Urban Stormwater

BMP Performance Monitoring

A Guidance Manual for Meeting the National

Stormwater BMP Database Requirements

April 2002
Urban Stormwater BMP Performance 

Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

Prepared by

GeoSyntec Consultants

Urban Drainage and Flood Control District

and

Urban Water Resources Research Council (UWRRC) of ASCE

In cooperation with

Office of Water (4303T)

US Environmental Protection Agency

Washington, DC 20460 

April 2002

EPA-821-B-02-001
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

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TABLE OF CONTENTS

List of Tables................................................................................................................................. viii

List of Figures .................................................................................................................................. x

Acknowledgements and Disclaimer................................................................................................ xi

1 INTRODUCTION ........................................................................................................................1

1.1 Scope.............................................................................................................................1

1.1.1 State of the Practice ....................................................................................................2

1.1.2 The Need for Guidance...............................................................................................2

1.1.3 National Stormwater Best Management Practices Database ......................................2

1.2 Format and Content of This Document ........................................................................2

2 BMP MONITORING OVERVIEW.............................................................................................4

2.1 Context of BMP Monitoring in the Regulatory Environment ......................................4

2.2 BMP Monitoring Goals.................................................................................................5

2.3 Physical and Chemical Characteristics of Stormwater Runoff.....................................7

2.4 Stormwater Quality Monitoring Challenges.................................................................8

2.5 Complexities Specific to BMP Monitoring ..................................................................9

2.5.1 Considerations for Evaluating BMP Effectiveness...................................................10

Load Versus Water Quality Status Monitoring.......................................................10

Consideration of Parameters for Monitoring...........................................................12

2.6 BMP Types and Implications for Calculation of Efficiency ......................................13

2.7 Relationship Between Monitoring Study Objectives and Data Analysis ...................14

2.8 Physical Layout and Its Effect on Efficiency and Its Measure...................................15

2.9 Relevant Period of Impact ..........................................................................................16

2.9.1 Concentrations, Loads, and Event Mean Concentrations.........................................17

2.9.1.1 Concentrations .................................................................................................17

2.9.1.2 Loads................................................................................................................17

2.9.1.3 Event Mean Concentrations.............................................................................18

2.9.2 Measures of BMP Efficiency....................................................................................18

2.9.2.1 Historical Approaches......................................................................................21

Efficiency Ratio.......................................................................................................21

Definition........................................................................................................21

Assumptions...................................................................................................23

Comments.......................................................................................................23

Example..........................................................................................................24

Summation of Loads ...............................................................................................24

Definition........................................................................................................24

Assumptions...................................................................................................24

Comments.......................................................................................................25

Example..........................................................................................................25

Regression of Loads (ROL) ....................................................................................25

Definition........................................................................................................25
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Assumptions...................................................................................................26

Comments.......................................................................................................27

Mean Concentration ................................................................................................29

Definition........................................................................................................29

Assumptions...................................................................................................29

Comments.......................................................................................................30

Efficiency of Individual Storm Loads.....................................................................30

Definition........................................................................................................30

Assumptions...................................................................................................31

Comments.......................................................................................................31

Summary and Comparison of Historical Methods..................................................32

2.9.2.2 Other Methods and Techniques.......................................................................32

“Irreducible Concentration” and “Achievable Efficiency” .....................................32

Percent Removal Relative to Water Quality Standards...........................................36

“Lines of Comparative Performance©” ..................................................................37

Multi-Variate and Non-Linear Models....................................................................40

2.9.2.3 Recommended Method ....................................................................................40

Effluent Probability Method....................................................................................40

2.9.2.4 Reference Watershed Methods........................................................................43

2.9.3 BMPs and BMP Systems..........................................................................................44

3 DEVELOPING A BMP MONITORING PROGRAM ..............................................................45

3.1 Phase I – Determine Objectives and Scope of BMP Water Quality Monitoring 

Program ......................................................................................................................46

3.1.1 Monitoring and Literature Review to Assess BMP Performance.............................47

3.1.2 Monitoring to Assess Compliance with Surface Water quality criteria ...................49

3.1.3 Criteria for the Protection of Aquatic/Marine Life ...................................................49

3.1.4 Human Health ...........................................................................................................50

3.1.5 Application of Water quality criteria to Stormwater ................................................50

3.1.6 Groundwater and Sediment Standards......................................................................51

3.1.7 Scope of Work for BMP Monitoring Program .........................................................51

3.1.8 Information Needs to Meet Established Goals of BMP Monitoring ........................55

3.2 Phase II – Develop BMP Monitoring Plan .................................................................56

3.2.1 Recommendation and Discussion of Monitoring Locations.....................................56

Integration of BMP Monitoring into a Municipal Monitoring Program.................57

Sampling from a Well Mixed Location...................................................................58

3.2.1.1 Upstream..........................................................................................................59

3.2.1.2 Downstream .....................................................................................................60

3.2.1.3 Intermediate Locations.....................................................................................60

3.2.1.4 Rainfall.............................................................................................................61

Site Proximity..........................................................................................................61

Number of Gauges...................................................................................................62

3.2.1.5 Groundwater ....................................................................................................62

3.2.1.6 Sediment Sampling ..........................................................................................63

3.2.1.7 Dry Deposition.................................................................................................63

3.2.1.8 Modeling Methods...........................................................................................64
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Estimates of Water Quality Parameters...................................................................64

Estimates of Flow....................................................................................................67

Estimates of Rainfall ...............................................................................................67

3.2.2 Recommendation and Discussion of Monitoring Frequency....................................68

3.2.2.1 Statistical Underpinnings of Study Design ......................................................68

3.2.2.2 Factors Affecting Study Design.......................................................................69

Number of Samples.................................................................................................69

Determining the Number of Observations Needed .................................................70

3.2.3 Recommendation and Discussion of Water Quality Parameters and Analytical 

Methods.....................................................................................................................76

3.2.3.1 Selecting Parameters........................................................................................76

3.2.3.2 Dissolved vs. Total Metals...............................................................................79

3.2.3.3 Measurements of Sediment Concentration ......................................................79

3.2.3.4 Analytical Methods..........................................................................................81

3.2.4 Recommendation and Discussion of Monitoring Equipment and Methods.............83

3.2.4.1 Equipment........................................................................................................83

Data Loggers ...........................................................................................................83

Power Requirements...........................................................................................87

Flow ....................................................................................................................89

Volume-Based Methods.................................................................................91

Stage-Based Methods.....................................................................................91

Manning’s Equation............................................................................................92

Other Empirical Stage-Flow Relationships ........................................................93

Stage Based Method Using Weirs and Flumes...................................................93

Stage-Based Variable Gate Meters.....................................................................94

Velocity-Based Methods.................................................................................94

Tracer Dilution Methods................................................................................95

Constant Injection Rate Tracer Dilution Studies................................................95

Total Recovery Tracer Dilution Studies.............................................................95

Pump Discharge Method ................................................................................95

3.2.4.2 Automatic Sampling Techniques.....................................................................96

Selection of Primary Flow Measurement Device....................................................96

Types of Primary Flow Measurement Devices..............................................96

Weirs...................................................................................................................97

Flumes.................................................................................................................97

Considerations for Selection of Primary Flow Measurement Device............99

Range of Flows...................................................................................................99

Flow Rate..........................................................................................................100

Accuracy ...........................................................................................................100

Cost ...................................................................................................................100

Head Loss and Flow Characteristics.................................................................101

Sediment and Debris.........................................................................................101

Construction Requirements...............................................................................101

Selection of Secondary Flow Measurement Device..............................................102

Float Gauge.......................................................................................................103

Bubbler Tube ....................................................................................................103
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Ultrasonic Depth Sensor ...................................................................................104

Pressure Probe...................................................................................................105

Ultrasonic “Uplooking” ....................................................................................106

Radar/Microwave..............................................................................................106

Equipment for Measuring Velocity.......................................................................107

Methods Suitable for Calibration .................................................................107

Tracer Studies ...................................................................................................108

Rotating-Element Current Meters.....................................................................108

Pressure Sensors................................................................................................108

Acoustical Sensors............................................................................................108

Float-and-Stopwatch Method............................................................................109

Deflection (or Drag-Body) Method ..................................................................109

Methods Most Suitable for Continuous Velocity Monitoring......................109

Ultrasonic (Doppler) Sensors............................................................................109

Electromagnetic Sensors...................................................................................110

Acoustic Path ....................................................................................................111

Water Quality Sample Collection Techniques......................................................111

Grab Samples ...............................................................................................111

Composite Samples......................................................................................112

Automatic Sampling..............................................................................................114

Automatic Sampling Equipment ..................................................................115

Overland Flow Sampler................................................................................118

In-situ Water Quality Devices, Existing Technology ..................................119

In-situ Water Quality Devices, Future Technologies...................................121

Ion-Selective Electrodes ...................................................................................121

On-Line Water Quality Analyzers....................................................................121

Particle Size Analyzers.....................................................................................122

In-situ Filtration and Extraction System...........................................................123

Remote Communications with Automatic Equipment..........................................123

Manual Sampling ..................................................................................................124

Manual Grab Sampling Equipment..............................................................125

Manual Composite Sampling Equipment.....................................................125

3.2.4.3 Error Analysis and Measurement Accuracy ..................................................126

3.2.5 Recommendation and Discussion of Storm Criteria...............................................127

3.2.5.1 Storm Characteristics.....................................................................................127

3.2.6 Recommendation and Discussion of QA/QC .........................................................129

3.2.6.1 Sampling Methods.........................................................................................132

Contamination/Blanks...........................................................................................133

Reconnaissance and Preparations..........................................................................134

Site Visits..........................................................................................................134

Laboratory Coordination...................................................................................134

Sample Containers/Preservation/ Holding Times.............................................135

Recommended Field QA/QC Procedures..............................................................135

Field Blanks..................................................................................................135

Field Duplicate Samples...............................................................................135

Field Sample Volumes .................................................................................136
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Chain of Custody..........................................................................................136

Recommended Laboratory QA/QC Procedures....................................................136

Method Blanks .............................................................................................136

Laboratory Duplicates..................................................................................136

Matrix Spike and Spike Duplicates..............................................................136

External Reference Standards ......................................................................136

3.2.7 Recommendations for Data Management...............................................................137

3.2.7.1 Database Requirements..................................................................................137

Analysis of Database Links...................................................................................138

Analysis of Outlying Records ...............................................................................138

Sample Comparisons Between Original Documents and Final Data Set..............139

Digital Conversion of Data....................................................................................139

Double Data Entry and Optical Character Recognition ........................................139

3.3 Phase III - Implementation of Monitoring Plan........................................................139

3.3.1 Training of Personnel..............................................................................................139

3.3.2 Installation of Equipment........................................................................................140

3.3.3 Testing and Calibrating Equipment ........................................................................141

3.3.4 Conducting Monitoring...........................................................................................141

3.3.5 Coordinate Laboratory Analysis.............................................................................143

3.4 Phase IV - Evaluation and Reporting of Results ......................................................144

3.4.1 Validate Data ..........................................................................................................144

3.4.2 Evaluate Results......................................................................................................144

3.4.2.1 Preliminary Data Evaluation..........................................................................145

3.4.2.2 Definitive Evaluations ...................................................................................145

3.4.3 Report Results.........................................................................................................146

3.4.3.1 National Stormwater BMP Database Requirements......................................147

3.4.3.2 Standard Format Examples............................................................................156

General Test Site Information ...............................................................................156

Watershed Information..........................................................................................159

Structural BMP Information..................................................................................164

Non-Structural BMP Information .........................................................................166

Detention Basin Design Data ................................................................................169

Retention Pond Design Data .................................................................................172

Percolation Trench and Dry Well Design Data.....................................................175

Media Filter Design Data ......................................................................................178

Grass Filter Strip Design Data...............................................................................181

Wetland Channel and Swale Design Data.............................................................183

Porous Pavement Design Data ..............................................................................186

Infiltration Basin Design Data...............................................................................189

Hydrodynamic Device Design Data......................................................................192

Wetland Basin Design Data ..................................................................................194

Monitoring Station Information ............................................................................198

Precipitation Data ..................................................................................................201

Flow Data ..............................................................................................................203

Water Quality Data................................................................................................205

3.4.3.3 On-line Information .......................................................................................207
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References ..................................................................................................................................208

Index ..................................................................................................................................214

APPENDIX A

APPENDIX B

APPENDIX C

APPENDIX D
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List of Tables

Page

Table 2.1: Objectives of BMP implementation projects and the ability of comprehensive 

water quality monitoring studies to provide information useful for 

determining performance and effectiveness ...................................................6

Table 2.2: Examples of water quality parameters and relevant monitoring 

period ............................................................................................................17 

Table 2.3: Summary of historical, alternative, and recommended methods for 

BMP water quality monitoring data analysis................................................20

Table 2.4: Example of ER method results for TSS in the Tampa Office Pond .............24

Table 2.5: Example of SOL method results for TSS in the Tampa Office Pond...........25

Table 2.6: Example of ROL method results for TSS in the Tampa Office Pond. .........27

Table 2.7: Example of Individual Storm Loads Method results for TSS in the 

Tampa Office Pond.......................................................................................32

Table 2.8: Comparison of BMP efficiency methods......................................................32

Table 2.9: “Irreducible concentrations” as reported by Scheuler, 2000. .......................33

Table 2.10: Example TSS results for typical ER Method................................................33

Table 2.11: Example TSS results for demonstration of Relative Efficiency

approach........................................................................................................35

Table 2.12: Example of percent removal relative to receiving water quality limits 

approach........................................................................................................36

Table 3.1: Typical urban stormwater runoff constituents and recommended detection 

limits .............................................................................................................79

Table 3.2: Flow measurement methods............................................................................. 91

Table 3.3: Equipment for measuring depth of flow ........................................................ 103

Table 3.4: Velocity measurement methods suitable for calibration.............................108

Table 3.5: National Stormwater BMP Database requirements for all BMPs ..............149

Table 3.6: National Stormwater BMP Database requirements for structural

BMPs...........................................................................................................150

Table 3.7: National Stormwater BMP Database requirements for 

Non-structural BMPs..................................................................................150

Table 3.8: National Stormwater BMP Database requirements for individual 

structural BMPs ..........................................................................................151

Table 3.9: National Stormwater BMP Database requirements for 

non-structural BMPs and structural BMPs that are based on 

minimizing directly connected impervious areas .......................................156

Table 3.10: National Stormwater BMP Database requirements for structural 

BMPs that are based on minimizing directly connected 

impervious areas .........................................................................................157

Table 3.11: General test site form data element descriptions ........................................158

Table 3.12: Watershed form data elements description.................................................160

Table 3.13: Structural BMP form data elements description.........................................165

Table 3.14: Non-structural BMP form data elements description .................................167

Table 3.15: Detention Basin design form data elements list..........................................170
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Table 3.16: Retention Pond design form data elements list ..........................................173

Table 3.17: Percolation trench and dry well design form data

elements list ................................................................................................176

Table 3.18: Media filter design form data elements list.................................................179

Table 3.19: Grass filter strip form data elements list.....................................................182

Table 3.20: Wetland channel and swale form data elements list ...................................184

Table 3.21: Porous pavement form data elements.........................................................187

Table 3.22: Infiltration basin form data elements list........................................................ 190

Table 3.23: Hydrodynamic device form data elements..................................................... 193

Table 3.24: Wetland basin form data elements list............................................................ 195

Table 3.25: Monitoring station form data elements .......................................................... 199

Table 3.26: Precipitation form data elements ................................................................202

Table 3.27: Flow form data elements.............................................................................204

Table 3.28: Water quality form data elements................................................................... 206

Table A.1: Example of inputs for estimation of errors in flow measurement 

Devices....................................................................................................... A-5

Table A.2: Summary of examples demonstrating the propagation of errors in 

flow measurement...................................................................................... A-7

Table D.1: Relationships of log-normal distributions.................................................. D-1
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List of Figures

Page

Figure 2.1 ROL plot for use in calculating efficiency for TSS

using the Tampa Office Pond (1990)............................................................28

Figure 2.2 ROL plot for use in calculating efficiency for TSS

using the Tampa Office Pond (1993-1994).......................................28

Figure 2.3 ROL plot for use in calculating efficiency for TSS using the Tampa 

Office Pond (1994-1995)..............................................................................29

