.

 

### Advocate open space design development and str eam buffers incorporating smaller lot sizes to minimize total impervious area, conserve natural areas, provide community recreational space, and promote watershed protection.

 

### Relaxation of setbacks to reduce overall lot imperviousness.

 

### Consider locating sidewalks on only one side of the street and providing common walkways linking pedestrian areas.

 

### Promote alternative driveway surfaces and shared driveways to reduce overall lot imperviousness.

 

### Direct rooftop runoff to pervious areas.

 

### Green roof technologies

7-22Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Illicit Connections (Non-Stormwater Discharges) Identification and Removal
In the 1987 Clean Water Act Amendments, three major goals were identified: to control pollution from municipal stormwater systems to the maximum extent practicable (MEP), to eliminate "illicit" discharges to storm sewers and to control the discharge of stormwater from industrial activities. These goals have generated the National Pollution Discharge Elimination System (NPDES) permitting program s for municipal storm sewer discharges to waters of the United States (see Subsection 2.5). For the second goal, "illicit" discharges are defined as those that are non-stormwater discharges to the storm sewer. Examples include laundromat wastewater, car washing water, restaurant wastes, etc. To achieve this goal, EPA has been encouraging municipalities to search for illicit connections and eliminate such discharges. The ongoing EPA NPDES illicit connection survey should be used to strengthen applicable codes and eliminate these connections which can cause plugs of toxic substances to enter surface waters. Aggressive inspection is a key component of this BMP program. Emphasis on cooperation and public outreach is also a critical to the effort to eliminate illicit discharges.

Erosion and Sediment Control on Construction Sites
Erosion and sediment control on construction sites provides for the protection of receiving waters from sediment loads. Proper erosion prevention and sediment flow controls during construction are listed below:

 

### Minimize clearing and grading using site planning, open space, buffer zones, and other protections.

 

### Constant retention and/or detention systems in first phase.

 

### Protect waterways and stabilize drainage ways.

 

### Phase construction to reduce soil exposure.

 

### Immediately cover, revegetate, and stabilize exposed soils with mulch or other means.

 

### Install controls to filter sediments, gravel filter weirs, including sediment fences keyed into land surface, temporary berms, swales, exit controls, and inlet filters at the perimeter of the site and, on larger sites, throughout the site.

 

### Employ advanced sediment settling contro ls, such as well-designed and maintained basins.

The state of Florida has recently created a sediment and erosion control training process that provides education on proper sediment and erosion management of construction sites. Certification is also provided.

Source Controls on Construction Sites
Source control on construction sites can be accomplished with proper construction practices to prevent or reduce the discharge of pollutants from dewatering operations, paving operations and structure construction and painting. Contractor and employee training should be integrated with existing training programs to encourage appropriate material

7-23Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### management, waste management and vehicle and equipment management to also prevent or reduce the discharge of pollutants. Dewatering flows should be filtered through a gravel filter weir or equivalent (FDOT washed stone of 1-inch diameter wrapped in filter fabric).
Operation and Maintenance (O&M)
A recent survey by FDEP has reported that nearly 70 percent of existing stormwater treatment facilities in Florida are not properly maintained, and therefore likely do not provide the intended pollutant removal effectiveness. Because of this, one of the most effective nonstructural BMPs is routine maintenance of existing treatment facilities. For publicly owned stormwater treatment facilities, routine maintenance and inspection should be performed. For privately owned stormwater fa cilities, a municipality does not typically perform maintenance. There are several options that can be pursued by a municipality to help ensure that proper maintenance is being conducted. These options include a certification program initiated by a municipal ity that requires all approved subdivision ponds (private) to be recertified by the owner on a predetermined time interval. A state certified/trained inspector or engineer may complete the recertification. Enforcement of maintenance of privately owned facilities is one of the most difficult problems for privately owned facilities. Potential enforcement meas ures may include governmental intervention (after sufficient notification) where the government completes critical maintenance and the cost of the maintenance is billed to the owner or by other means as deemed necessary by the municipality. Another option would be to consider the assessment of fines.
Maintenance can be provided on a routine basis or as needed based upon inspection. Manygovernments provide a mixture of routine maintenance for critical facilities and inspectionbased maintenance for less critical facilities. The following paragraphs highlight some important maintenance considerations for BMPs.
Mowing
The side slopes, embankments, emergency spillways, and other grassed areas of stormwater facilities must be periodically mowed to prohibit woody growth and control weeds. More frequent mowing may be required in residential areas by adjacent homeowners. Mowing usually constitutes the largest routine maintenance expense. The use of native or introduced grasses that are water-tolerant, pest-tolerant, and slow growing are recommended.

Debris and Litter Removal
Debris and litter accumulate near stormwater facility control structures and should be removed during regular mowing operations. Particular attention should be paid to floatable debris that can eventually clog the control structure or riser. Trash screens or racks can be strategically placed near inflow or outflow points to capture debris.

Erosion Control
Side slopes, emergency spillways, and embankm ents all may periodically suffer from slumping and erosion. This should not occur often if the soils are properly compacted and vegetated during construction. Regrading and revegetation may be required to correct any problems that develop.