Figure 2.4 Removal Efficiency (ER Method) of TSS as a function of influent 

concentration ................................................................................................38

Figure 2.5 Removal Efficiency (ER Method) of total phosphorous as a 

function of influent concentration.................................................................38

Figure 2.6 Removal Efficiency (ER Method) of total zinc as a function of influent 

concentration.................................................................................................39

Figure 2.7 Percent removal as a function of influent concentration for randomly 

generated, normally distributed influent and effluent concentrations. .........39

Figure 2.8 Probability plot for Suspended Solids...........................................................42

Figure 2.9 Probability plot for Total Dissolved Solids ..................................................42

Figure 2.10 Probability plot for Chemical Oxygen Demand ...........................................42

Figure 3.1 Nomograph relating coefficient of variation of a samples set to the 

allowable error in the estimate of the population mean................................71

Figure 3.2 Number of samples required using a paired sampling approach to observe a 

statistically significant percent difference in mean concentration as a function 

of the coefficient of variation

(power of 80% and confidence of 95%) .......................................................75

Figure 3.3 Data logger with weatherproof housing........................................................84

Figure 3.4 Data logger without housing.........................................................................85

Figure 3.5 Data logger summary....................................................................................88

Figure 3.6 Parshall flume ...............................................................................................98

Figure 3.7 H-flume .........................................................................................................98

Figure 3.8 Bubbler flow meter .....................................................................................104

Figure 3.9 Ultrasonic-depth sensor module .................................................................105

Figure 3.10 Pressure transducers....................................................................................106

Figure 3.11 Area velocity sensors module .....................................................................110

Figure 3.12 Automatic sampler......................................................................................116

Figure 3.13 VOC sampler ..............................................................................................117

Appendix B Figures: Number of samples required for various powers, confidence 

intervals, and percent differences ...............................................................B-1
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Acknowledgements and Disclaimer 

The authors, Eric Strecker, P.E. of GeoSyntec Consultants, Ben Urbonas, P.E. Urban 

Drainage and Flood Control District, Denver, Marcus Quigley, P.E., Jim Howell, and 

Todd Hesse of GeoSyntec Consultants would like to thank Jesse Pritts, P.E. and Eric 

Strassler of the Environmental Protection Agency and Tom McLane and Lorena Diaz of 

the American Society of Civil Engineers (ASCE) for their support for and participation in 

the ASCE/EPA National Stormwater Best Management Practices Database Project and the 

development of this guidance. The authors would also like to thank the following 

members of ASCE’s Urban Water Resources Research Council for their thorough review 

and contributions to this guidance: 

Robert Pitt, P.E., Ph.D. (University of Alabama, Birmingham) 

Eugene Driscoll, P.E. 

Roger Bannerman, P.E. (Wisconsin Department of Natural Resources) 

Shaw Yu, P.E., Ph.D. (University of Virginia) 

Betty Rushton (Southwest Florida Water Management District) 

Richard Field (EPA), P.E. 

Jonathan Jones, P.E. (Wright Water Engineers) 

Jane Clary (Wright Water Engineers) 

Tom Langan (Wright Water Engineers) 

Sections of this manual were developed by the authors concurrently with the Federal 

Highway Administration’s (FHWA) “Guidance Manual For Monitoring Highway Runoff 

Water Quality.” Although the focus of the FHWA manual is on highway runoff 

monitoring, much of the information on equipment selection, use, and installation is 

applicable to best management practice monitoring and thus was adapted for this 

guidance. 

In addition, portions of this document were adapted from work originally conducted for 

the Washington State Department of Ecology’s (DOE) November 1995, “Stormwater 

Monitoring Guidance Manual” by an author of this document (Eric Strecker) and Mike 

Milne (Brown and Caldwell), Terry Cook (URS Group, Inc.), Gail Boyd (URS Group, 

Inc.), Krista Reininga (URS Group, Inc.), and Lynn Krasnow. The thoroughness and 

specific insight provided in the DOE Manual were useful in assembling this guidance. 

The authors would also like to thank Joan LeBlanc, and Kathy Staffier (GeoSyntec 

Consultants) for editorial review and edits of the final document. 

Disclaimer: 

Mention of trade names or commercial products does not constitute endorsement by EPA 

or ASCE, or recommendation for use.
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

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1 Introduction

1.1 Scope 

Existing guidance is available for assessing the effectiveness of stormwater best

management practices (EPA 1997; FHWA 2000). However, few existing documents

provide targeted practical assistance in conducting and reporting data from a water quality 

based monitoring program that results in data that are useful for assessing BMP

effectiveness on a broader scale.

This guidance has been developed by integrating experience gleaned from field 

monitoring activities conducted by members of ASCE’s Urban Water Resource Research

Council and through the development of the ASCE/EPA National Stormwater Best

Management Practices Database. The manual is intended to help achieve stormwater BMP 

monitoring project goals through the collection of more useful and representative rainfall, 

flow, and water quality information. Many of the recommended protocols (particularly

those for reporting monitoring, watershed, and design information) are directly related to

requirements of the National Stormwater Best Management Practices Database. 

This manual is intended to improve the state of the practice by providing a recommended

set of protocols and standards for collecting, storing, analyzing, and reporting BMP

monitoring data that will lead to better understanding of the function, efficiency, and

design of urban stormwater BMPs. This manual provides insight into and guidance for

strategies, approaches, and techniques that are appropriate and useful for monitoring

BMPs. 

This document addresses methods that were in use at the time it was written. As the state 

of the practice and the design of monitoring equipment progress, new monitoring

approaches and techniques, more sensitive devices, and equipment based on new

technologies will likely be employed. Although the technology may change somewhat

from that described herein, most of the basic flow and water quality monitoring methods

discussed in this document have a long history of use and will most likely remain viable

even as new and different technologies emerge.

This manual focuses primarily on the collection, reporting, and analysis of water quantity

and quality measurements at the heart of quantitative BMP efficiency projects. It does not 

address, in detail, sediment sampling methods and techniques, biological assessment, 

monitoring of receiving waters, monitoring of groundwater, streambank erosion, channel

instability, channel morphology, or other activities that in many circumstances may be as, 

or more, useful for measuring and monitoring water quality for assessing BMP efficiency.
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April 25, 2002

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1.1.1 State of the Practice

Many studies have assessed the ability of stormwater treatment BMPs (e.g., wet ponds,

grass swales, stormwater wetlands, sand filters, dry detention, etc.) to reduce pollutant

concentrations and loadings in stormwater. Although some of these monitoring projects

conducted to date have done an excellent job of describing the effectiveness of specific

BMPs and BMP systems, there is a lack of standards and protocols for conducting BMP

assessment and monitoring work. These problems become readily apparent for persons

seeking to summarize the information gathered from a number of individual BMP

evaluations. Inconsistent study methods, lack of associated design information, and

reporting protocols make wide-scale assessments difficult, if not impossible. (Strecker et

al. 2001; Urbonas 1998) For example, individual studies often include the analysis of

different constituents and utilize different methods for data collection and analysis, as well 

as report varying degrees of information on BMP design and flow characteristics. The

differences in monitoring strategies and data evaluation alone contribute significantly to

the range of BMP “efficiency” that has been reported in literature to date.

1.1.2 The Need for Guidance

Municipal separate storm sewer system owners and operators need to identify effective

BMPs for improving stormwater runoff water quality. Because of the current state of the

practice, however, very little sound scientific data are available for making decisions about 

which structural and non-structural management practices function most effectively under 

what conditions; and, within a specific category of BMPs, to what degree design and

environmental static and state variables directly affect BMP efficiency. This guidance

addresses this need by helping to establish a standard basis for collecting water quality,

flow, and precipitation data as part of a BMP monitoring program. The collection, storage, 

and analysis of this data will ultimately improve BMP selection and design.

1.1.3 National Stormwater Best Management Practices Database

The National Stormwater BMP Database (Database) serves two key purposes: (1) to

define a standard set of data reporting protocols for use with BMP monitoring efforts; and 

(2) to assemble and summarize historical and future BMP study data in a standardized

format. The software consists of a data entry module for reporting data on new BMP

studies and a search engine module to allow users to retrieve data. The Database is a userfriendly, menu-driven software program developed in a run-time version of Microsoft®

Access 97 and Access 2000. The software has been distributed on CD-ROM and is now

also accessible via the Internet at www.bmpdatabase.org.

1.2 Format and Content of This Document

This document is broken down into two main sections following this introduction:

Section 2 provides an overview of BMP monitoring. Discussion is provided on the context 

of BMP monitoring, difficulties in assessing BMP performance, and understanding the
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April 25, 2002

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relationship between BMP study design and the attainment of monitoring program goals.

Useful analysis of data collected from BMP monitoring studies is essential for

understanding and comparing BMP monitoring study results. A summary of historical

and recommended approaches for data analysis is provided in this section to elucidate the 

relationship between the details and subtleties of each analysis approach and the

assessment of performance.

Section 3 discusses the specifics of developing a monitoring program, selecting

monitoring methods and equipment, installing and using equipment, implementing

sampling approaches and techniques, and reporting information consistent with the

National Stormwater Best Management Practices Database. 

In addition, four appendices have been included in this guidance document. The first

appendix describes methods for calculating expected errors in field measurements. The

second provides detailed information about the number of samples required to obtain

statically significant monitoring data. The third appendix includes charts for estimating

the number of samples required to observe a statically significant difference between two

populations for a various levels of confidence and power. The final appendix is a table for 

estimating arithmetic descriptive statistics based on descriptive statistics of logtransformed data.
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A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

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2 BMP Monitoring Overview

This section provides an overview of BMP monitoring program context and execution,

including a discussion of approaches used for quantifying BMP efficiency.

2.1 Context of BMP Monitoring in the Regulatory Environment 

BMP monitoring is conducted by researchers, public entities, and private companies for

meeting both regulatory and non-regulatory needs. This section briefly discusses some of 

the regulatory programs that drive BMP monitoring programs. 

A number of environmental laws exist for implementation of stormwater and BMP

monitoring programs including:

• The Clean Water Act (CWA) of 1972: 

Section 208 of 1972 CWA requires every state to establish effective BMPs to

control nonpoint source pollution. The 1987 Water Quality Act (WQA) added

section 402(p) to the CWA, which requires that urban and industrial stormwater

be controlled through the National Pollutant Discharge Elimination System

(NPDES) permit program.

Section 303(d) of WQA requires the states to list those water bodies that are not

attaining water quality standards including designated uses and identification of

relative priorities among the impaired water bodies. States must also develop

TMDLs (Total Maximum Daily Loads) that quantify the pollutant load or the

impairing pollutants that will bring the waterbody back into attainment.

• The Endangered Species Act:

The Endangered Species Act of 1973 protects animal and plant species currently

in danger of extinction (endangered) and those that may become endangered in

the foreseeable future (threatened). It provides for the conservation of ecosystems 

upon which threatened and endangered species of fish, wildlife, and plants

depend, both through Federal action and by encouraging the establishment of state 

programs.

• Coastal Zone Act Reauthorization Amendments (CZARA) of 1990:

CZARA was passed to help address nonpoint source pollution in coastal waters. 

Each state with an approved coastal zone management program must develop and 

submit to the EPA and National Oceanic and Atmospheric Administration

(NOAA) a Coastal Nonpoint Pollution Control Program (CNPCP), which

provides for the implementation of the most economically achievable
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management measures and BMPs to control the addition of pollutants to coastal

waters.

CZARA does not specifically require that states monitor implementation of

management measures and BMPs. They must, however, provide technical

assistance to local governments and the public in the implementation of the

management measures and BMPs, which may include assistance to predict and

assess the effectiveness of such measures.

CZARA also states that the EPA and NOAA shall provide technical assistance to 

the states in developing and implementing the CNPCP, including methods to

predict and assess the effects of coastal land use management measures on coastal 

water quality and designated uses:

1. Protection of stream and water body designated use (meet fishable and

swimmable goals)

2. Antidegradation policies designated to protect water quality when the

water quality already is higher than existing standards

3. Other state, county, and local regulations or ordinances

As regulations and the application and enforcement thereof change over time, details

about the above environmental laws and their implications for specific sites and

watersheds are best obtained from current EPA, state, county, and local resources.

2.2 BMP Monitoring Goals

BMP monitoring projects are initiated to address a broad range of programmatic,

management, regulatory, and research goals. Goal attainment is often focused on the

achievement of water quality objectives downstream of the BMP. However, there are

many other objectives that have been established as part of BMP implementation projects 

that cannot be measured using a water quality monitoring approach alone. Table 2.1

below describes the relationship between BMP implementation objectives and the ability

of water quality monitoring studies to address the attainment of these objectives.

Studies directed at addressing the efficiency of BMPs in attaining water quality goals are

usually conducted to obtain information to help answer one or more of the following

questions:

• What degree of pollution control or effluent quality does the BMP provide under

normal conditions?

• How does this efficiency vary from pollutant to pollutant?
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• How does this normal efficiency vary with large or small storm events?

• How does this normal efficiency vary with rainfall intensity?

• How do design variables affect efficiency?

• How does efficiency vary with different operational and/or maintenance approaches?

• Does efficiency improve, decay, or remain stable over time?

• How does this BMP's efficiency compare with the efficiency of other BMPs?

The ability of a specific BMP monitoring program to answer these questions and

ultimately address the desire to measure goal attainment is a vital planning stage

component of setting up a meaningful BMP monitoring program. 

Table 2.1: Objectives of BMP implementation projects and the ability of 

comprehensive water quality monitoring studies to provide information useful for 

determining performance and effectiveness

Category Goals of BMP Projects Ability to Evaluate

Performance and Effectiveness

Hydraulics • Improve flow characteristics upstream and/or downstream

of BMP -

Hydrology • Flood mitigation, improve runoff characteristics (peak

shaving)

 ̧

Water Quality • Reduce downstream pollutant loads and concentrations of

pollutants

 ̧

• Improve/minimize downstream temperature impact  ̧

• Achieves desired pollutant concentration in outflow  ̧

• Removal of litter and debris -

Toxicity • Reduce acute toxicity of runoff  ̧

• Reduce chronic toxicity of runoff  ̧

Regulatory • Compliance with NPDES permit -

• Meet local, state, or federal water quality criteria  ̧

1

Implementation

Feasibility

• For non-structural BMPs, ability to function within

management and oversight structure -

Cost • Capital, operation, and maintenance costs -

Aesthetic • Improve appearance of site -

Maintenance • Operate within maintenance, and repair schedule and

requirements -

• Ability of system to be retrofit, modified or expanded -

Longevity • Long-term functionality  ̧

Resources • Improve downstream aquatic environment/erosion control -

• Improve wildlife habitat -

• Multiple use functionality -

Safety, Risk and • Function without significant risk or liability -

Liability • Ability to function with minimal environmental risk

downstream -

Public 

Perception

• Information is available to clarify public understanding of

runoff quality, quantity and impacts on receiving waters

 ̧

 ̧ can be evaluated using water quality monitoring as primary source of information 

 ̧

1 can be evaluated using water quality monitoring as the primary source of information combined with a secondary source of

comparative data

- cannot be directly evaluated using water quality monitoring, but in some cases may be supported by work associated with collecting 

water quality information (i.e., detailed flow data)
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2.3 Physical and Chemical Characteristics of Stormwater Runoff

In this guidance manual, the term "stormwater" refers to more than just storm-driven 

surface runoff. Here the term is expanded to cover water and other substances that are

transported through stormwater conveyance systems during, after, and between storm

events. In addition to the runoff from rainfall or snowmelt, a typical stormwater sample

may contain materials that were dumped, leaked, spilled, or otherwise discharged into the 

conveyance system. The sample may also contain materials that settled out in the system 

toward the end of previous storms and were flushed out by high flows during the event

being sampled. Stormwater also can include dry weather flows such as pavement

washing, pavement cutting wash water, or irrigation. Loads from dry weather flows, in

some cases, can greatly exceed wet weather loads over the course of a year and must be

taken into account.