7-24Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Nuisance Control
Standing water or soggy conditions within a stormwater facility can create nuisance conditions for nearby residents. Odors, mosquitoes, weeds, and litter can all be potential problems in stormwater facilities. However, wetland plants established in wet detention ponds can harbor birds and predacious insects and fish that serve as a natural check on mosquitoes, and regular maintenance to remove debris and ensure control structure functionality will help control these potential problems.
Structural Repairs and Replacement
Eventually, the facility control structure will deteriorate and must be replaced. For ponds, these should be inspected at least once annually. In the case of exfiltration trenches and porous pavement, when the trench or pavement becomes clogged, part or all of the facility may need replacement.



# 7.2 SOURCES NOT REGULATED BY NPDES

While the sources discussed in Section 7.1 are regulated by NPDES and generally have sufficient discharge information, this subsection considers other potentially significant pollutant sources that are not regulated by NPDES permits and may not have discharge data. These sources can be categorized as septic tanks, agricultural sources and distributed

sources.


## 7.2.1 Septic Tanks
As discussed in Section 3, roughly 2.3 million septic tanks in Florida treat approximately 0.4 billion gallons per day of domestic wastewater, serving approximately 30 percent of Florida’s population. In areas with correct soils, sufficient distance from groundwater influences and where they are properly spaced and maintained, septic tanks can function well. However as noted previously, between 5 and 15 percent of such onsite facilities present a pollutant source to nearby surface waters when improperly placed, designed, constructed, or maintained (EPA, 1986). Section 3 recommends that a value of 10 percent should be used for septic tank failures in areas with proximal surface waters. In cases where septic tank failures represent a significant pollutant source, there are only two treatment technologies available to remediate the source: repair or re placement of the septic tank system, or the connection of the homes with septic tanks to a local or regional wastewater treatment facility.



## 7.2.2 Agricultural Sources
Information related to agricultural sources is presented in Subsection 3.4.3. To date, FDACS and FDEP have produced a number of BMP manual s for specific agricultural programs including Citrus, Cow-Calf Programs, Agrichemical Handling, and Blended Fertilizer Plants. The BMP documents generally describe methods to control irrigation, fertilization (for nutrient load reduction as appropriate) and other land management practices to reduce pollutant loading. Included at the end of this section are a series of Information Sheets for some of the standard agricultural BMPs to aid in the understanding of the pollution loading potential. Table 7-2 presents a list of agricultural BMPs.

7-25Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Table 7-2 Agricultural BMPs
Agricultural BMPs Included in This Document:
Irrigation Management Conservation Tillage
- No-till/Strip Till

- Mulch Till
- Ridge Till

- Terraces

Conservation Buffer
- Filter Strips
- Strip Cropping Contour
- Riparian Forest Buffer Contour Farming

Water and Sediment Control Basin
Animal Waste Management

Other BMPs for Consideration Include:

Nutrient BMPs Soil Testing and Plant Analysis
Correct Timing and Placement of Fertilizer

Use of Slow Release Fertilizer

Pesticide BMPs

Correct Pesticide Selection
Correct Pesticide Application
Correct Container Disposal
Biologic Control
Selection of Resistant Crop Varieties
Water Management BMPs

Use of Plastic Mulches
Water Table Management
Use of Water Tolerant Crops

Animal Waste BMPs
Fencing Planned (rotational) grazing
Provide Water/Feeder Locations away from natural water bodies
Providing Shade sources away from natural water bodies

Sediment BMPs

Diversion and Terraces



### 7-26Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Irrigation Management for Agricultural Operations – Information Sheet Proper irrigation scheduling/management will help to as sure efficient use of water and energy in crop production. Irrigation scheduling methods that ar e currently applicable in Florida are 1) a water budget method requiring estimation of daily ET and soil water content, and 2) the use of soil moisture measurement instrumentation. When properly used and combined with efficient methods of water application, irrigation management should also result in increased production and profits. (Smajstrla et al.)



### Potential Benefits

 If applied properly can increase produc tivity and reduce irrigation expenses

 Efficient irrigation can reduce farm discharges and thus reduce pollutant loading

 Irrigation management systems can al so include a fertilization component



### Potential Limitations

 May require significant upfront capital investment

 Depending on the type of system implement ed, the grower may have to implement more thorough recording keeping practices and increased levels of maintenance


### Design Considerations

 System designs must include a thorough analysis of the total costs including operating and maintenance costs. Typically, a hi gher initial capital investment can pay for itself in the long-term by reducing maintenance costs and achi eving improved system performance.