Stormwater quality tends to be extremely variable (EPA 1983; Driscoll et al. 1990). The 

intensity (volume or mass of precipitation per unit time) of rainfall often varies

irregularly and dramatically. These variations in rainfall intensity affect runoff rate,

pollutant washoff rate, in-channel flow rate, pollutant transport, sediment deposition and

re-suspension, channel scour, and numerous other phenomena that collectively determine 

the pollutant concentrations, pollutant forms, and stormwater flow rate observed at a

given monitoring location at any given moment. In addition, the transitory and

unpredictable nature of many pollutant sources and release mechanisms (e.g., spills,

leaks, dumping, construction activity, landscape irrigation runoff, vehicle washing

runoff), and differences in the time interval between storm events also contribute to

inter-storm variability. As a result, pollutant concentrations and other stormwater

characteristics at a given location should be expected to fluctuate greatly during a single

storm runoff event and from event to event. 

In addition, the complexity of introducing a structural management practice can greatly

affect hydraulics and constituent concentrations in complex ways. For example, flows

from detention facilities are often not confined only to the period of wet weather, as drain 

time can be significant. 

Numerous studies conducted during the late 1970s and early 1980s show that stormwater 

runoff from urban and industrial areas are a potentially significant source of pollution

(EPA 1983; Driscoll et al. 1990). As a result, federal, state and local regulations have

been promulgated to address stormwater quality (see Section 2.1 above).

The impacts of hydrologic and hydraulic (physical as opposed to chemical) changes in

watersheds are increasingly being recognized as significant contributors to receiving

waters not meeting beneficial criteria. These impacts include stream channel changes

(erosion, sedimentation, temperature changes) as well as wetland water level fluctuations.
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2.4 Stormwater Quality Monitoring Challenges

Information collected on the efficiency and design of BMPs serves a variety of goals and 

objectives as discussed in Section 2.2. The principal challenge facing persons

implementing BMP monitoring programs is the great temporal and spatial variability of

stormwater flows and pollutant concentrations. Stormwater quality at a given location

varies greatly both between storms and during a single storm event, and thus a small

number of samples are not likely to provide a reliable indication of stormwater quality at

a given site or the effect of a given BMP. Therefore, collection of numerous samples is

generally needed in order to accurately characterize stormwater quality at a site and BMP 

efficiency (see Section 3.2.2). 

Collecting enough stormwater samples to answer with a high level of statistical

confidence many of the common questions regarding BMP efficiency is generally

expensive and time-consuming. A poorly-designed monitoring program could lead to

erroneous conclusions and poor management decisions, resulting in misdirected or

wasted resources (e.g., staff time, funds, credibility, and political support). Therefore,

before one begins a BMP monitoring program, it is critical to clearly identify and

prioritize the goals of the project, determine the type and quality of information needed to 

attain those goals, and then compare this list of needs to the resources available for

monitoring. If the available resources cannot support the scale of monitoring needed to

provide the quality of information deemed necessary, then consider the following options 

to obtain useful results within your resource limitations (e.g., funds, personnel, time):

• A phased approach wherein you address only a subset of the overall geographic area, 

or only the most important stormwater questions.

• Limiting the number of constituents evaluated as an alternative to reducing the

number of samples collected.

• Utilizing available data from other locations to support decision-making.

The key question should be: "Will the information provided from the monitoring program 

I am considering (and would be able to implement) significantly improve my

understanding of the effectiveness of the BMP being monitored?" If the answer is no,

reconsider the monitoring program.
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2.5 Complexities Specific to BMP Monitoring

Monitoring BMPs introduces a number of specific difficulties into the already complex

task of monitoring stormwater runoff water quality. 

In many ways a structural BMP system is best viewed as an environmental unit process

with a large number of static and state variables affecting functionality of the process. 

For example, static variables that can directly affect BMP system function include:

• BMP design (e.g., length, width, height, storage volume, outlet design, upstream

bypass, model number, etc.)

• Geographical location.

• Watershed size.

• Percent imperviousness.

• Vegetative canopy.

• Soil type.

• Watershed slopes.

• Compaction of soils.

State variables that directly affect BMP function may include:

• Rainfall intensity.

• Flow rate.

• Season.

• Vegetation.

• Upstream non-structural controls.

• Inter-event timing.

• Settings for control structures such as gates, valves, and pumps.

• Maintenance of the BMP.
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The inconsistent use of language in reporting BMP information can compound the

difficult task of assessing physically complex systems. In order to provide a consistent

context for discussion of monitoring approaches in this guidance, the following

definitions are provided:

• Best Management Practice (BMP) - A device, practice, or method for removing,

reducing, retarding, or preventing targeted stormwater runoff constituents, pollutants,

and contaminants from reaching receiving waters.

• BMP System - A BMP system includes the BMP and any related bypass or overflow. 

For example, the efficiency (see below) can be determined for an offline retention

(Wet) Pond either by itself (as a BMP) or for the BMP system (BMP including

bypass).

• Performance - measure of how well a BMP meets its goals for stormwater that the

BMP is designed to treat.

• Effectiveness - measure of how well a BMP system meets its goals in relation to all

stormwater flows.

• Efficiency - measure of how well a BMP or BMP system removes or controls

pollutants.

Researchers often want to determine efficiency of BMPs and BMP systems and to

elucidate relationships between design and efficiency. Efficiency has typically been

quantified by “percent removal”. As is discussed in the following sections, “percent

removal” alone is not a valid measure of the functional efficiency of a BMP (Strecker et

al. 2001). As a result the definition of “efficiency” in this manual can mean any measure 

of how well a BMP or BMP system removes or controls pollutants and is not restricted

by the historical use of the term referring to “percent removal.”

2.5.1 Considerations for Evaluating BMP Effectiveness

Load Versus Water Quality Status Monitoring

The choice between monitoring either (a) the status or condition of the water resource or

(b) the pollutant load and event mean concentrations discharged to the water resource

should be made with care (Coffey and Smolen 1990). Monitoring of loads and event

mean concentrations is focused on obtaining quantitative information about the amount

of pollutants transported to the receiving water from overland, channel and pipe,

tributary, or groundwater flow. Load and concentration monitoring can be used to

evaluate pollutant export at a stormwater BMP. 
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Water Quality Status Monitoring

Water quality status can be evaluated in a number of ways, including: 

• Evaluating “designated use” attainment1.

• Evaluating Water Quality Standards violations.

• Assessing ecological integrity.

• Monitoring an indicator parameter.

Monitoring water quality status includes measuring a physical attribute, chemical

concentration, or biological condition, and may be used to assess baseline conditions,

trends, or the impact of treatment on the receiving water. Monitoring water quality status 

may be the most effective method to evaluate the impact of the management measure

implemented, but sensitivity may be low (Coffey and Smolen 1990). When the

probability of detecting a trend in water quality status is low, load monitoring may be

necessary.

When deciding between measuring load or water quality status (i.e., it is not clear

whether abatement can be detected in the receiving resource), a pollutant budget may

help to make the decision (Coffey and Smolen 1990). The budget should account for

mass balance of pollutant input by source, all output, and changes in storage. Sources of 

error in the budget should also be evaluated (EPA 1993a). 

Pollutant Load and Event Mean Concentration Monitoring

Load monitoring requires considerable effort and should include the protocols that are the 

primary intent of this document. Because of potentially high variability of discharge and 

pollutant concentrations in watersheds impacted by both point and non-point sources,

collecting accurate and sufficient data from a significant number of storm events and base 

flows over a range of conditions (e.g., season, land cover) is important. This manual

describes several methods for collecting and analyzing meaningful pollutant loading and

event concentration data. Most of these methods are also applicable to water quality

status monitoring where specific chemical concentrations must be monitored.

Monitoring for designated use attainment or standards violations should focus on those

parameters or criteria specified in state water quality standards. Where the monitoring

objective includes relating improvements in water quality to the pollution control

activities, it is important that the parameters monitored are connected to the management 

 

1

 See Clean Water Act, Section 303(c)(2)
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measures implemented. For violations of standards, the choice of variable is specified by 

the state water quality standard (EPA 1993a). 

Consideration of Parameters for Monitoring

Many studies have been conducted to assess the effectiveness of stormwater treatment

BMPs to reduce pollutant concentrations and loads in stormwater runoff. Unfortunately, 

inconsistent study methods and reporting make assessment and comparison of BMP

efficiency studies difficult. The studies often analyze different constituents with varying

methods for data collection and analysis. These differences can contribute considerably

to the range of BMP effectiveness observed (Strecker 1994). 

Several protocols for parameter selection have been used in the past. The most widely

applied was developed as a part of the Nationwide Urban Runoff Program (NURP). 

NURP adopted consistent data collection techniques and analytical parameters so that

meaningful comparisons of gathered data could be made. NURP adopted the following

constituents as “standard pollutants characterizing urban runoff” (EPA 1983):

• SSC – Suspended Solids Concentration

• BOD – Biochemical Oxygen Demand

• COD – Chemical Oxygen Demand

• CU – Copper

• Pb – Lead

• Zn – Zinc

• TP – Total Phosphorous

• SP – Soluble Phosphorous

• TKN – Total Kjeldahl Nitrogen

• NO2 + NO3 – Nitrate + Nitrite

The following factors were considered for including a parameter in the list of

recommended monitoring constituents (Strecker 1994):

• The pollutant has been identified as prevalent in typical urban stormwater at

concentrations that could cause water quality impairment.
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• The analytical test used can be related back to potential water quality impairment.

• Sampling methods for the pollutant are straight forward and reliable for a moderately

careful investigator.

• Analysis of the pollutant is economical on a widespread basis.

• Treatment is a viable option for reducing the load of the pollutant.

Similar considerations should go into the planning of water quality constituents and

analytical methods to be used in monitoring the effectiveness of stormwater BMPs. The

NURP parameters are a starting point and may or may not represent constituents of

concern for discharges from specific BMPs. As mentioned previously, there is often a

tradeoff between the breadth and depth of a monitoring program given a fixed cost and,

as a result, narrowing the list of constituents monitored can dramatically improve the

ability to quantify the efficiency of the BMP.

Large volumes of data have been collected over the past 20 years on the performance of

many structural stormwater BMPs, with most of the data relating to the performance of

detention basins, retention ponds, and wetlands. Less data are available on the

effectiveness of other types of BMPs (Urbonas 1994). Many of the reported results do

not demonstrate a clear relationship between the efficiency of similar BMPs among the

sites in which they were investigated. Sufficient parametric data has generally not been

reported with the performance data to permit a systematic analysis of the data collected

(Urbonas 1994). 

There are a number of important parameters that need to be measured and reported

whenever BMP performance is monitored (Urbonas 1994). A detailed discussion on this 

subject is provided in Section 3.4 of this manual.

2.6 BMP Types and Implications for Calculation of Efficiency

The issues involved in selecting methods for quantifying efficiency, performance, and

effectiveness are complex. It would be difficult, at best, to find one method that would

cover the data analysis requirements for the widely varied collection of BMP types and

designs available. When analyzing efficiency, it is convenient to classify BMPs

according to one of the following four distinct categories:

• BMPs with well-defined inlets and outlets whose primary treatment depends upon

extended detention storage of stormwater, (e.g., retention (wet) and detention (dry)

ponds, wetland basins, underground vaults).

• BMPs with well-defined inlets and outlets that do not depend upon significant storage 

of water, (e.g., sand filters, swales, buffers, structural “flow-through” systems).
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• BMPs that do not have a well-defined inlet and/or outlet (e.g., full retention,

infiltration, porous pavement, grass swales where inflow is overland flow along the

length of the swale).

• Widely distributed (scattered) BMPs where studies of efficiency use reference

watersheds to evaluate effectiveness, (e.g., catch basin retrofits, education programs,

source control programs).

Any of the above can also include evaluations where the BMP’s efficiency was measured 

using before and after or paired watershed comparisons of water quality.

The difficulty in selecting measures of efficiency stems not only from the desire to

compare a wide range of BMPs, but also from the large number of methods currently in

use. There is much variation and disagreement in the literature about what measure of

efficiency is best applied in specific situations, however it is generally accepted that event 

mean concentrations and long-term loading provide the best means for observing the

effects of the BMP respectively on acute and chronic pollution. 

It has been suggested that intra-storm monitoring could be used to establish paired

inflow/outflow samples during the storm based upon average travel times. However, this 

method would only be valid if a BMP were functioning as a perfect plug-flow reactor,

which is rarely the case.

2.7 Relationship Between Monitoring Study Objectives and Data Analysis

In selecting a specific method for quantifying BMP efficiency, it is helpful to look at the 

objectives of previous studies seeking such a goal. BMP studies are usually conducted to 

obtain information regarding one or more of the following objectives:

• What degree of pollution control does the BMP provide under typical operating

conditions?

• How does effectiveness vary from pollutant to pollutant?

• How does effectiveness vary with various input concentrations?

• How does effectiveness vary with storm characteristics such as rainfall amount,

rainfall density, and antecedent weather conditions?

• How do design variables affect performance?

• How does effectiveness vary with different operational and/or maintenance

approaches?
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• Does effectiveness improve, decay, or remain stable over time?

• How does the BMP’s efficiency, performance, and effectiveness compare to other

BMPs?

• Does the BMP reduce toxicity to acceptable levels?

• Does the BMP cause an improvement in or protect downstream biotic communities?

• Does the BMP have potential downstream negative impacts?

The monitoring efforts implemented most typically seek to answer a small subset of the

above questions. This approach often leaves larger questions about the efficiency,

performance and effectiveness of the BMP, and the relationship between design and

efficiency, unanswered. This document recommends monitoring approaches consistent

with protocols established as part of the National Stormwater Best Management Practices 

Database project and useful for evaluating BMP data such that some or all of the above

questions about BMP efficiency can be assessed.

2.8 Physical Layout and Its Effect on Efficiency and Its Measure

The estimation of the efficiency of BMPs is often approached in different ways based on

the goals of the researcher. A BMP can be evaluated by itself or as part of an overall

BMP system. The efficiency of a BMP when bypass or overflow are not considered may 

be dramatically different than the efficiency of an overall system. Bypasses and

overflows can have significant effects on the ability of a BMP to remove constituents and 

appreciably reduce the efficiency of the system as a whole. Researchers who are

interested in comparing the efficiency of an offline wet pond and an offline wetland may

not be concerned with the effects of bypass on a receiving water. On the other hand,

another researcher who is comparing offline wet ponds with online wet ponds would be

very interested in the effects of the bypass. Often in past study reports detailed

information about the bypass flows is not available. In some cases, comprehensive

inflow and outflow measurements allow for the calculation of a mass balance that can be 

used to estimate bypass flow volumes. Estimations of efficiency of a BMP system can be 

based on these mass balance calculations coupled with sampling data.

The effect of devices in series is often neglected in the analyses of BMPs. BMPs are

often used in conjunction with a variety of upstream controls. For example detention

ponds often precede wetlands, and sand filters typically have upstream controls for

sediment removal such as a forebay or a structural separator or settling device. 

Depending on the approach used to quantify BMP efficiency, the effects resulting from

upstream controls can have a sizable impact on the level of treatment observed.
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The efficiency of a BMP system or a BMP can be directly affected by the way in which

an operator chooses to physically manage the system. This is the case where parameters 

of a design can be adjusted (e.g., adjustments to the height of an overflow/bypass weir or 

gate). These adjustments can vary the efficiency considerably. In order to analyze a

BMP or BMP system thoroughly, all static and state variables of the system must be

known and documented for each monitoring period. The protocols established for the

National Stormwater Best Management Practices Database (Database) provide a

framework for reporting the static and state variables thought to most strongly contribute 

to BMP efficiency and provide flexibility for non-standard situations.

2.9 Relevant Period of Impact

The period of analysis used in carrying out a monitoring program is important. The

period used should take into account how the parameter of interest varies with time. This 

allows for observation of relevant changes in the efficiency of the BMP on the time scale 

in which these changes occur. For example, in a wetland it is often observed that during

the growing season effluent quality for nutrients improves. The opposite effect may be

observed during the winter months or during any period where decaying litter and plant

material may contribute significantly to export of nutrients and, potentially, other

contaminants. Therefore, monitoring observations may need to be analyzed differently

during different seasons. This variation of performance and more specifically efficiency

on a temporal scale is extremely important in understanding how a specific BMP

functions.

In addition to observing how factors such as climate affect BMP efficiency as a function 

of time, it is important to relate the monitoring period to the potential impact a given

constituent would have on the receiving water. For example, it may not be useful to

study the removal of some heavy metals (e.g., mercury) for a short period of record when 

the negative impacts of such a contaminant are generally expressed over a long time scale 

(accumulation in sediments and biota). Likewise, some parameters (e.g., temperature, 

BOD, DO, pH, TSS and metals) may have a significant impact in the near term. 

Toxicity plays a major role in evaluating the type of monitoring conducted at a site as

well as the time period that should be used to analyze efficiency. Specific constituents

that are acutely toxic may require a short-term analysis on an “intra-storm” basis. Where 

dilution is significant and/or a constituent is toxic on a chronic basis, long-term analysis

that demonstrates removal of materials on a sum of loads or average EMC basis may be

more appropriate. Many contaminants may have both acute and chronic effects in the

aquatic environment. These contaminants should be evaluated over both periods of time. 

Similarly, hydraulic conditions merit both short and long-term examination. Event peak

flows are examples of short-term data, while seasonal variations of the hydrologic budget 

due to the weather patterns are examples of long-term data. Examples of water quality

parameters and their relationship to the time scale over which they are most relevant are

given in Table 2.2.
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Table 2.2: Examples of water quality parameters and relevant monitoring period 

Time Scale for Analysis Water Quality Parameter

Short-term BOD, DO

Long-term Organics, Carcinogens

Both Short- and Long-term Metals, TSS, Nitrogen, 

Phosphorous, Temperature, 

pH, Pesticides

2.9.1 Concentrations, Loads, and Event Mean Concentrations

A variety of tools are available for assessing and quantifying the amount of pollutant

conveyed to and from a BMP. Three primary measures are used most commonly:

concentrations of stormwater at some point in time, the total load conveyed over a

specified duration, or the event mean concentration (EMC).

2.9.1.1 Concentrations

Concentrations measured at a point in time can be useful for BMP efficiency evaluation

in a number of circumstances. Concentrations resulting from samples collected at specific 

times during an event allow the generation of a pollutograph (i.e., a plot of the

concentration of pollutants as a function of time). The generation of pollutographs

facilitates the analysis of intra-event temporal variations in runoff concentration. For

example, pollutographs can be used to determine if the “first-flush” phenomenon was

observed for a specific event. Detailed concentration data is one of the approaches for

assessing concentrations of pollutants that have acutely toxic effects, particularly where

runoff from storm events constitutes a significant proportion of downstream flow. Under 

some circumstances, reduction of peak effluent concentrations may be more important

than event mean concentration reduction. The cost of implementing a monitoring

program that collects sufficient data to evaluate the temporal variation in runoff and BMP 

effluent concentration can be high. The trade-off between collecting data from a larger

number of events versus collecting detailed concentration data from intra-storm periods

often limits the utility of studies that collect detailed concentration data. This type of

detailed monitoring is best focused on outflow monitoring rather than inflow and

outflow.

2.9.1.2 Loads

Loads are typically calculated by the physical or mathematical combination of a number

of individual concentration measurements, which have been assigned by some means an

associated flow volume. A variety of methods are available for estimation of loads. The

method employed is dependent on the sampling and flow measurement techniques used. 

Sampling approaches include collection of either timed samples, flow weighted samples,

or some combination of both. Likewise, flow can be collected continuously,
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intermittently, or modeled from other hydrologic information such as rain gauge

information, or gauging conducted in a nearby watershed. Many BMP monitoring studies 

focus efforts on water quality sample collection and neglect flow measurement. Accurate 

flow measurement or well-calibrated flow modeling is essential for loading

determination.

Loads are often most useful for assessing the impact of a BMP where receiving waters

are lakes or estuaries where long-term loadings can cause water quality problems outside 

of storms. Where the effluent flow rate from a particular BMP is small compared to the

flow rate of the receiving water body, potential downstream impairments are typically not 

dependent on concentrations, but the absolute load of pollutant reaching the receiving

water. For example, loads are the central issue in BMP studies that have direct links to

receiving water bodies that are regulated under the Total Maximum Daily Load (TMDL) 

program, particularly where the concern is pollutants deposited in slow moving systems.

Dry weather flows can also contribute substantially to long-term loading. In addition,

“on-line” BMPs (ponds and possibly filters) that have appreciable dry weather flows

passing through them, may have reduced “capacity” for storage of wet weather

pollutants. For example, pond performance may also be affected by the amount of water 

in the pond before the event, and filters may have some of their adsorption capacity

consumed by pollutants and other constituents during dry weather flows.

2.9.1.3 Event Mean Concentrations

The term event mean concentration (EMC) is a statistical parameter used to represent the 

flow-proportional average concentration of a given parameter during a storm event. It is

defined as the total constituent mass divided by the total runoff volume. The calculation 

of EMCs from discrete observations is discussed in detail in Section 2.5.3. When

combined with flow measurement data, the EMC can be used to estimate the pollutant

loading from a given storm. The EMC approach to understanding BMP efficiency is

primarily aimed at wet weather flows. 

Under most circumstances, the EMC provides the most useful means for quantifying the

level of pollution resulting from a runoff event. Collection of EMC data has been the

primary focus of the National Stormwater Best Management Practices Database Project. 

2.9.2 Measures of BMP Efficiency

The efficiency of stormwater BMPs (how well a BMP or BMP system removes

pollutants or results in acceptable effluent quality) can be evaluated in a number of ways. 

An understanding of how BMP monitoring data will be analyzed and evaluated is

essential to establishing a useful BMP monitoring study. The different methods used to

date are explained in this section to illustrate historical approaches and provide context

for the method recommended in this manual (Effluent Probability Method), which is
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presented at the end of this section. The following table (Table 2.3) summarizes all of the 

methods examined by this guidance.
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Table 2.3: Summary of historical, alternative, and recommended methods for BMP water 

quality monitoring data analysis

Category Method Name Recommendation Comments

Historical 

Methods

Efficiency Ratio (ER) Not recommended as 

a stand-alone 

assessment of BMP 

performance. More 

meaningful when 

statistical approach is 

used.

Most commonly used method to 

date. Most researchers assume this 

is the meaning of “percent 

removal”. Typical approach does 

not consider statistical significance 

of result.

Summation of Loads 

(SOL)

Not recommended as 

a stand-alone 

assessment of BMP 

performance. More 

meaningful when 

statistical approach is 

used.

Utilizes total loads over entire 

study. May be dominated by a 

small number of large events. 

Results are typically similar to ER

method. Typical approach does not 

consider statistical significance of 

result.

Regression of loads

(ROL)

Do not use Very rarely are assumptions of the 

method valid. Cannot be 

universally applied to monitoring 

data.

Mean Concentration Do not use Difficult to “track” slug of water 

through BMP without extensive 

tracer data and hydraulic study. 

Results are only for one portion of 

the pollutograph.

Efficiency of Individual 

Storm Loads

Do not use Storage of pollutants is not taken 

into account. Gives equal weight to 

all storm event efficiencies 

Alternative 

Methods

Percent Removal 

Exceeding Irreducible 

Concentration or 

Relative to WQ 

Standards/Criteria

Not recommended –

May be useful in 

some circumstances 

Typically only applicable only for 

individual events to demonstrate 

compliance with standards.

Relative Efficiency Not recommended –

May be useful in 

some circumstances

Typically only applicable only for 

individual events to demonstrate 

how well a BMP perfoms relative 

to how well it would perform if it

“Lines of Comparative 

Performance©”

Do not use Spurious self-correlation. Method 

is not valid.

Multi-Variate and NonLinear ModelsPossible future use Additional development of 

methodology based on more 

complete data sets than are 

currently available.

Recommended 

Method

Effluent Probability 

Method

Recommended 

Method

Provides a statistical view of 

influent and effluent quality. 

This is the method recommended 

in this guidance manual. 

Benefits over other approaches 

that are described in this section 

of the Guidance.
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2.9.2.1 Historical Approaches 

A variety of pollutant removal methods have been utilized in BMP monitoring studies to 

evaluate efficiency. This section describes and gives examples of methods employed by

different investigators. Historically, one of six methods has been used by investigators to 

calculate BMP efficiency: 

• Efficiency ratio 

• Summation of loads

• Regression of loads

• Mean concentration

• Efficiency of individual storm loads

• Reference watersheds and before/after studies

Although use of each of these methods provides a single number that summarizes 

efficiency of the BMP in removing a particular pollutant, they are not designed to look at 

removal statistically, and thus, do not provide enough information to determine if the

differences in inflow and outflow water quality measures are statistically significant. 

Efficiency Ratio

Definition

The efficiency ratio is defined in terms of the average event mean concentration (EMC) of

pollutants over some time period:

average inlet EMC

average inlet EMC - average outlet EMC

average inlet EMC

average outlet EMC ER = 1− =

EMCs can be either collected as flow weighted composite samples in the field or

calculated from discrete measurements. The EMC for an individual event or set of field

measurements, where discrete samples have been collected, is defined as:
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∑

∑

=

=

= n

i

i

n

i

i i

V

V C

EMC

1

1

where,

V: volume of flow during period i

C: average concentration associated with period i

n: total number of measurements taken during event

The arithmetic average EMC is defined as:

m

EMC

m

j

∑ j

=

=

1

average EMC

where,

m: number of events measured

In addition, the log mean EMC can be calculated using the logarithmic transformation of 

each EMC. This transformation allows for normalization of the data for statistical

purposes.

( )

m

Log EMC

m

j

∑ j

=

=

1 Mean of the Log EMCs

Estimates of the arithmetic summary statistics of the population (mean, median, standard 

deviation, and coefficient of variation) should be based on their theoretical relationships

(Appendix A) with the mean and standard deviation of the transformed data. Computing

the mean and standard deviation of log transforms of the sample EMC data and then

converting them to an arithmetic estimate often obtains a better estimate of the mean of

the population due to the more typical distributional characteristics of water quality data. 

This value will not match that produced by the simple arithmetic average of the data. 

Both provide an estimate of the population mean, but the approach utilizing the logtransformed data tends to provide a better estimator, as it has been shown in various

investigations that pollutant, contaminant, and constituent concentration levels tend to be 

well described by a log-normal distribution (EPA 1983). As the sample size increases,

the two values converge. 
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Assumptions

This method:

• Weights EMCs from all storms equally regardless of relative magnitude of storm. 

For example, a high concentration/high volume event has equal weight in the average 

EMC as a low concentration/low volume event. The logarithmic data transformation

approach tends to minimize the difference between the EMC and mass balance

calculations.

• Is most useful when loads are directly proportional to storm volume. For work

conducted on nonpoint pollution (i.e., inflows), the EMC has been shown to not vary

significantly with storm volume. Accuracy of this method will vary based on the

BMP type.

• Minimizes the potential impacts of smaller/”cleaner” storm events on actual

performance calculations. For example, in a storm by storm efficiency approach, a

low removal value for such an event is weighted equally to a larger value. 

• Allows for the use of data where portions of the inflow or outflow data are missing,

based on the assumption that the inclusion of the missing data points would not

significantly impact the calculated average EMC.

Comments

• This method is taken directly from non-point pollution studies and does a good job

characterizing inflows to BMPs but fails to take into account some of the

complexities of BMP design. For example, some BMPs may not have outflow EMCs 

that are normally distributed (e.g., media filters and other BMPs that treat to a

relatively constant level that is independent of inflow concentrations).

• This method also assumes that if all storms at the site had been monitored, the

average inlet and outlet EMCs would be similar to those that were monitored.

• Under all circumstances this method should be supplemented with an appropriate

non-parametric (or if applicable parametric) statistical test indicating if the

differences in mean EMCs are statistically significant (it is better to show the actual

level of significance found, than just noting if the result was significant, assuming a

0.05 level).
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Example 

The example calculations given below are for the Tampa Office Pond using arithmetic

average EMCs in the efficiency ratio method.

Table 2.4: Example of ER Method results for TSS in the Tampa Office Pond

Period of Record Average EMC In Average EMC Out Efficiency Ratio

1990 27.60 11.18 59%

1993-1994 34.48 12.24 64%

1994-1995 131.43 6.79 95%

ER is rounded, but the other numbers were not (to prevent introduction of any rounding errors in the calculations)

Summation of Loads

Definition

The summation of loads method defines the efficiency based on the ratio of the

summation of all incoming loads to the summation of all outlet loads, or:

sum of inlet loads

sum of outlet loads SOL =1-

The sum of outlet loads are calculated as follows:

j

m

j

j

m

j

n

i

CiVi

 = EMC ⋅V











= ∑ ∑ ∑ =1 =1 =1

sum of loads

Assumptions

• Removal of material is most relevant over entire period of analysis. 

• Monitoring data accurately represents the actual entire total loads in and out of the

BMP for a period long enough to overshadow any temporary storage or export of

pollutants.

• Any significant storms that were not monitored had a ratio of inlet to outlet loads

similar to the storms that were monitored.
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• No materials were exported during dry periods, or if they were, the ratio of inlet to

outlet loads during these periods was similar to the ratio of the loads during the

monitored storms.

Comments

• A small number of large storms typically dominate efficiency.

• If toxics are a concern then this method does not account for day-to-day releases,

unless dry weather loads in and out are also accounted for. In many cases long-term 

dry weather loads can exceed those resulting from wet weather flows.

• Under all circumstances this method should be supplemented with an appropriate

non-parametric (or if applicable parametric) statistical test indicating if the

differences in loads are statistically significant (it would be better to show the actual

level of significance found, rather than just noting if the result was significant,

assuming a 0.05 level).

Example

The example calculations given in Table 2.5 are for the Tampa Office Pond using a mass 

balance based on the summation of loads.

Table 2.5: Example of SOL Method results for TSS in the Tampa Office Pond.

Period of Record Sum of Loads 

In (kg)

Sum of Loads 

Out (kg)

SOL Efficiency

1990 134.60 39.67 71%

1993-1994 404.19 138.44 66%

1994-1995 2060.51 130.20 94%

SOL Efficiency is rounded, but the other numbers were not (to prevent introduction of any rounding errors in the calculations)

Regression of Loads (ROL)

Definition

The regression of loads method as described by Martin and Smoot (1986) defines the

regression efficiency as the slope (b) of a least squares linear regression of inlet loads and 

outlet loads of pollutants, with the intercept constrained to zero. The zero intercept is

specified as an “engineering approximation that allows calculation of an overall

efficiency and meets the general physical condition of zero loads-in (zero rainfall) yield

zero loads-out”. The equation for the ROL efficiency is:
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Loadsin

Loads out Loads out = b • Loadsin = b −

The percent reduction in loads across the BMP is estimated as:

Loadsin

Loads out Percent Removal = 1− b = 1−

Due to the nature of stormwater event monitoring, it is rare that all of the assumptions for 

this method are valid, particularly requirements for regression analysis. The example

calculations and plots provided in this section are from one of the better studies available 

at the time this manual was written, and as can be seen from the ROL plots, the data does 

not meet the requirements for proper simple linear regression analysis.

Assumptions

• Any significant storms that were not monitored had a ratio of inlet to outlet loads

similar to the storms that were monitored. The slope of the regression line would not

significantly change with additional data.

• No materials were exported during dry periods, or if they were, the ratio of inlet to

outlet loads during these periods was similar to the ratio of the loads during the

monitored storms.

• The data is well represented by a least squares linear regression, that is:

o The data is “evenly” spaced along the x-axis.

o Using an analysis of variance on the regression, the slope coefficient is

significantly different from zero (the p value for the coefficient should

typically be less than 0.05, for example).

o A check of the residuals shows that the data meets regression requirements.

The residuals should be random (a straight line on probability paper) and the

residuals should not form any trend with predicted value or with time (i.e.,

they form a band of random scatter when plotted).
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Comments

• A few data points often control the slope of the line due to clustering of loads about

the mean storm size. Regressions are best used where data is equally populous

through the range to be examined. This is readily observed in the examples that

follow (See Figures 2.1 through 2.3).

• The process of constraining the intercept of the regression line to the origin is

questionable and in some cases could significantly misrepresent the data. It may be

more useful to apply the Regression of Loads method over some subset of the data

without requiring that the intercept be constrained to the origin. The problem with

this alternative approach is that a large number of data points are required in order to

get a good fit of the data. Often a meaningful regression cannot be made using the

data that was collected. This is well illustrated by the very low R2

 values in the table 

below. Forcing the line through the origin, in these cases, provides a regression line

even where no useful trend is present. 

• There is sufficient evidence that this first order polynomial (straight line) fit is not

appropriate over a large range of loadings. Very small events are much more likely to 

demonstrate low efficiency where larger events may demonstrate better overall

efficiency depending on the design of the BMP. 

Table 2.6: Example of ROL Method results for TSS in the Tampa Office Pond.