 System design requires an underst anding of many factors, includi ng: crop water needs, soils, climate, irrigation method(s), management objec tives, and regulatory constraints (FDACS 2004)

 If coupled with a fertilization component, Flor ida law requires proper backflow prevention



### Targeted Parameters

Sediment and Nutrients

Source: Tim McCabe USDA 2004 Ima g e Number: 85cs0114 CD0890-100

References: 1. A.G. Smajstrla, B.J. Boman, D.Z. Haman, F.T. Izuno, D.J. Pitts and F.S. Zazueta 1997. Basic Irrigation Scheduling in Florida Bulletin No. 249. Institute of Food and Agricult ural Sciences, Univer sity of Florida. 2. FDACS (Florida Department of Agriculture and Consumer Services) 2004. Water Quality/Quantity Best Management Practices for Florida Ve g etable and A g ronomic Cro p s



### 7-27Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Conservation Tillage: No-till/Str ip Till - Information Sheet

In conservation tillage, previous crop residue is conserved by using only the minimum tillage necessary to control pests and su ccessfully plant the next crop. Conservation tillage, other than notill, is not well suited to low residue crops like cotton since not enough surface residue will remain for erosion control. No-till is planting crops in a pr evious crop’s residue or cover crop with no surface tillage, except a slot to put the seed in the ground.

Potential Benefits

 Residue keeps soil from blowing or washing away. In favorable conditions, conservation tillage can reduce erosion by as much as 90 percent.

 Residue helps to promote increased water infiltration, slows evap oration, and can reduce the need for irrigation.

 Reduced runoff and increased infiltration keep sediment and other pollutants from reaching the River.

 Crop residue contains valuable nutrients that can make the soil more fertile.

 Crop yields may increase because topsoil and nutrients are not washed away.

 Conservation tillage practices can save time and money because they involve less labor, less fuel, and fewer pieces of equipment.

Potential Limitations Properly timed and accurate herbicide application is critical. There are still a few weeds that cannot be controlled economically in no-till systems. Conservation tillage is mu ch less effective than no-till in reducing erosion. (No-till is often considered to be a type of conservation tillage, but conservation tillage usually means more soil disturbance).

Design Considerations A minimum of 30 percent of the soil surface should be left covered by crop residue after planting, which helps control erosion.

Targeted Parameters TSS and nutrients

Typical Mass Removal Efficiencies United States Environmental Protection A gency, Report EPA-840-B -92-002, January 1993. http://nonpoint.deq.state.la.us/manage7.html

References http://economics.ag.utk.e du/extension/bcstudy/Ro w%20Crops.p65linked2.pdf



### 7-28Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Conservation Tillage: Mulch Till - Information Sheet

Mulch-till systems manage crop residue on the soil surface year round, while growing crops where the entire soil surface is tilled prior to or duri ng the planting operation. Residue is partially incorporated using chisels, sweeps , field cultivators, or similar farming implements. Mulch-till is defined as leaving 30 percent crop residue cover after planting.

Potential Benefits The beneficial effects of mulching are attributed to:

 Physical effects that minimize raindrop impac t, improve rainfall acceptance through enhancement of soil structure and reduce runoff and erosion;

 Biological effects that increase the activity and species diversity of soil flora and fauna, notably earthworms increased biomass carbon, and improved crop growth; and

 Chemical effects that alter nutrient status and influence crop growth.

Potential Limitations Heavy residue can pose a problem for the implements during seedbed preparation, Numerous operations are becoming increasingly expens ive in terms of fuel and equipment costs, and Seeding difficulties due to straw residue.

Design Considerations Not available.

Targeted Parameters Runoff, sediment, pesticide residue

Typical Mass Removal Efficiencies United States Environmental Protection A gency, Report EPA-840-B -92-002, January 1993. http://nonpoint.deq.state.la.us/manage7.html

References http://www.epa.gov/watertrain/pdf/Agriculture.pdf



### 7-29Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Conservation Tillage: Ridge Till - Information Sheet

Ridge till is a system in which seeds are planted in to a seedbed that is prepared by scraping off the top of a ridge. The scraped-off ridge usually provid es an excellent environment for planting. Ridges are formed during cultivation of the previous year's crop.

Potential Benefits

 On poorly drained soil, seeds are planted in a warmer, better-drained seedbed than with most other tillage systems.

 Ridge till can greatly reduce erosion when compared to conventional tillage, especially when ridges are on the
contour.

 Fuel, equipment, and labor costs are all less wi th ridge till when compared to conventional tillage.

 Ridge till often allows earlier planting than conventional tillage, especially on poorly drained soils.

 Ridge till may not present as many weed-control problems as no-till. Weed seeds on the soil surface, including volunteer corn kernels, are pushed to the middle of the rows where they can be destroyed by cultivation. Example of Ridge Till 1

Potential Limitations The combine used on ridge-till fields may need to have its wheel spacings ad justed. It is important that the combine wheels be spaced to operate between rows. That way, the wheels will not compact the ridges formed during cultivation for the next y ear's crop. Research has shown a significant yield decrease in rows driven upon by a combine. A sprea der or chopper is also desirable to distribute the residue more uniformly across the field. Residue left in the windrows may hamper subsequent operations.

Design Considerations Research shows that a ridge till system is best suited to medium-to-heavy textured soils with gentle slopes and a continuous corn or co rn-soybean cropping system. Because corn and soybeans predominate in the state,and many of the agricultural soils in Illinois are mediumto-heavy and gently sloping, ridge till is a viable system in Illinois. Perhaps it should be used much more throughout the state.