Period of Record Slope of 

Regression

Line

R

2

Percent Removal

1990 0.21 0.06 79%

1993-1994 0.18 -0.06 82%

1994-1995 0.05 0.46 95%

Percent Removal is rounded, but the other numbers were not (to prevent introduction of any rounding errors in the calculations)

The regressions used to arrive at the above slopes are given in Figures 2.1-2.3.
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0 5.0 10.0 15.0 20.0 25.0

LOAD IN (KG)

0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

LOAD OUT (KG)

Figure 2.1: ROL Plot for use in Calculating Efficiency for TSS using the Tampa Office 

Pond (1990) (Slope = 0.2135, R

2

 = 0.0563, Standard Error in Estimate =

2.176, one point is considered an outlier with a Studentized Residual of

3.304). All points were used for regression. Method is not valid due to

failure of simple linear regression assumptions.

0 10 20 30 40 50 60 70 80

LOAD IN (KG)

0

10

20

30

40

50

60

LOAD OUT (KG)

Figure 2.2: ROL Plot for use in Calculating Efficiency for TSS using the Tampa Office 

Pond (1993-1994) (Slope = 0.1801, R

2

 = -0.0562, Standard Error in

Estimate = 10.440, one point is considered an outlier with a Studentized

Residual of 13.206 and one point has a high Leverage of 0.323). All points

were used for regression. Method is not valid due to failure of simple linear 

regression assumptions.
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0 100 200 300 400 500 600 700

LOAD IN (KG)

0

10

20

30

40

LOAD OUT (KG)

Figure 2.3: ROL Plot for use in Calculating Efficiency for TSS using the Tampa Office 

Pond (1994-1995) (Slope = 0.0492, R2 = 0.4581, Standard Error in Estimate 

= 5.260, three points are considered outliers (Studentized Residuals of

3.724, 8.074, and –4.505, the point to the far right on the graph has large

Leverage (0.724) and Influence, Cook Distance = 36.144). All points were

used for regression. Method is not valid due to failure of simple linear

regression assumptions.

Mean Concentration 

Definition

The mean concentration method defines the efficiency as unity minus the ratio of the

average outlet to average inlet concentrations. The equation using this method is:

average inlet concentration

average outlet concentration Mean Concentration =1-

This method does not require that concentrations be flow weighted. This method might

have some value for evaluating grab samples where no flow weighted data is available or 

where the period of record does not include the storm volume.

Assumptions

• The flows from which the samples were taken are indicative of the overall event.
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Comments

• This method might be useful for calculating BMP’s effectiveness in reducing acute

toxicity immediately downstream of the BMP. This is due to the fact that acute

toxicity is measured as a threshold concentration value of a specific constituent in the 

effluent at or near the point of discharge. 

• This methods weights individual samples equally. Biases could occur due to

variations in sampling protocols or sporadic sampling (i.e., collecting many samples

close in time and others less frequently). The sample collection program specifics are 

not accounted for in the method and estimated efficiencies are often not comparable

between studies. 

• There is appreciable lag time for most BMPs between when a slug of water enters a

BMP and when the slug leaves the BMP. Unless this lag time is estimated (e.g.,

through tracer studies) results from this approach can be quite inaccurate. Results of

this method may be particularly difficult to interpret where lag time is ignored or not 

aggressively documented.

• This method does not account for storage capacity. Typically BMPs will have an

equal or lesser volume of outflow than of inflow. On a mass basis this affects

removal, since volume (or flow) is used with concentration to determine mass for a

storm event,

average inlet concentration

average outlet concentration 1-

C

1-

out ≥

in in

out

C V

V

where,

Cin: Concentration In 

Cout: Concentration Out

Vin: Volume In

Vout: Volume Out

In this respect, it is often more conservative (i.e., lower removal efficiency stated) to use 

a concentration rather than mass-based removal approach.

Efficiency of Individual Storm Loads

Definition 

The Efficiency of Individual Storm Loads (ISL) method calculates a BMP’s efficiency

for each storm event based on the loads in and the loads out. The mean value of these
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individual efficiencies can be taken as the overall efficiency of the BMP. The efficiency

of the BMP for a single storm is given by:

in

out

Load

Load Storm Efficiency = 1−

The average efficiency for all monitored storms is:

m

m

∑=

=

j 1

Storm Efficiencyj

Average Efficiency

where,

m: number of storms

Assumptions

• Storm size or other storm factors do not play central roles in the computation of

average efficiency of a BMP.

• Storage and later release of constituents from one storm to the next is negligible.

• The selection of storms monitored does not significantly skew the performance

calculation. 

Comments 

• The weight of all storms is equal. Large storms do not dominate the efficiency in this 

scenario. The efficiency is viewed as an average performance regardless of storm

size.

• Some data points cannot be used due to the fact that there is not a corresponding 

measurement at either the inflow or the outflow for a particular storm, and thus

efficiency cannot always be calculated on a storm-by-storm basis. This is not true for 

the ER method, however it is a limitation of the Summation of Load Method.

• Storm by storm analysis neglects the fact that the outflow being measured may have a 

limited relationship to inflow in BMPs that have a permanent pool. For example, if a 

permanent pool is sized to store a volume equal to the average storm, about 60 to 70

percent of storms would be less than this volume [from studies conducted using

SYNOP (EPA 1989)]. 
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Table 2.7: Example of Individual Storm Loads Method results for TSS in the Tampa 

Office Pond.

Period of Record Efficiency

1990 29%

1993-1994 -2%

1994-1995 89%

Summary and Comparison of Historical Methods

The table below shows the results of the various historical methods shown above for

calculating efficiency for the Tampa Office Pond. The four methods demonstrated (mean 

concentration method was not applicable to data available from the Tampa Office Pond

study) vary widely in their estimates of percent removal depending on the assumptions of 

each method as discussed above.

Table 2.8: Comparison of BMP efficiency methods.

Method

Design Efficiency

Ratio (ER)

Summation 

of Loads 

(SOL)

Regression of

Loads (ROL)

Efficiency of 

Individual Storms

1990 59% 71% 79% 29%

1993-1994 64% 66% 82% -2%

1994-1995 95% 94% 95% 89%

2.9.2.2 Other Methods and Techniques

“Irreducible Concentration” and “Achievable Efficiency”

As treatment occurs and pollutants in stormwater become less concentrated, they become 

increasingly hard to remove. There appears to be a practical limit to the effluent quality

that any BMP can be observed to achieve for the stormwater it treats. This limit is

dictated by the chemical and physical nature of the pollutant of concern, the treatment

mechanisms and processes within the BMP, and the sensitivity of laboratory analysis

techniques to measure the pollutant. This concept of “irreducible concentration” has

significant implications for how BMP efficiency estimates are interpreted. However, it is 

possible to get concentrations as low as desired, but in most cases achieving extremely

low effluent concentrations may not be practical (i.e., would require treatment trains or

exotic methods). For example, colloids are typically viewed as “never” being able to be

removed in a pond (settling is the primary mechanism for treatment in ponds), despite the 

fact that they could be further removed through chemical addition.

The term “irreducible concentration” (C*) has been used in stormwater literature

(Schueler 2000) to represent the lowest effluent concentration for a given parameter that
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can be achieved by a specific type of stormwater management practice. Schueler

examined the effluent concentrations achieved by stormwater management practices from 

published studies for several parameters. From this research, the following estimates of

“irreducible concentrations” for TSS, Total Phosphorous, Total Nitrogen, NitrateNitrogen, and TKN for all stormwater management practices were proposed:

Table 2.9: “Irreducible concentrations” as reported by Scheuler, 2000.

Contaminant Irreducible Concentration

TSS 20 to 40 mg/L

Total Phosphorous 0.15 to 0.2 mg/L

Total Nitrogen 1.9 mg/L

Nitrate-Nitrogen 0.7 mg/L

TKN 1.2 mg/L

Recent research (ASCE 2000) indicates that achievable effluent concentrations vary

appreciably between BMP types. For example, in many cases, well-designed sand filters

can achieve lower effluent concentrations of TSS than well-designed detention facilities

or grassed swales. However, sand filters have issues with long-term maintenance of flow 

treatment volumes. 

The typical approach to reporting the ability of a BMP to remove pollutants from

stormwater entails comparing the amount of pollutant removed by the BMP to the total

quantity of that pollutant. The concept of irreducible concentration, however, suggests

that in some cases it may be more useful to report the efficiency of the BMP relative to

some achievable level of treatment (i.e. express efficiency as the ability of the BMP to

remove the fraction of pollutant which is able to be removed by a particular practice.)

The following example illustrates this approach. Suppose that two similar BMPs have

been monitored and generated the following results for TSS:

Table 2.10: Example TSS results for typical ER Method

Percent TSS Removal Using Absolute Scale

BMP A BMP B

Influent Concentration 200 mg/L 60 mg/L

Effluent Concentration 100 mg/L 30 mg/L

Efficiency Ratio 50% 50 %

Clearly, the effluent from BMP B is higher quality than that from BMP A, however

comparing percent removals between BMPs alone would indicate that both BMPs have

an equal efficiency. Methods have been suggested for quantifying the dependence of

BMP efficiency on influent concentration. The following section presents one such

method advanced by Minton (1998).
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In order to account for the dependence of BMP efficiency on influent concentration,

Minton (1998) suggests a method of evaluating BMP efficiency that would recognize the 

relationship between influent concentration and efficiency. The relationship is

summarized as follows: 

Achievable Efficiency = (Cinfluent – Climit)/ Cinfluent

where,

Cinfluent : Influent Concentration of Pollutant; and

Climit : The lower attainable limit concentration of the BMP (e.g., “irreducible

concentration” or value obtained from previous monitoring of effluent

quality)

For example, if a BMP had a lower treatment limit of TSS at 20mg/L concentration, then 

at an influent TSS concentration of 100 mg/L, it would be assigned an equivalent

performance of 80%, while at an influent TSS concentration of 50 mg/L the equivalent

performance would be 60%. 

This method relies on the ability to determine the lower attainable limit concentration,

which is analogous to the “irreducible concentration” for a specific BMP, however

effluent quality is best described not as a single value, but from a statistical point of view 

(See the Effluent Probability Method).

The Achievable Efficiency may be useful in better understanding the results of the ER

method in cases where the influent concentration is lower than is typically observed. 

Alternately, a single factor (dubbed the Relative Efficiency here) can be used to report

how well a BMP is functioning during some period relative to what that BMP is

theoretically or empirically able to achieve (as defined by the Achievable Efficiency). 

As shown below, the Relative Efficiency can be found by dividing the Efficiency Ratio

by the Achievable Efficiency, thus yielding an estimate of how well the BMP performed 

relative to what is “achievable”.
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Relative Efficiency =

Efficiency Ratio [(C influent - C effluent)/C influent]

Achievable Efficiency =

[(C influent – C limit)/ C influent]

Or simplifying:

Relative Efficiency = (C influent - C effluent)/(C influent – C limit)

If applied to the example presented earlier in this section, the following results are 

obtained:

Table 2.11: Example TSS results for demonstration of Relative Efficiency approach.

BMP A BMP B

Influent Concentration 200 mg/L 60 mg/L

C limit 20 mg/L 20 mg/L

Effluent Concentration 100 mg/L 30 mg/L

Relative Efficiency 56% 75 %

For this example, the results indicate that BMP B is achieving a higher level of treatment 

than BMP A and this approach may be more useful as a comparative tool than the

Efficiency Ratio for some data sets. The Relative Efficiency for a BMP’s effectiveness is 

still influenced by influent concentration but less so than is the Efficiency Ratio. 

As C influent approaches C limit the Relative Efficiency goes to infinity, which is not a very

meaningful descriptor. However, if the influent concentration is near the “irreducible

concentration” for a particular pollutant, very little treatment should occur and C influent -

C effluent should approach zero. C effluent, at least theoretically, should always be higher

than C limit and the numerator of the equation should approach zero faster than the

denominator. If C influent is less than C limit, the Relative Efficiency approach should not

be used. As is always the case, any of the percent removal efficiency approaches

(including the Efficiency Ratio Method) should not be employed if there is not a

statistically significant difference between the average influent and effluent

concentrations.

If this method is used to represent data from more than one event (i.e., mean EMCs are

calculated) it should be supplemented with an appropriate non-parametric (or if

applicable parametric) statistical test indicating if the differences are statistically

significant (it would be preferred to show the actual level of significance found, instead

of just noting if the result was significant, assuming a 0.05 level).
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Percent Removal Relative to Water Quality Standards

From a practical or programmatic perspective, it may be more useful to substitute the

water quality limit for the “irreducible concentration” as a measure of how well the BMP

is meeting specific water quality objectives. A measure of efficiency can be calculated to

quantify the degree to which stormwater BMPs employed are meeting or exceeding state or 

federal water quality criteria or standards for the runoff they treat. 

Standards are enforceable regulations established within the context of an NPDES permit

or a TMDL and are usually specific to the receiving water. Water quality criteria are

more general guidelines expressed as constituent concentrations, levels, or narrative

statements, representing a quality of water that supports a particular beneficial use. 

By showing that stormwater is being treated to a level that is higher than standards require

or criteria recommend, a permitee may be able to demonstrate to regulators or stakeholders

that their current stormwater management practices are adequate for a particular constituent

of concern. The equation to calculate the Percent Removal Relative to Receiving Water

Quality Limits is as follows:

Percent Removal Relative to Receiving Water Quality Limits = 

(C influent - C effluent)/(C influent – C standard/criterion)

The following example illustrates the application of this approach for reporting efficiency:

Table 2.12: Example of percent removal relative to receiving water quality limits 

approach.

BMP A

Influent Concentration (EMC) 1.65 ug/l

C standard/criterion 0.889 ug/l

Effluent Concentration (EMC) 0.635 ug/l

Percent Removed Relative to Established WQ Limits 133 %

The results indicate that the BMP for the given event is meeting the water quality

standard or criterion for dissolved lead. In fact the BMP is functioning to remove in

excess of the amount needed to bring the influent concentration below the water quality

limit (as indicated in the example by a value greater than 100%). Use of this method is

only recommended for specific event analysis. As mentioned for previous analyses, if

this approach is taken for a series of events it should be supplemented with an appropriate 

non-parametric (or if applicable parametric) statistical test indicating if the differences

are statistically significant (it would be better to show the actual level of significance

found, than just noting if the result was significant, assuming a 0.05 level)
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“Lines of Comparative Performance©”

For many stormwater treatment BMPs, the efficiency of the BMP decreases as a function 

of the influent concentration. Methods have been recommended that integrate this

concept into efficiency evaluations. The “Lines of Comparative Performance©” (Minton 

1999) is one such method. 

In this method, plots of percent removal as a function of the influent concentration for

each storm are generated for each pollutant monitored. The results of these plots are

overlain on plots of data collected from studies of similar BMPs within a region. 

“Lines of Comparative Performance©” are generated for the data from similar BMPs

based on best professional judgment by examining the likely “irreducible concentration”

for a particular pollutant, the detection limit for that pollutant, and knowledge of expected 

maximum achievable efficiency for a BMP type.

This method has primarily been suggested as an approach to evaluate the efficiency of

innovative and “unapproved” stormwater technologies. “To be accepted, the

performance data points of an unapproved treatment technology must fall above and to

the left of the ‘Line of Comparative Performance©’.”

This approach has several major problems. The most significant flaw is the use of

“spurious” self-correlation. Plots such as those shown in Figures 2.4 through 2.6 can be

generated using random, normally distributed influent and effluent concentrations as seen 

below in Figure 2.7. As such, it is strongly recommended that this approach not be

employed in BMP monitoring evaluation studies. This approach may lead to overly

complicated analysis methodologies without providing additional useable information on 

BMP functionality. 

Figures 2.4-2.6 below show work conducted by Minton in the development of the

Achievable Efficiency approach.
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Figure 2.4: Removal Efficiency (ER Method) of TSS as a Function of Influent 

Concentration (Minton 1999)

Figure 2.5: Removal Efficiency (ER Method) of Total Phosphorous as a function of

influent concentration (Minton 1999)
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Figure 2.6: Removal Efficiency (ER Method) of Total Zinc as a Function of Influent

Concentration (Minton 1999)

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

0 100 200 300 400 500

Influent Concentration

Percent Removal

Figure 2.7: Percent removal as a function of influent concentration for randomly

generated, normally distributed influent and effluent concentrations. Any

number of similar charts can be generated from randomized data. 
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An alternate method which does not include the serious problems associated with the

“Lines of Comparative Performance©”, but presents relatively the same information can

be generated using a simple plot of effluent concentration as a function of influent

concentration with “rays” (or curves on a log plot) originating from the plot origin for

several levels of control (e.g., 0, 25, 50, 75, and 90%). The plot may need to be a log-log 

plot for data with a large range of values typical of stormwater monitoring data.