Targeted Parameters TSS, nutrients and pesticides Ridge Tillage in Operation

Typical Mass Removal Efficiencies United States Environmental Protection A gency, Report EPA-840-B -92-002, January 1993. http://nonpoint.deq.state.la.us/manage7.html

References

1 http://web.aces.uiuc.edu/vi sta/pdf_pubs/RIDGING.PDF



### 7-30Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Conservation Tillage: Terraces with Surface or Underground Outlets - Information Sheet

Terraces are long, low earthen embankments construc ted across a slope, as nearly as practical on the contour. They intercept runoff water and guide it off the field safely. Terraces are best used to control concentrated flow and prevent gullies wh en no-till, conservation tillage and grassed waterways will not work without them.

Potential Benefits

 Terraces help reduce gullying in fields, reducing wear and tear on machinery.

 By reducing erosion, terraces help maintain t he yield potential and long-term value of land.

 By slowing water flow, more water is absorbed into the soil and is available during dry periods.

Example of a Terrace Potential Limitations

 Generally more expensive than no-till.

 Make machinery operation more difficult.

 Not suited to fields with irregular, short slopes.

 Usually require annual maintenance. When not maintained, they can increase gully erosion problems.

Design Considerations

 Terraces must have stable outlets like grassed waterways or underground pipes to carry water off the field.

 Terraces should not be used on slopes of more than 8 percent.

Targeted Parameters

 TSS, nutrients, and pesticides

Typical Mass Removal Efficiencies

 Terraces can reduce the soil loss by 50 percent or more.

References http://ianrpubs.unl.edu/soil/g750.htm#terplan http://economics.ag.utk.e du/extension/bcstudy/Ro w%20Crops.p65linked2.pdf



### 7-31Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Conservation Buffer: Filter Strips for Agricultural Operations - Information Sheet Filter Strips are used to remove sediment, organic matter, and other pollutants from runoff or wastewater by deposition, infilt ration, and sorption, thereby reducing pollution, improving water quality, and protecting the environment (NRCS 1999).

Potential Benefits

 Can be applied to a variety of agricultural practi ces including row crops, cattle/calf operations, forestry etc.

 Protection of downstream receiving waters

Potential Limitations

 Potential for short-circuiting if rills or sm all channels are formed wi thin the filter strip

 May be a wildlife attractant, therefore caution should be considered when conducting weed control, mowing and other maintenance activities Design Considerations

 Width of filter strip should vary based on land slope; land slopes of less than 5 percent typically require filter strip widths from 5 feet to 35 feet. NRCS recommends a 3-foot increase in filter strip width per 1 percent increase in land slope over 5 percent.

 Care shall be taken to ensure runoff flows perp endicularly across the filter in a uniform manner.

 If implemented near concentrated livestock areas for lounging which are normally void of vegetation during the winter months , the filter strip width should be at least 100 feet wide between the lounging area and water bodies.

 May require fencing to prevent access by farm animals

 Existing native vegetation sh ould be used when appropriate.

Targeted Parameters

Sediment, Nutrients, and Organic Matter

Source: EPA 2004. Section 319 Success Stories, Vol. III . Stillwater River Watershed Protection Project

References: 1. National Resources Conservation Service (NRCS) 1999. Conservation Practice Standard No. 393 – Filter Strip



### 7-32Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Conservation Buffer: Contour Strip Cropping - Information Sheet Contour strip cropping divides a steep land into contour strips that cut across the path of overland flow and retard its velocity. Contour strip cropping is an alternation of contour buffer strips with contour cropped strips. Low-growing soil conserving crops (e.g. cowpea, soybeans, Stylosanthes, Pueraria) are grown in alternate strips with open- row soil-degrading crops (e.g. maize, rice). A soilconserving crop is grown in a contour strip down slop e of the erosion promoting crop to absorb runoff, retard runoff velocity, and encourage sedimentation of entrained sediment. Various categories of strip cropping include the following: Contour Strip Cro pping, Buffer Strip Cropping, Field Strip Cropping, Barrier Strips, and Border Strips.

Potential Benefits

 Strip cropping is generally effective on gent le slopes (< 7%) on rolling terrain.

 For steep slopes, strip cropping should be reinforced with engineering structures.

Potential Limitations

 Herbicide drift from one crop to another can be a problem.

 Because every crop in the rotation is in every field, this practice can increase the amount of machinery time spent moving from field to field compared to rotating whole fields. This may increase costs significantly in operations with scattered fields.

Design Considerations

 Contour strip cropping works best on fields with long, uniform slopes. If the fields have slopes that
are short and/or not uniform (complex slopes), the two problems with using this practice are complex row patterns and more turning of machinery. Example of Contour Strip Cropping in the Midwest

Design Criteria (Source: NRCS Strip Width Guidelines)  On irregular, complex slopes, strips can be planted across the general slope instead of on the contour. This practice, called field strip cropping, is less effective in erosion control. % Slope Strip Width

1–2% 150 ft

3–5% 135 ft

6–8% 120 ft

9–15% 105 ft

16–20% 90 ft

≥ 21% 60 ft Targeted Parameters TSS, Nutrients and Pesticides

Typical Mass Removal Efficiencies

United States Environmental Protec tion Agency, Report EPA-840-B-92- 002, January 1993.