Multi-Variate and Non-Linear Models

Reporting efficiency as a percent removal that is calculated based on the difference

between influent and effluent concentrations will always make a BMP that treats higher

strength influents appear to be more efficient than one treating weaker influents if both

are achieving the same effluent quality. A more useful descriptor of efficiency would

take into consideration that weaker influents are more difficult to treat than concentrated

ones. A multi-variate equation that includes corrections to compensate for this

phenomena or a non-linear model may be worth considering for reporting efficiency. 

A model that approaches pollutant removal in a manner similar to the reaction rates for

complex physical and chemical batch and plug-flow processes may be useful. To date

calibration of such a model for all but the most elementary situations (e.g., settling of

solids in relatively simplistic flow regimes) is difficult given the complexity of the realworld problem. As more high quality data becomes available, other approaches to

evaluating BMP efficiency may become apparent.

Currently, effluent quality, as discussed below, is the best indicator of overall BMP

performance.

2.9.2.3 Recommended Method

The following method is recommended for use in analyzing new and existing monitoring 

studies.

Effluent Probability Method

The most useful approach to quantifying BMP efficiency is to determine first if the BMP 

is providing treatment (that the influent and effluent mean EMCs are statistically different 

from one another) and then examine either a cumulative distribution function of influent

and effluent quality or a standard parallel probability plot. 

Before any efficiency plots are generated, appropriate non-parametric (or if applicable

parametric) statistical tests should be conducted to indicate if any perceived differences in 

influent and effluent mean event mean concentrations are statistically significant (the

level of significance should be provided, instead of just noting if the result was

significant, assume a 95% confidence level). 

Effluent probability method is straightforward and directly provides a clear picture of the 

ultimate measure of BMP effectiveness, effluent water quality. Curves of this type are the 
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single most instructive piece of information that can result from a BMP evaluation study. 

The authors of this manual strongly recommend that the stormwater industry accept this

approach as a standard “rating curve” for BMP evaluation studies.

The most useful approach for examining these curves is to plot the results on a standard

parallel probability plot (see Figures 2.8-2.10). A normal probability plot should be

generated showing the log transform of both inflow and outflow EMCs for all storms for 

the BMP. If the log transformed data deviates significantly from normality, other

transformations can be explored to determine if a better distributional fit exists. Figures

2.8-2.10 show three types of results that can be observed when plotting pollutant

reduction observations on probability plots. The data was taken from the Monroe St. wet 

detention pond study in Madison, WI, collected by the USGS and the WI DNR. Figure

2.8 for suspended solids (particulate residue) shows that SS are highly removed over

influent concentrations ranging from 20 to over 1,000 mg/L. A simple calculation of

“percent removal” (ER Method) would not show this consistent removal over the full

range of observations. In contrast, Figure 2.9 for total dissolved solids (filtered residue)

shows poor removal of TDS for all concentration conditions, as expected for this wet

detention pond. The “percent removal” (ER Method) for TDS would be close to zero and 

no additional surprises are indicated on this plot. Figure 2.10, however, shows a wealth of 

information that would not be available from simple statistical numerical summaries,

including the historical analysis approaches described in this manual. In this plot, filtered 

COD is seen to be poorly removed for low concentrations (less than about 20 mg/L), but

the removal increases substantially for higher concentrations. Although not indicated on

these plots, the rank order of concentrations was similar for both influent and effluent

distributions for all three pollutants (Burton and Pitt 2001).

Water quality observations do not generally form a straight line on normal probability

paper, but do (at least from about the 10th to 90th percentile level) on log-normal 

probability plots. This indicates that the samples generally have a log-normal distribution 

as described previously in this document and many parametric statistical tests can often

be used (e.g., analysis of variance), but only after the data is log-transformed. These plots 

indicate the central tendency (median) of the data, along with their possible distribution

type and variance (the steeper the plot, the smaller the COV and the flatter the slope of

the plot, the larger the COV for the data). Multiple data sets can also be plotted on the

same plot (such as for different sites, different seasons, different habitats, etc.) to indicate 

obvious similarities (or differences) in the data sets. Most statistical methods used to

compare different data sets require that the sets have the same variances, and many

require normal distributions. Similar variances are indicated by generally parallel plots of 

the data on the probability paper, while normal distributions would be reflected by the

data plotted in a straight line on normal probability paper. (Burton and Pitt 2001)

Probability plots should be supplemented with standard statistical tests that determine if

the data is normally distributed. These tests, at least some available in most software

packages, include the Kolmogorov-Smirnov one-sample test, the chi-square goodness of

fit test, and the Lilliefors variation of the Kolmogorov-Smironov test. They are paired
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tests comparing data points from the best-fitted normal curve to the observed data. The

statistical tests may be visualized by imagining the best-fit normal curve data (a straight

line) and the observed data plotted on normal probability paper. If the observed data

crosses the fitted curve data numerous times, it is much more likely to be normally

distributed than if it only crosses the fitted curve a small number of times (Burton and Pitt 

2001).

Figure: 2.8: Probability plot for Suspended 

Solids 

Figure: 2.9 Probability plot for Total 

Dissolved Solids 

Figure: 2.10: Probability plot for Chemical 

Oxygen Demand 

(Originally by Burton and Pitt 2001)
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2.9.2.4 Reference Watershed Methods

Many BMPs do not allow for comparison between inlet and outlet water quality

parameters. In addition, it is often difficult or costly, where there are many BMPs being

installed in a watershed (e.g., retrofit of all catch basins), to monitor a large number of

specific locations. A reference watershed is often used to evaluate the effectiveness of a 

given BMP or multiple BMPs of the same type. The database allows for a watershed and 

all associated data to be identified for use as a reference watershed. One of the primary

reasons for using a reference watershed is that for some BMPs there is no clearly defined 

inlet or outlet point at which to monitor water quality. Such is the case with many nonstructural BMPs, porous pavements, and infiltration practices. 

The difficulty in determining the effectiveness of a BMP using a reference watershed

approach stems from the large number of variables typically involved. When setting up a 

BMP monitoring study, it is advantageous to keep the watershed characteristics of the

reference watershed and the test watershed as similar as possible. Unfortunately, finding

two watersheds that are similar is often quite difficult, and the usefulness of the data can 

be compromised as a result. In order to determine the effectiveness of a BMP based on a 

reference watershed, an accurate accounting of the variations between the watersheds,

and operational and environmental conditions is needed. The Database explicitly stores 

some of the key parameters required for normalization of watershed and environmental

conditions. 

The most obvious parameter used to normalize watershed characteristics is area. If the

ratio of land uses and activities within each watershed is identical in both watersheds then 

the watershed area can be scaled linearly. The loads found at each downstream

monitoring station for each event can be scaled linearly with area as well. Difficulty

arises when land use in the reference watershed is not found in the same ratio. In this

case, either the effects of land use must be ignored or a portion of the load found for each 

event must be allocated to a land use and then scaled linearly as a function of the area

covered by that land use. In many cases, the differences in land use can be ignored, (e.g., 

between parking lots with relatively small, but different unpaved areas). The effect of the 

total impervious area is relevant and should always be reported in monitoring studies. 

The ratio of the total impervious areas can be used to scale event loads. Scaling the loads 

based on impervious areas would be best used where the majority of pollutants are from

runoff from the impervious areas (e.g., parking lots), or the contaminant of interest results 

primarily from deposition on impervious surfaces, (e.g., TSS in a highly urban area).

Methods that attempt to determine BMP performance from poorly matched watersheds

yield poor results at best. As the characteristics of the two watersheds diverge, the effect 

of the BMP is masked by the large number of variables in the system; the noise in the

data becomes greater than the signal. 

The analysis of BMPs utilizing reference watersheds also requires incorporation of

operational details of the system, (e.g., frequency of street sweeping, type of device used, 

device setup). Monitoring studies should always provide the frequency, extent, and other 
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operational parameters for nonstructural BMPs. If the BMP is an alteration of the

frequency of a certain practice, the system can be viewed in two ways, (1) as a

control/test system, or (2) as a series of data aimed at quantifying the continuous effect of 

increasing or decreasing BMP frequency. In the first case, the BMP can be analyzed in a 

manner similar to other BMPs with reference watersheds. In the second case, the loads

realized at the monitoring stations need to be correlated with the frequency using some

model for the effectiveness of the practice per occurrence.

2.9.3 BMPs and BMP Systems

Overflow and bypassing of treatment BMPs affect the long-term performance of the

pollution control measure. Many types of BMP structures, such as detention or filtration

basins, are designed to treat specific volumes of stormwater runoff. Runoff volumes (or

flows) exceeding the designed storage volume or maximum flow rate are bypassed

untreated or partially treated. In order to accurately assess the long-term efficiency of the 

BMP system, the bypass flow needs to be taken into consideration. Ideally, a third flow

monitor should be installed to measure by-passed flow directly (Oswald and Mattison

1994).

If monitoring data is not cost effective or physically difficult to collect, estimates of

bypass can be made using inflow / outflow water balance calculations or modeled from

local rainfall data, watershed hydrology, and BMP system hydraulics. The volume

treated by a BMP for each event can be compared to a measured or modeled runoff 

volume yielding the volume of bypass. 

Estimates of BMP system efficiency should always be calculated for the entire BMP

system (in addition to the BMP). Mass balance checks should be performed in all cases to 

help verify monitoring data and/or modeled flow rates.
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3 Developing a BMP Monitoring Program

This chapter describes the steps involved in developing and implementing a monitoring

program to evaluate BMP effectiveness. Regardless of the scope and objectives, designing

a monitoring plan generally involves four phases:

Phase 1: Determine the objectives and scope of your monitoring program

Phase 2: Develop the monitoring plan in view of your objectives

Phase 3: Implement the monitoring plan

Phase 4: Evaluate and report the results of monitoring

The activities associated with each phase are listed below.

Phase 1: Determine Objectives and Scope

• Identify permit requirements and/or information needs

• Compile and review existing information (maps, drawings, results from prior sampling, 

etc.) relevant to permit requirements and/or information needs

• Develop monitoring program objectives and scope

Phase 2: Develop Monitoring Plan

• Select monitoring locations 

• Select monitoring frequency 

• Select parameters and analytical methods 

• Select monitoring methods and equipment

• Select storm criteria (i.e., size, duration, season)

• Develop mobilization procedures

• Prepare a quality assurance/quality control plan

• Prepare a health and safety plan

• Prepare a data management plan

Phase 3: Implement Monitoring Plan

• Install equipment (and modify channels, if applicable)

• Test and calibrate equipment

• Conduct training

• Conduct monitoring (collect samples)

• Conduct analyses (field and/or laboratory)
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Phase 4: Evaluate and Report Results

• Validate chemical data quality 

• Evaluate results

• Report the results

Several of the steps in developing a monitoring program are dependent on one another. 

Consequently, earlier steps may need to be revisited and refined throughout the planning

process. For example, if it is determined in Phases 2 or 4 that monitoring more storms is

needed to achieve objectives, revisiting the "select monitoring location" task and

selecting a lower number of sampling locations and/or a different analytical scheme may

be needed to keep within the schedule and budget. 

Determine Key Study Parameters

Key parameters of the monitoring project are determined using the information gathered

in the previous steps of the systematic planning process. Key study parameters include

site selection, number of monitored storm events and their temporal distribution,

characteristics of target storm events, types of samples (composite, grab, etc.), and

analytical constituents. The better these characteristics are understood, the more

efficiently the monitoring data can be collected (Caltrans 1997).

The planned number of sites and monitoring events are often constrained by fiscal

factors, such as the cost of sample collection and analysis. For this reason, the list of

analytical constituents is often considered in the early stages of project planning (see

Section 3.2.3), so that costs of the appropriate sample collection and analysis can be

factored into the expected cost per monitoring event. The analytical constituents are

often prescribed by regulatory or legal mandate.

3.1 Phase I – Determine Objectives and Scope of BMP Water Quality

Monitoring Program

It is particularly important that the objectives of a BMP monitoring program be clearly

stated and recorded. The process of writing them down generally results in careful

consideration being given to the possible options. Written objectives help avoid

misunderstandings by project participants, are an effective way of communicating with

sponsors, and provide assurance that the monitoring program has been systematically

planned. 

Studies of BMP performance are usually conducted to obtain information regarding one

or more of the following questions:
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• What degree of pollution control or effluent quality does the BMP provide under 

normal conditions?

• How does this performance vary from pollutant to pollutant?

• How does this normal performance vary with large or small storm events?

• How does this normal performance vary with rainfall intensity?

• How do design variables affect performance?

• How does performance vary with different operational and/or maintenance 

approaches?

• Does performance improve, decay, or remain stable over time?

• How does this BMP's performance compare with the performance of other 

BMPs?

• Does this BMP help achieve compliance with water quality standards?

Many BMP monitoring programs have been established to satisfy requirements prescribed

by permits to monitor the effectiveness of BMPs, but often the wording of such

requirements is vague. Local program-specific objectives are likely to provide the soundest 

basis for planning a BMP monitoring study.

A well-designed BMP monitoring program may help address specific monitoring

questions, thereby enabling better decisions regarding allocation of resources to address

stormwater quality issues. The ultimate use of the monitoring results should be kept in

mind throughout the monitoring program planning process. 

3.1.1 Monitoring and Literature Review to Assess BMP Performance

Typically, structural BMPs have well-defined boundaries and are relatively easy to monitor. 

Other types of BMPs, especially non-structural BMPs (e.g., street sweeping, catch basin

cleaning, sewer cleaning, illicit discharge elimination), are more difficult to monitor partly

because they tend to be geographically interspersed with many pollutant sources and can be 

influenced by many factors that cannot be "controlled" in an experimental sense. Some

non-structural BMPs, such as public education programs, oil recycling programs, and litter

control programs are virtually impossible to monitor or at best can be evaluated using trend

monitoring. 

It is assumed that many stormwater quality management programs will consider the

possibility of implementing some structural BMPs by experimenting with them on a pilot-
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scale by testing and demonstrating their performance, their costs, and their practical

implications before committing to larger-scale implementation. Programs that already have

structural BMPs in place may also test their performance for a variety of reasons. 

Before obtaining BMP performance data or establishing the objectives and scope of the

BMP monitoring program, it is useful to investigate other regional BMP monitoring

programs to learn from their successes and/or failures in implementing the BMP,

establishing their objectives and scope of their BMP monitoring program, and obtaining

meaningful results. This research will also provide some level of foresight in developing a

meaningful monitoring program that will produce results that will be useful in achieving

project goals and comparable to other programs.

Nationally, many stormwater programs need BMP performance data, and many are

planning or conducting performance monitoring. The concept of sharing monitoring results 

is very appealing but could be seriously constrained if pre-planning to maximize the chances 

of yielding comparable/compatible monitoring approaches, analytical protocols, and data 

management are not implemented. Some of the guidance provided in this manual and

referred to in literature citations is intended to facilitate exchanges of more transferable data 

among programs. 

As an example, in a review of the use of wetlands for stormwater pollution control (Strecker 

et al. 1992), a summary of the literature was prepared regarding the performance of wetland 

systems and the factors that are believed to affect pollutant removals. The studies reported

in the reviewed literature were inconsistent with respect to the constituents analyzed and the 

methods used to gather and analyze data. Several pieces of information were improperly

collected and recorded, which decreased their usefulness for evaluating the effectiveness of

stormwater wetlands. Furthermore, the lack of such basic information limits the

transferability of the studies' findings into better design practices. 

The technical literature has many reports of monitoring programs to evaluate BMP

performance. Those that address conceptual and strategic aspects of monitoring (e.g.,

Strecker 1994; Urbonas 1993) could be of particular value during the planning stage. In

addition, EPA and ASCE’s Urban Water Resources Research Council have compiled a

National Stormwater Best Management Practices Database (ASCE 1999) (on the world

wide web at http://www.bmpdatabase.org/). The purpose of this effort is to develop a

more useful set of data on the effectiveness of individual BMPs used to reduce pollutant 

discharges from urban development. Review of the protocols established for the database 

is useful in determining what and how information should be collected.

It is also valuable to review the monitoring methods and findings of other reported programs 

because they may contain transferable concepts (or even data). In considering the use of

data collected elsewhere, critical attention must be given to differences that might lead to

erroneous conclusions (e.g., weather, soil types, role of specific sources of pollutants). 

Particular care should be taken to avoid errors that are often introduced by assuming (rather 

than determining) that certain pollutants are associated with certain sediment fractions. 
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These associations of pollutants with particles are very important (in fact they are the reason 

why most BMPs are effective), but they vary dramatically from place to place and must be

determined based on careful local studies of relevant factors. When reviewing data from

relatively early studies, it is important to remember that state of the art of analyses has

advanced considerably in the past decade or so. For example, many data entries that report

"non-detect" may not be relevant.

3.1.2 Monitoring to Assess Compliance with Surface Water quality criteria

A main objective of BMP monitoring is to determine if the BMP helps reduce

concentrations of constituents of concern and therefore achieves compliance with water

quality criteria set forth by state and federal regulations.

Water quality standards may include bacteria, dissolved oxygen, temperature, pH,

turbidity, and toxic organic and inorganic compounds in marine and freshwater bodies. 

The water quality standards for toxic compounds (e.g., metals, pesticides) are intended to 

protect aquatic organisms, terrestrial animals, and humans who drink the water and/or

consume shellfish and fish from the waterbody. In addition, the water quality bacterial

standards are intended to guard against human health risks associated with recreational

activities such as swimming, wading, boating, fishing, and shellfish consumption.

State water quality standards often include the federal water quality criteria for the

protection of human health and aquatic life (40 CFR 131.36). Federal water quality

criteria may include a number of additional compounds not listed in state water q

uality standards.

Note that water quality criteria are guidelines, whereas water quality standards are

enforceable regulations. In this section, water quality criteria are used to encompass both 

state standards and the federal guidelines. 

There are two general categories of water quality criteria: aquatic (or marine) criteria, and 

human health criteria. These are summarized below.

3.1.3 Criteria for the Protection of Aquatic/Marine Life

Criteria for the protection of aquatic and marine life were developed based on laboratory

toxicity tests of representative organisms using test solutions spiked with pollutants to 

simulate exposure. In order to apply the results of these tests, EPA has classified aquatic 

life standards as either "acute" or "chronic" based on the length of time the organisms are 

exposed to the listed concentrations.

Criterion maximum concentrations (CMC - acute) are intended to protect against shortterm exposure. Criterion continuous concentrations (CCC - chronic) are designed to

protect against long-term exposure. In deriving the acute criteria, the laboratory
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organisms were exposed to pollutant concentrations for 24 to 48 hours. EPA suggests

one hour as the shortest exposure period, which may cause acute effects and recommends 

the criteria be applied to one-hour average concentrations. That is, to protect against

acute effects, the one-hour average exposure should not exceed the acute criteria. EPA

derives chronic criteria from longer term (often greater than 28-day) tests that measure

survival, growth, reproduction, or in some cases, bioconcentration. For chronic criteria, 

EPA recommends the criteria be applied to an averaging period of 4 days. That is, the 4-

day average exposure should not exceed the chronic criteria.

water quality criteria for aquatic life were developed based on an allowable exceedance

frequency of once every three years, based on the theory that an ecosystem is likely to

recover from a brief water quality exceedance, provided it does not occur too often. 

3.1.4 Human Health

Water quality standards for the protection of human health contain only a single

concentration value and are intended to protect against long-term (chronic) exposure. For 

carcinogenic compounds, a lifetime exposure over 70 years is generally used to calculate

the criteria. For non-carcinogens, exposure periods are more chemical specific and

depend on the particular endpoint and toxic effect. 

EPA has defined two levels of protection for human health criteria. The first criteria

were derived based on cumulative risks associated with drinking water and eating

organisms that live in the water. The criteria for carcinogenic compounds are the

calculated water-column concentrations that would produce a one in a million (10-6) 

lifetime cancer risk if water were consumed by humans and a given amount of organisms, 

like fish or shellfish, living in that water was eaten every day. The second set of criteria 

is based on consumption of organisms alone (the water is not consumed by humans). 

These standards apply to saltwater or other water that is not a drinking water source but

does support a fishery, and that is used as food. The standard for carcinogenic

compounds in the consumption of organisms only criteria is the calculated water

concentration that would produce a one in a million (10-6) lifetime cancer risk if a person 

were to consume a given amount of fish or shellfish from that waterbody (without

drinking the water).

3.1.5 Application of Water quality criteria to Stormwater

The water quality criteria are intended to protect the beneficial uses of streams, lakes, and 

other receiving water bodies. Most of the man-made conveyances within a near-highway 

stormwater drainage system do not support these beneficial uses. Thus, monitoring to

assess compliance with water quality criteria is usually conducted in a receiving water

body (rather than in the stormwater conveyance system that discharges into it) in order to 

provide a direct measure of whether the beneficial uses of the waterbody are impaired or 

in jeopardy.
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Direct comparisons between stormwater quality and the water quality criteria should be

interpreted with caution because the effects of receiving water hardness levels do not

account for mixing and dilution in the receiving waters or for such comparisons on heavy 

metals. This is especially true when the stormwater discharge is very small relative to the 

receiving waterbody. 

The variable nature of stormwater quality further complicates comparison to water

quality standards. Stormwater quality varies both between and during storm events, so it 

is very difficult to extrapolate data from one storm to another or to generate statistically

representative data for all types and combinations of storms. 

In spite of the limitations mentioned above, comparisons between stormwater quality and 

water quality standards can provide valuable information for stormwater management. 

Water quality standards can be used as screening criteria, or "benchmarks," for assessing

stormwater quality problems and establishing management priorities. Direct comparisons 

with the water quality criteria can over-estimate the potential impact of the stormwater

discharges on the receiving water bodies because mixing and dilution are not taken into

account. However, the relative frequency and magnitude of water quality standards

exceedances within storm sewer systems can help prioritize additional investigations

and/or implementation of control measures. Frequent large exceedances are a clear

indication that further investigation and control measures are warranted. Marginal or

occasional exceedances are more typical and more difficult to interpret.

3.1.6 Groundwater and Sediment Standards

In addition to surface water quality standards, stormwater discharges may affect

compliance with standards for groundwater quality and/or marine sediment quality. 

However, stormwater monitoring is typically of limited value with regard to assessing

compliance with groundwater and/or sediment quality standards. Compliance with the

groundwater standards is generally assessed through groundwater monitoring (rather than 

stormwater monitoring) because stormwater quality is likely to change substantially

while percolating through soils, and the extent of the change is very difficult to predict

without a great deal of site-specific information. Similarly, compliance with sediment

quality standards is generally assessed through sediment monitoring within receiving

water bodies. This is because numerous storms would need to be monitored in order to

develop useful estimates of total annual sediment loads, and the particulate portion of

each sample would need to be divided into particle size fractions prior to chemical

analysis to allow even a qualitative evaluation of potential sediment transport/deposition.

For these reasons, this manual does not address stormwater monitoring to assess

compliance with groundwater or sediment quality standards. 

3.1.7 Scope of Work for BMP Monitoring Program

Once monitoring objectives have been defined, the scope of the monitoring program must 

be determined. It is important to balance information needs with the resources available, 
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and to consider alternative means for obtaining information. To that end, consider the

following:

• How accurate or representative do the monitoring results need to be in order to 

support forthcoming management decisions?

If objectives include determination of stormwater quality trends or evaluation of BMP

effectiveness, numerous storms may need to be monitored in order to account for the

variability inherent in stormwater quality data. It can be difficult and expensive to obtain 

truly definitive stormwater data. For example, one of the City of Fresno's monitoring

programs (15 storms per year) has a 20% probability of detecting a 20% change in

stormwater quality at a confidence level of 95%. This monitoring program was expected 

to cost about $1.55 million over 10 years, which was about 21% of Fresno's total budget

for stormwater management during that period. To attain an 80% probability of detecting 

a 20% change at a 95% confidence limit, the monitoring cost would have risen to about

$5.84 million, or 41% of the total stormwater management budget (Harrison 1994). 

Note that the BMPs necessary to reduce stormwater contamination from built-out areas

by 20% would probably be costly and challenging to implement. Cave and Roesner

(1994) estimated that typical non-structural BMPs are likely to result in stormwater

pollutant reductions on the order of 5%-10%, while structural measures may reduce some 

stormwater pollutants by 50%-90%. They suggested that a fully implemented municipal

stormwater management program is likely to result in pollutant load reductions of 25% or 

less for built-out areas. This number, however, has been cited by others to be closer to

40% (Bannerman 2001).

Devoting large amounts of time and money to achieve a high level of accuracy may not

be the best use of stormwater program resources. It might be more cost effective to

spend less on trend monitoring and more on source identification, sediment monitoring,

and/or control measures. In some cases, a simple, screening-type monitoring program

may be sufficient to meet needs. 

• Are sufficient staff and financial resources available to obtain the needed information 

at the desired level of accuracy? If not, can additional resources be obtained?

This is a critical consideration. BMP monitoring is generally expensive and timeconsuming. This question can be addressed by developing an overview of monitoring

required and reviewing general cost information of other programs. 

In assessing personnel resources, consider staff size, technical background, physical

condition, and ability (and willingness) to respond to storm events with little advance

notice. These factors are discussed below. 

Staff Size. Few organizations can afford to have many personnel whose sole

responsibility is stormwater monitoring. In most cases, monitoring duties are assigned to 
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certain people in addition to their regular responsibilities. Back-ups are needed in case

the designated personnel are sick, on vacation, or otherwise unavailable when a storm

monitoring event occurs. The assigned people must be able and willing to drop what they 

are doing and mobilize for a storm event on short notice. In some organizations,

personnel are not allowed to perform work that is not specified in their job descriptions. 

Insurance and liability may also be considerations. Because of these staffing issues,

some agencies elect to hire contractors to perform monitoring.

Technical Expertise. Some technical expertise is needed to properly conduct monitoring, 

especially if automated equipment is used. Special training is required for any personnel 

that enter confined spaces, such as manholes, to collect samples. In addition, the person

directing a monitoring program should be familiar with how the results will be used, so

that effective decisions are made regarding storm selection, when to cancel a monitoring

event, etc. 

Physical Condition/Health. Stormwater monitoring can be physically demanding. 

Monitoring personnel may be required to work in slippery or otherwise challenging

conditions at night. 

Ability to Respond to Storm Events. Storms often occur outside of normal working

hours when it is more difficult to contact and mobilize monitoring personnel. 

If resources are not sufficient to sample enough storms and/or enough locations to meet

tentatively identified program objectives, monitoring program objectives and scope

should be scaled back until they are commensurate with resources. This can sometimes

be accomplished by using a phased approach where only one or two areas or questions

are addressed at a time so that useful results can be obtained within budget limitations. 

Supplementing existing resources should also be considered. It may be worthwhile to

contact neighboring municipalities or facilities to find out if they are willing to pool their 

resources in order to fund a joint BMP monitoring program. If objectives cannot be met

with the available resources, possible alternatives to stormwater monitoring should be

considered (discussed below), or monitoring resources should be allocated to additional

pollution control measures.

• Can some of the information needed be obtained without conducting BMP

monitoring?

Because of the typically high cost of BMP monitoring, it may be desirable to evaluate

alternative means for addressing some information needs (assuming that BMP monitoring 

is not required to comply with a permit). Depending on the situation, sediment sampling, 

biological sampling, and/or visual surveys of the stormwater conveyance system may be

cost-effective alternatives to stormwater quality monitoring. Literature reviews may also 

help address some stormwater management issues.

• Who is going to use the monitoring data and what is the intended use?
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Develop specific monitoring objectives and scope based on answers to these questions. 

At this point, the objectives should still be considered flexible because they may need to

be re-considered and revised as the monitoring program is developed. 
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3.1.8 Information Needs to Meet Established Goals of BMP Monitoring

Generally, the more information that is available, the easier it is to design a practical

monitoring program. For BMP monitoring programs, compile and review the following

information, if available:

• Results from prior surface water and groundwater quality studies, other BMP

monitoring studies in the local area, sediment quality studies, aquatic ecology

surveys, dry weather reconnaissance, etc.

• Drainage system maps.

• Land use maps (or general plan or zoning maps).

• Aerial photographs.

• Precipitation and streamflow records.

• Reported spills and leaks.

• Interviews with public works staff.

• Literature on design of structural BMPs to understand functionality and pollutant

removal processes.

For BMPs monitored in industrial areas, the following information may also be relevant:

• BMP performance data for similar industries in region.

• Facility map(s) showing locations of key activities or materials that could be exposed 

to stormwater.

• Lists of materials likely to be exposed to stormwater.

• Reported spills and leaks.

• Interviews with facility staff and others who are knowledgeable about the facility.

In addition to gathering information about the study area and BMP design, some

forethought should be given to the expected data characteristics and subsequent data

analysis methods in order to optimize collection of data within the limitations of the

proposed study and ensure that useful results will be provided to fulfill study objectives

(Caltrans 1997).

Essential data characteristics include the type of data to be collected (e.g., constituents

and concentrations), the variables affecting the data (e.g., antecedent conditions, rainfall

intensity, site type and location) and the expected variability of the data (derived from

previous studies when available). Statistical techniques such as power analysis can then

be used to determine key study parameters, such as the number of monitoring locations

and storm events to be monitored (Caltrans 1997).

Prior to the initiation of environmental sampling, a strategy should be developed for

analysis of the data, directed to answering the specific study questions. The selected data 

analyses technique(s) may influence the types and quantities of data required to satisfy
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study objectives. The analysis methods applied to data collected for BMP evaluations or 

characterization studies typically involve straight-forward statistical operations. 

3.2 Phase II – Develop BMP Monitoring Plan

3.2.1 Recommendation and Discussion of Monitoring Locations

The number of locations to be monitored depends on program objectives, permit

requirements (if applicable), the size and complexity of the drainage basin(s), and the

resources (time, personnel, funds) allocated to monitoring. In addition, the frequency of

sampling at each location must be considered. Depending on objectives, resources, and

logistical considerations, many locations may be sampled infrequently, or fewer locations 

more frequently. The former approach is generally better for evaluating place-to-place 

variability; the latter approach is generally better for evaluating storm-to-storm variability 

and for characterizing the monitoring location more accurately. If the effectiveness of a

specific structural BMP needs to be evaluated, monitoring locations should be located

immediately upstream and downstream of the structure. 

In general, choose monitoring sites that facilitate representative sampling and flow

measurement. Consider the criteria listed below in the selection of monitoring sites:

• The contributing (upgradient) catchment should be completely served by a separate

storm drain system or, if it is served by a combined sewer system, carefully consider

the possibility that stormwater samples would be contaminated by sanitary sewage.

• The storm drain system should be sufficiently well understood to allow a reliable

delineation and description of the catchment area (e.g., geographic extent,

topography, land uses).

• For monitoring stations that will be used to measure flow in open channels, the flow

measurement facilities need to be located where there is suitable hydraulic control so 

that reliable rating curves (i.e., stage-discharge relationships) can be developed. In

other words, the upstream and downstream conditions must meet the assumptions on

which the measurement method is based. 

ß Where possible, stations should be located in reaches of a conveyance where flows

tend to be relatively "stable" and "uniform" for some distance upstream

(approximately 6 channel widths or 12 pipe diameters), to better approach "uniform"

flow conditions. Thus, avoid steep slopes, pipe diameter changes, junctions, and

areas of irregular channel shape due to breaks, repairs, roots, debris, etc.
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• Locations likely to be affected by backwater and tidal conditions should be avoided

since these factors can complicate the reliable measurement of flow and the

interpretation of data. 

• Stations in pipes, culverts, or tunnels should be located to avoid surcharging (pressure 

flow) over the normal range of precipitation.

• Stations should be located sufficiently downstream from inflows to the drainage

system to better achieve well-mixed conditions across the channel and to favor the

likelihood of "uniform" flow conditions.

• Stations should be located where field personnel can be as safe as possible (i.e., 

where surface visibility is good and traffic hazards are minimal, and where

monitoring personnel are unlikely to be exposed to explosive or toxic atmospheres).