References http://www.unu.edu/unupress/unupbooks/uu27s e/uu27se09.htm#1.%20mulch%20farming
http://economics.ag.utk.e du/extension/bcstudy/Ro w%20Crops.p65linked2.pdf



### 7-33Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Conservation Buffer: Riparian Forest Buffer - Information Sheet Riparian forest buffer is a particular type of conservation buffer. There are approximately 10 conservation practices commonly thought of as bu ffers: alley cropping, contour buffer strips, field borders, filter strips (or riparian grass buffer), grassed waterways with filters, herbaceous wind barriers, riparian forest buffers, v egetative barriers, and windbreaks/she lterbelts. Unlike filter strips, riparian forest buffers are woody areas (trees and shrubs) maintained in permanent vegetation between the edge of fields and streams, lake, rivers or tidal waters.

Potential Benefits

 They help filter nutrients, sediments, and other pollutant from runoff, as well as remove nutrients from groundwater. They also offer food and shelter for wildlife.

 Buffers can vary widely in their vegetation and location on the landscape in order to enhance specific ecological functions that achieve conditions landowners and other stakeholders want.

 The ecological functions of buffers include creating stable and productive soils, providing cleaner water, enhancing wildlife populations, protecting crops and livestock, enhancing aesthetics and recreation opportuniti es, and creating sustainable landscapes.

Potential Limitations

 Reduction of acreage available for crops.
Design Considerations (1)

Buffer Goal Buffer Width (feet) Water Temperature Moderation 75 – 100
Sediment Removal 40 – 200

Nutrient Removal 25 – 300 Diversity 10 – 350

Targeted Parameters Nitrogen, Phosphorous, Sediment, Pesticides, Herbicides
Typical Mass Removal Efficiencies (2) Nitrogen: 17-58% Phosphorous: 50-78%

Sediment: 50-75%

References (1) http://www.epa.gov/watertrain/pdf/Agriculture.pdf (2) http://dnrweb.dnr.state.md.us/wate rsheds/surf/bmp/info/ripariangrass.html



### 7-34Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Contour Farming - Information Sheet The simplest approach to erosion control is contour farming (e.g., performing all farm operations on the contour rather than up and down the slope or parallel to field boundaries). Important farm operations to control soil erosion include plowing, ridging, sowing, fertilizer application, and inter-row cultivation.

Potential Benefits On fields with long, smooth slopes, contour farming can be one of the least expensive ways to reduce erosion.

Potential Limitations The major drawbacks of contour farming are frequent turning involving extra labor and machinery time, and loss of some area that may have to be put out of production.

Design Considerations

 Contour farming is most effective on slopes between 2 and 10 percent.

 This practice will be less effective in achieving the stated purpose(s) on slopes exceeding 10 percent and in areas with 10-year frequency, single storm energy intensity (EI) values greater than 140. (EI = total storm energy times the maximum 30 minute intensity). Practice of Contour Farming

 The practice is not well suited to rolling topography having a high degree of slope irregularity because of the difficulty meeting row grade criteria.

 A contour farming layout shall not occur on a hill slope that is longer than the critical slope l ength, unless supported by other practices (e.g., terraces, diversions) that either reduce slope length below the critical lengt h or reduce overland flow velocities.

Targeted Parameters TSS, Nutrients and Pesticides

Typical Mass Removal Efficiencies The effectiveness of contour farming decreases with increase in slope gradient and slope length, and increasing intensity of rains. If the rainfall exceeds the surface detention capa city of the contouring system, concentrated runoff flowing downstream unchecked can lead to accelerated erosion and even severe gulling. Therefor e, contour farming alone is not sufficient to control erosion on steep, long slopes, er odible soils, and during erosive rains. % Slope Strip Width

1–2% 150 ft

3–5% 135 ft

6–8% 120 ft

9–15% 105 ft

16–20% 90 ft

≥ 21% 60 ft Design Criteria (Source: NRCS Strip Width Guidelines)

United States Environmental Protection A gency, Report EPA-840-B -92-002, January 1993.

References http://lubbock.tamu.edu/irrigate/documents/ 2074410-L5205.pdf http://efotg.nrcs.usda.gov/refer ences/public/SD/330final.pdf http://www.unu.edu/unupress/unupbooks/uu27s e/uu27se09.htm#1.%20mulch%20farming http://economics.ag.utk.e du/extension/bcstudy/Ro w%20Crops.p65linked2.pdf



### 7-35Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Water and Sediment Control Basins - Information Sheet Water and sediment control basins are erosion cont rol structures commonly installed to prevent bank and gully erosion on farmland. These structures control erosion due to concentrated water flows and are not effective in combating sheet erosion. This erosion control structure may also be referred to as a "channel terrace" or a "floodwater storage for a smaller watershed”. A water and sediment control basin in a conservation system can achieve the same objective as a grassed waterway. This structur e is comprised of an earthen berm, constructed across a low draw in a field, and built to a height to pond the runoff water from the upstream watershed for the maximum expected storm which may occur once every 10
years.

Potential Benefits

 The peak runoff flows from a watershed are buffered reducing their erosive capab ility downstream. Sediment settles out of the runoff water in the storage pond decreasing pollution and silting problems in watercourses below.

 Outlet flows from the storage pond are small in co mparison to a system with no storage available, resulting in smaller diameter, lower cost outlet pipes.

 Potential plugging of the pond tile inlet system is minimized, as compared to a tile/catch basin system with no storage, since debris has ti me to settle out before reaching the inlet pipe.

Potential Limitations

 Flooding of the land in the ponding area will occur for a period up to 24 hours after the runoff event. A higher risk is associated with this stru cture because of the poss ibility of berm washout or water overtopping the berm causing problem further down in the watershed.

 There is an inconvenience factor associated with working around the berms with farm equipment. Berms (especially narrow-based) are vulnerable to rodent damage which could result in failure.

 A water and sediment control basin system requ ires a thorough design by a qualified person before being constructed.

Design Considerations

 Before a water and sediment control system can be designed, a field survey should be undertaken to determine the topographical features which will affect the berm locations and ponding volumes available. Soil types, watershed de sign features and outlet availability should also be investigated.

 Having established the berm locations in the fiel d the following factors should be considered in the design of the structure.

 The peak flow and total volume of runoff water for the watershed is to be determined.

Targeted Parameters TSS, nutrients, and pesticides

Typical Mass Removal Efficiencies

 United States Environmental Protection A gency, Report EPA-840-B -92-002, January 1993.

 See also retention, dry detention, and wet detention urban BMP information sheets.

References http://www.gov.on.ca/OMAFRA/engl ish/engineer/facts/89-167.htm Sediment Control Basin



### 7-36Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003

Animal Waste Management - Information Sheet Animal waste management is a generic term that encompasses waste management from different farm animal as diverse as swine, dairy/beef cattl e, chicken, and turkey production. Depending upon the producer's choice, it can be included into an irrigation management plan as well as a nutrient conservation plan for maximum fertilization or nutrient reduction plan for ease of management. For large and small livestock operations, storage lagoons are the common animal waste management. They are designed and operated either anaerobically or aerobically. Anaerobic lagoons are preferred over aerobic lagoons because they are cheaper to operate and they offer a better pretreatment for concentrated organic waste. However, in aerobic lagoons, bacterial degradation is more complete with relatively odor-free end products.

Potential benefits

 Storage and disposal flexibility

 Less land for total treatment system

 Liquid recycling for pit waste removal

 Land application by simple irrigation

 Lower labor needs and operating costs

Potential Limitations

 Appreciable loss of nutrient value

 Offensive odor if improperly designed and managed

 Frequent sludge removal if undersized

 Groundwater protection consideration

 High mechanical aeration cost if used

Design Considerations Liquid volume rather than surface area is the basis for anaerobic lagoon design.

Anaerobic lagoon

 Accumulation rate design criteria in table 2 for each livestock

 Storage for a 25-year, 24-hour rainfall and an additi onal foot of freeboard to prevent embarkment and a 180-day storage capacity

 Any shape but without any deep bays and pockets

 For rectangular shape, the length to width ration should not exceed 4:1

 Side slope varies from 1:1 in clay soils to 3:1 in sandy soils

 Minimum liquid depth of 6 feet at all times (Maxim um up to 20 feet to minimize surface area and encourage dissolution of gases)

Aerobic lagoon

 Liquid depth ranges from 3 to 5 feet and daily load of 50 pounds of BOD5 per acre of lagoon surface

Targeted Parameters Nutrient, BOD and TSS

Typical Mass Removal Efficiencies Reduction of nutrient for land application up to 85%.

References http://www.bae.ncsu.edu/programs/extension/publicat/wqwm/ebae185 93.html http://www.bae.ncsu.edu/programs/extension/publicat/wqwm/ebae103 83.html



### 7-37Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## 7.2.3 Distributed Sources
As noted above and in Subsection 3.4.3, distributed sources include atmospheric deposition through wet and dry fall, groundwater sources, and sediment/legacy sources. While each of these sources can be quantified to some degree through water and/or pollutant balance calculations, reduction of the pollutant load from distributed sources is complicated and sometimes not possible. For example, in the Tampa Bay National Estuary Program (NEP) atmospheric deposition can range from 8 percent of the total nitrogen loading in Hillsborough Bay to 83 percent of the total nitrogen loading in Lower Tampa Bay, for an overall nitrogen loading of potentially 29 percent (TBNEP, Dec 1996). However, researchers have not agreed on how much of the locally generated nitrogen is deposited in Tampa Bay and how much of the nitrogen generated outside of the Tampa area is locally deposited. Nitrogen is also generated by mobile sources (e.g., automobiles), so that treatment of atmospheric nitrogen appears to need a “shotgun” approach – treat everything in a hope that the major source will be affected.
Treatment for groundwater and sediment/legacy sources may be better defined. For groundwater sources, treatment is better stated as prevention – that is, prevention of pollutant sources by best management practices. Such practices include: fertilization controls; sediment and toxic material controls at marinas, ports and other near shore activities; and pesticide controls on agricul tural activities. Sediment/legacy sources can be reduced using a combination of two activities: the reduction of the source of sediment (e.g., runoff from construction sites, excess erosion, etc.) and elimination of built-up sediment in slow moving surface waters (e.g., lake sediments or stream deposits). Elimination or reduction of one without a concomitant reduction of the other will not result in a long-term control of the pollutant source.

7-38Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



## SECTION 7 ADDITI ONAL REFERENCES

CDM. 1993. California Best Management Practice Handbooks.

FDACS (Florida Department of Agriculture and Consumer Services) 2004. Water Quality/Quantity Best Management Practices for Florida Vegetable and Agronomic Crops

FDER. 1988. The Florida Development Manual: A Guide to Sound Land and Water Management.

http://dnrweb.dnr.state.md.us/watersheds/surf/bmp/info/ripariangrass.html

http://economics.ag.utk.edu/extension/bcstudy/Row%20Crops.p65linked2.pdf

http://efotg.nrcs.usda.gov/references/public/SD/330final.pdf

http://ianrpubs.unl.edu/soil/g750.htm#terplan

http://lubbock.tamu.edu/irrigate/documents/2074410-L5205.pdf

http://web.aces.uiuc.edu/vista/pdf_pubs/RIDGING.PDF

http://www.bae.ncsu.edu/programs/ex tension/publicat/wqwm/ebae103 83.html

http://www.bae.ncsu.edu/programs/ extension/publicat/wqwm/ebae18593.html

http://www.epa.gov/watertrain/pdf/Agriculture.pdf

http://www.gov.on.ca/OMAFRA/english/engineer/facts/89-167.htm

http://www.unu.edu/unupress/unupbooks/uu27se/ uu27se09.htm#1.%20mulch%20farming

Indian River Citrus. 2002. BMPs. Indian River Research and Education Center.

Metropolitan Government of Nashville and Davidson County. 2000. Stormwater Management Manual.

National Resources Conservation Service (NRCS). 1999. Conservation Practice Standard No. 393 – Filter Strip.

SFWMD. 2002. Best Management Practices for South Florida Urban Stormwater Management Systems.

Smajstrla, A.G., B.J. Boman, D.Z. Haman, F.T. Izuno, D.J. Pitts and F.S. Zazueta. 1997. Basic Irrigation Scheduling in Florida Bulletin No. 249. Institute of Food and Agricultural Sciences, University of Florida.

7-39Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.03/05-003



### Tampa Bay National Estuary Program (TBNEP). 1996. "Charting the Course: The Comprehensive Conservation Management Plan for Tampa Bay."

Tyack, J.N., and R.A. Fenner. 1997. “The Use of Scaling Laws in Characterising Residence Time in Hydrodynamic Separators.” Presented at the 1997 IAWQ Conference, Aalborg, Denmark.

U.S. EPA, 1999. Stormwater Technology Fact Sheet – Porous Pavement.

U.S. EPA, 1999. Stormwater Technology Fact Sheet – Storm Water Wetlands.

United States Environmental Protection Agency. 1993. Report EPA-840-B-92-002.

Wade, D., Janicki, A., Pribble, R. 1997. Watershed Management Model for Optimal Allocation of BMPs User’s Guide and Case Study . Tampa Bay National Estuary Program Technical Publication No. 07-96.

Wanielista, M.P., and Y.A. Yousef. 1993. Stormwater Management. John Wiley & Sons.

  

7-40Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.02/04-003



# Section 8 MODEL DOCUMENTATION

TMDL Report Prepare the Draft

TMDL Report

Finalize the Draft TMDL

Report TMDL Report

No

23 Duplication and Distribution of the Final TMDL Report Yes

Transfer of Final
Electronic Files and 24

Documentation FDEP
A cceptance Clarification/Liaison/Status Meetin g 19 Draft Report

20

Review Comments Independent

Technical

Review

21

22 Final Report



### Element V

Protocol to Allocate

and Implement TMDL



### 8-1Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.02/04-003



### The next step in the TMDL process is the documentation of the results. Because the results will be used as part of a regulatory process and the potential consequences of the TMDL may be stringent, model documentation has three purposes:

 

### Provide sufficient information so that the TMDL analysis can be reproduced by others;

 

### Provide sufficient information for technical peer review; and

 

### Summarize potential data and analysis refinements as may be required.



# 8.1 TMDL Documentation Outline

Based on the review of TMDL requirements by EPA and those suggested by other states (EPA, 1999a; EPA Region 9, 2000; Idaho Division of Environmental Quality, 1999; EPA, 1999b; Virginia Department of Environmental Quality, 2000), Table 8.1 provides the recommended general outline of the TMDL documentation. The outline provides information on each area identified in this Model Documentation Protocol including data collection; standards and targets; watershed and receiving water data assessment; site specific model preparation, verification, calibration, and validation; model application; TMDL definition; TMDL allocation; and TMDL implementation.
As part of the appendices of the report, references, correspondence and a complete digital record of data and analysis used for the TMDL should be included. The model itself should be included as well as all model input datasets a nd output files in digital form. Example input and output may also be valuable in hardcopy form. Finally, the appendix should include a digital version of the documents in Adobe Acrobat © format.



# 8.2 TMDL Documentation Form

For quick reference to the TMDL analysis, a TMDL documentation form is recommended, as shown in Figure 8.1 . The documentation form is relatively simple; however, it allows for quick reference to a specific TMDL analysis as well as to the documents related to the TMDL and the source of the information about the TMDL analysis. The documentation form should be filled out as part of the TMDL analysis and access to the documentation form should be available from the FDEP TMDL website as well as project files and library references.

8-2Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.02/04-003



### Table 8.1 Florida TMDL Protocol Recommended TMDL Documentation Outline

Executive Summary

1. Introduction
1.1. Purpose of Document
1.2. Problem Identification Including Parameters of Concern
2. Water Segment Description
2.1. Name, Location and Mapping
2.2. 303(d) Listed and Related Parameters
2.3. General Watershed and Receiving Water Descriptions
3. Applicable Water Quality Standards and Targets
3.1. Water Quality Standards
3.2. Numerical Targets (If Any)
4. Data Collection and Analysis

4.1. Watershed Data
4.1.1. Rainfall, Evaporation, and other Meteorological Data

4.1.2. Soils
4.1.3. Topography and Subbasins
4.1.4. Land Use and Impervious Area

4.1.5. Point Sources
4.1.6. Nonpoint Sources
4.1.7. Tributary Stage and Flow
4.1.8. Tributary Cross-sections
4.1.9. Existing Models
4.1.10. Reports
4.2. Receiving Water Data
4.2.1. Water Quantity Data
4.2.1.1 Bridges, Culverts, Weirs, and Gates
4.2.1.2 Stages and Flows
4.2.1.3 Bathymetry

4.2.1.4 Cross-sections

8-3Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.02/04-003



### 4.2.1.5 Boundary Conditions
4.2.2. Water Quality Data

4.2.2.1 Concentrations

4.2.2.2 Loads

4.2.2.3 Sediments
4.2.2.4 Biology

4.2.2.5 Other Considerations
4.2.3. Existing Models
4.3. Data Analysis Summary
4.3.1. Stages and Flows

4.3.2. Concentrations and Loads

4.3.3. Seasonal Variations
4.3.4. Uncertainty

4.3.5. Data Needs and Refinements
4.3.6. TMDL from Data (if applicable)
5. Site Specific Model Selection, Preparation, Verification, Calibration, and Validation
5.1. Model(s) Selection and Description
5.2. Model Preparation

5.2.1. Model Parameters
5.2.2. Model Boundary Conditions

5.2.3. Model Simulation Periods

5.3 Model Verification

5.3.1 Conservation of Mass
5.3.2 Numerical Stability

5.3.3 Other Tests

5.4 Model Calibration

5.4.1 Simulation Period
5.4.2 Watershed or Receiving Water Variations

5.4.3 Goodness of Fit Tests
5.4.4 Sensitivity Analysis

5.5 Model Validation

5.5.1 Simulation Period

8-4Florida Department of Environmental Protection June 2006 TMDL Protocol Version 6.0 Task Assignment 003.02/04-003



### 5.5.2 Watershed or Receiving Water Variations

5.5.3 Goodness of Fit Tests
5.6 Model Uncertainty and Margin of Safety
5.7 Model Quality Control

5.8 Recommended Data Needs and Model Refinements
6. Model Application
6.1. Design Conditions and Periods
6.2. Natural Background Conditions
6.3. Simulations Under Design Conditions
6.3.1. Existing Point Sources and Nonpoint Sources
6.3.2. Existing Point Sources and Nonpoint Sources at 45% Participation
6.3.3. Existing Point Sources and Nonpoint Sources at 90% Participation
6.4. Model Uncertainty and Margin of Safety

6.5. Model Conclusions and Recommendations
7. TMDL Allocation and Implementation
7.1. Total Loading(s) Allowed and Margin of Safety
7.2. Total Reduction(s) Required
7.3. Allocation of Total Load(s) to Point Sources and Nonpoint Sources
7.4. Recommendations for Updates and Refinements

Appendices

A. TMDL Documentation Form
B. Correspondence
C. Data Summary and Tables
D. Digital Copy of Model (CD) and Copy of Input and Output Files and Example Hardcopies
E. Digital Copy of Report (PDF or equivalent format)

F. References

  

8-5

### Figure 8.1 Florida TMDL Protocol Documentation Form

Florida TMDL Protocol
Documentation Form

Water Segment Description: Water Segment Common Name
Watershed Name
WBID Number Water Body Type (Lake, River, Estuary)

Pollutants of Concern: Dissolved Oxygen/BOD Sediments
Nutrients Toxic Materials Pathogens
Other
List:

General Watershed Description: Total Area (acres) acres General Land Uses Percent Impervious
Annual Rainfall inches Design Conditions:
Low Flow High Flow
Other Period

Total Maximum Daily Load Definition:
Load Units Existing Load Reduction Required
Point Source Allocation Nonpoint Source Allocation
Seasonal Variation
Load For Future Growth Margin Of Safety Statement of Uncertainty
Potential Refinements

References:
State of Florida Contact
Phone
e-mail
Name of TMDL Document