• Stations should be located where access and security are good, and vandalism of

sampling equipment is unlikely.

• Stations should be located where the channel or storm drain is soundly constructed.

• If an automated sampler with a peristaltic pump is to be used, and the access point is a 

manhole, the water surface elevation should not be excessively deep (i.e., it should be 

less than 6 meters, or 20 feet, below the elevation of the pump in the sampler, and

preferably less than 4.5 meters or 15 feet deep).

• If automated equipment is to be used, the site configuration should be such that

confined space entry (for equipment installation, routine servicing, and operation) can 

be performed safely and in compliance with applicable regulations.

Each potential sampling station should be visited, preferably during or after a storm to

observe the discharge. A wet-weather visit can provide valuable information regarding

logistical constraints that may not be readily apparent during dry weather. 

Integration of BMP Monitoring into a Municipal Monitoring Program

In most cases, it is not practical to monitor water quality at every BMP within a

municipality. Therefore, most municipal monitoring programs are designed to yield

estimates of effluent water quality for other similar BMPs by extrapolating data collected 

at a small number of locations.

Many municipal stormwater monitoring programs use stations that monitor relatively

small, homogeneous land use catchments (so called "single land use" or upland stations). 

Data from a study site may then be extrapolated to other catchments within the project

area that are thought to have similar sources and pollutant-generating mechanisms. This
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approach may also be useful for BMP monitoring studies. However, extrapolations

should be interpreted with caution because it is difficult to ascertain the degree to which

catchments and BMP functionality are truly similar. Also, previous studies have shown

that stormwater quality within a given land use category can vary considerably; thus, the

correlation between land use and stormwater quality, and thus the utility of a particular

BMP, may not be as strong as is typically assumed. 

Other municipal programs use stations that sample relatively large catchments

representing a composite of land uses. These stations are typically located in streams or

other stormwater conveyances at the lower end of a watershed and are sometimes

referred to as "mixed land use" stations or "stream stations." If possible, choose stream

stations that receive runoff from catchments with a land use composition similar to that of 

the project area as a whole. This will make it easier to apply BMP monitoring results to

similar watersheds. A geographic information system (GIS) can be very helpful in

characterizing land uses and identifying stormwater monitoring locations. 

Care must be taken to locate flow measurement and sampling sites in places that are likely

to yield good data over diverse operational conditions. For performance monitoring

approaches that are intended to compare changes in pollutant loads (i.e., “loads in” versus

“loads out” of the BMP), it is especially important to use accurate flow measurement

methods and to site the points of measurement at locations that maximize the attainment of

credible data (see Section 3.2.1). The added cost of a weir or flume, as opposed to less

sophisticated flow measurement methods, is almost always worthwhile because

measurement errors propagate through various aspects of the analysis. Propagation of errors 

due to inaccurate measurement is discussed in detail in Section 3.2.4.3. 

It is often difficult to identify large, homogeneous land use catchments that satisfy all of

the above criteria. As a result, compromises will typically need to be made. Refer to

basic texts on hydraulics and flow measurement and the instructions provided by

monitoring equipment manufacturers to guide judgment.

Sampling from a Well Mixed Location

The location of a permanent sampling station is probably the most critical factor in a

monitoring network that collects water quality data. If the samples collected are not

representative of the water mass, the frequency of sampling as well as the mode of data

interpretation and presentation becomes inconsequential. The following paragraphs

describe the theory of mixing within a river cross-section, which is applicable to

stormwater flows within stormwater conveyance systems. Typically these calculations

are not needed for stormwater monitoring design, but they are presented here to bring

attention to the need to be aware of mixing problems, particularly in wide conveyances.

(Saunders 1983)

The representativeness of a water quality sample is a function of the uniformity of the

sample concentrations in a river’s cross sectional area. Wherever the concentration of a
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water quality variable is independent of depth and lateral location in a river’s cross

section, the river at that point is completely mixed and could serve as a desirable

sampling location (Saunders 1983).

Well mixed zones in a river for representative water quality sampling can be defined,

given that several assumptions will apply. By assuming that a pollutant distribution from 

an instantaneous point source is normally distributed on both the lateral and vertical

transect and applying classical image theory, a theoretical distance from an outfall to a

well mixed zone in a straight uniform river channel is a function of 1) mean stream

velocity, 2) location of the point source and 3) the mean lateral and vertical turbulent

diffusion coefficients (Saunders 1983).

There are several models available that are functions of the mixing coefficients, which

have been shown to apply for predicting a zone of relatively complete mixing. Ruthven

(1971) derived an expression for a mixing distance utilizing the solution to the steadystate, two-dimensional advection and dispersion equation. Assuming that complete

vertical mixing is assured in a relatively short distance, he established a relationship from 

the two-dimensional solution to predict the mixing distance to a point where the

concentration variation in the cross section does not exceed ten percent. The approach

taken by Ruthven is shown in the following equation:

Dy

w u

L

2

≥ 0.075 Equation 3.1

where,

L: mixing distance

w: width of channel 

u: mean stream velocity 

Dy: lateral turbulent diffusion coefficient 

The distance needed for complete mixing using the above approach results in great

distances for most situations. In addition, many upstream discharges normally exist and it 

is rarely possible to get far enough below all of them. Because of the distance required

for complete mixing, there is often a need to composite samples across wide streams. 

Extensive discussion on this subject can be found in Fischer et al. (1979). 

3.2.1.1 Upstream

Monitoring stations established upstream of a BMP can give results that reveal the

influent concentration or load of pollutants before they flow through the BMP. Upstream 

water quality is indicative of concentrations and pollutant loads that would be observed

downstream if no BMP were implemented. It is important to monitor only waters that

flow into the BMP to be able to use the resultant data to compare upstream water quality
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with downstream locations. Upstream monitoring locations can also be useful to

determine bypass water quality. Where bypass is present, accurate flow measurement is

highly important. Where sufficient funds are available and the physical layout of the

control structures allow, bypass and flow to the BMP should be monitored directly. In

situations where direct measurement is not practical, modeling of bypass flows can be

substituted, particularly where the hydraulics of the bypass structure are well known or

can be calibrated to flow rates. Typically a mass balance approach is used to model

bypass flow rates and volumes.

Upstream monitoring stations should be located far enough away from the BMP to ensure 

that samples are independent of the BMP. Immediately upstream from a BMP,

contributing runoff could be affected by backflow, slope, vegetation, etc. Upstream

monitoring should be representative of conditions that existed before the BMP was

implemented.

3.2.1.2 Downstream

Monitoring stations established downstream of a BMP can indicate water quality of flows 

that are treated by the BMP. Downstream monitoring is essential for establishing:

• That the BMP provides a measurable and statistically significant change in water

quality.

• That the BMP provides effluent of sufficient quality to meet water quality criteria.

• A comparison of effluent concentrations with similar BMPs to determine if the BMP

is achieving typical effluent water quality. 

Monitoring stations should be located immediately downstream so that BMP effluent is

sampled before it is introduced into the receiving waters or is exposed to factors that may

affect constituent concentrations. Where bypass is present and one wants to understand

the efficiency of the BMP in addition to the BMP system, it is important to monitor water 

quality of the bypass flows and the effluent separately. In some cases where influent

water quality is not expected to be appreciably different than bypass water quality,

upstream data may be used to determine water quality. This approach does not, however, 

obviate the need for accurate estimates of bypass flow rates and/or volumes from

monitoring or flow modeling. In some cases, bypass flows may be very difficult to

separate from treated effluent (e.g., in hydrodynamic devices). 

3.2.1.3 Intermediate Locations

BMPs are often designed as a group of devices or chambers that target specific processes. 

For example, a filter might have a settling chamber to quickly remove large settlable

solids before flowing into the filter media chamber. A treatment train approach is

sometimes taken to combine various BMPs in order to maximize removal of specific

constituents. Intermediate monitoring locations in the interior of the BMP are useful for
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investigating how various sections of the BMP are working and establishing mid-BMP 

concentrations. Monitoring stations are also useful in between treatment train BMPs to

assess effectiveness of each individual BMP in addition to monitoring

upstream/downstream stations to determine overall BMP efficiency. 

Intermediate monitoring locations should be located either interior to the BMP or in

between BMPs linked in a treatment train. For interior monitoring, such as in the middle 

of a wetland or detention pond, stations should be established in a location that is

representative of the BMP. For example, monitoring within a wetland should be done in

the middle section, where the slopes, vegetation, channel width, etc., are uniform and

similar to the rest of the wetland, avoiding any microcosms of unique vegetation, basins,

or slopes. To monitor in between treatment train BMPs, stations should be established to 

capture effluent from the upstream BMP or inflow to the downstream BMP, or both. 

Monitoring should not be conducted in a place where backflow or mixing is occurring, as 

these processes do not allow for isolated sampling of direct BMP discharge or inflow. 

During high flow conditions, this may be difficult because many BMPs overflow,

reducing the distinction and separation between BMPs. Intermediate treatment train

BMP monitoring stations need to be carefully evaluated to determine if samples taken

during high flows are representative of water quality of flow between the BMPs and not

backflow or some other phenomena.

3.2.1.4 Rainfall

Rainfall monitoring can be an essential piece of the monitoring puzzle. Rainfall data may 

help determine when to start sampling as well as provide information to calculate rainfall 

characteristics such as intensities. The importance of accurate rainfall data, however,

decreases as the accuracy and reliability of flow information is improved. Rainfall data

are relatively inexpensive to collect and therefore, even in cases where rainfall data may

not be required for a detailed analysis of BMP efficiency, it is usually worthwhile to

monitor for validation of flow monitoring results.

Site Proximity

Rainfall gauges should be established as close as possible to the monitoring stations. In

many regions, rainfall is highly variable within a small area due to orographic effects,

elevation, and proximity to water bodies. The US Geological Survey, National Weather

Service, and many municipalities have networks of rain gauges, some with real-time rain 

data available over the Internet. These established stations are convenient to use if they

are in close proximity to the monitoring site, or as a general estimate of rainfall if they are 

not in close proximity to the monitoring site.

Rain gauges may need to be installed near the site to obtain accurate rainfall data where 

established gauges are not available. Proper installation and maintenance of the rain

gauge is as important as gauge proximity to the monitoring site. Installation of rain
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gauges is often a straightforward matter. Manufacturers provide guidelines on the

appropriate mounting of the devices. The main concerns during installation are:

• Leveling the device.

• Making sure that vegetation (trees) or structures are not obstructing rainfall.

• Providing enough height above the ground to prevent vandalism.

• Locating the rain gauge in close proximity to other monitoring equipment to provide

required connections for recording of rainfall depths and/or representative records.

Number of Gauges

The number of precipitation gauges installed in a system directly affects the quality of

precipitation data. Generally, the higher the number of precipitation gauges, the better

the estimate of precipitation amounts. Locating a gauge at each monitoring site for small

catchments is imperative, because local variations in total rainfall and rainfall intensity

can have significant effects on runoff when the watershed is minimal in size. Nearby

locations may not be useful in estimating rainfall at the actual site. 

In addition to the network of rain gauges accessed for monitoring, it is also useful to

install manual rain gauges at the monitoring site to check accuracy, consistency and

proper functioning among different gages. It is not difficult to discover a gauge that

produces different rainfall data than that observed at the site due to the location of the

gauge at a different elevation or microclimate, improper installation or placement, or

natural interferences (birds resting on the gauge, for example). 

3.2.1.5 Groundwater

Although most BMPs are designed to treat surface water runoff, some BMPs also

promote groundwater infiltration. BMPs incorporating infiltration should not process

large quantities of certain constituents (petroleum products, pesticides, solvents, etc.) that 

could be mobilized in groundwater or pose a drinking water hazard to those who rely on 

downstream wells.

Groundwater monitoring wells should be established if contamination of groundwater is

suspected. Groundwater flow, direction and elevation as well as soil types should be

established before monitoring sites are chosen. Monitoring stations should be located

sufficiently down gradient from the BMP where infiltrated water from the BMP is

accessible. A series of monitoring stations could be established: a station upstream of the 

BMP, one a short distance downstream from the BMP, another a longer distance

downstream, and another even further downstream from the BMP. This will indicate if

there is any contribution of constituents to the groundwater from the BMP, and where
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there is a contribution, if the concentrations decrease with increasing distance from the

BMP.

3.2.1.6 Sediment Sampling

Many constituents either settle out of the water column or prefer not to be in the water

column (due to hydrophobicity) and become incorporated in the sediment. Sediment can 

store significant amounts of certain constituents, such as BTEX, PCBs, metals, and

microbes. During high flows, these sediments are stirred up and can release their

potentially high concentrations of accumulated constituents. Many BMPs are designed to 

remove the sediment from runoff, theoretically removing the associated constituents as

well.

Sediment sampling can determine concentrations of constituents not necessarily found

through water column monitoring. Sediments can be sampled upstream and downstream 

of BMPs as well as internal to the BMP to assess removal and effluent efficiencies as

well as internal accumulation of sediment and associated constituents.

When sampling for suspended sediments in the water column, it is important to take the

sample well below the surface of the water, ideally in the middle portion of the water

column where the average concentration of suspended sediment is found. When

sampling sediment from the creek bed or internal to the BMP (e.g., sampling the filter

media or detention pond bottom sediments) sediments should be collected minimizing

disturbance or resuspension of the sediment bed so that the original settled material is

captured in the sample apparatus. Depth of sediment sample should also be noted as

constituent concentrations can vary with depth.

3.2.1.7 Dry Deposition

Many constituents are quite volatile, including mercury, BTEX, PCBs, and some

pesticides. Atmospheric deposition has been pointed to as a significant source of certain 

constituents to water bodies in some areas. These constituents are continuously being

deposited out of the atmosphere either by coming into contact with the surface and

sorbing to it, settling out of the air, or through rainfall. Constituents are deposited onto

surfaces, such as roads, rooftops, and driveways and then incorporated into runoff during 

storm or low flow events. Therefore, atmospheric deposition may contribute some

material to those BMPs that are exposed to the atmosphere, such as detention ponds and 

wetlands. 

In order to assess the contribution of atmospheric deposition to constituent concentrations 

and to isolate influent and effluent concentrations, dry deposition can be monitored in

conjunction with BMP monitoring. Pans can be set out near BMPs to capture dry

deposition of these volatile constituents much in the same way that rainfall gauges are

installed to capture rainfall. After a period of time the deposited material can be analyzed 

to determine constituent concentrations. It is recommended that dry deposition sampling
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should only be conducted as a follow-up investigation where sufficient evidence indicates 

that dry deposition may be contributing appreciably to stormwater pollution.

It is important to note that very little of the total watershed dry deposition actually

contributes to stormwater runoff. The only contributions to water quality impairment that 

currently can be directly attributed to dry deposition fall on the receiving waters

themselves (such as PCBs and DDT measurements for the Great Lakes) (Pitt 2001).

Otherwise, most is incorporated in soils or may not wash off paved areas during rains.

Fugitive dust from nearby sources is usually comprised of relatively large material that is 

poorly washed off, while particulates from regional air pollution sources (particularly

power generation and autos) are mostly very small and are typically incorporated in soils; 

however, these smaller particles are much more easily washed off from pavements and

might be a quantifiable source of pollutants where depositional rates are relatively large

compared to other sources.

3.2.1.8 Modeling Methods

When monitoring is not feasible due to a limited budget or lack of sampling staff,

estimates of water quality parameters, flow, and rainfall can be made using various

models and assumptions. The use of modeling to estimate these parameters may limit

usability of the data depending on the validity of the assumptions made, the accuracy of 

the model itself, and accuracy of the information input into the model. 

Estimates of Water Quality Parameters

Certain water quality parameters can be estimated by monitoring instead for related

parameters that are simpler or less expensive. These related or surrogate parameters are

statistically correlated to the more complicated or expensive parameters. Some common

surrogate parameters and represented parameters are:

Surrogate Parameter Parameter Represented by Surrogate

 Turbidity TSS

 Fecal Coliform Pathogens

 Chemical oxygen Demand (COD) Biological Oxygen Demand (BOD)

In addition to monitoring for surrogate parameters at each monitoring site, water quality

models can be used to estimate constituent concentrations at monitoring sites using

available monitoring data, upstream land use, hydrology, geology, and history to

calculate a mass balance for each constituent. Water quality models are a tool for

simulating the movement of precipitation and pollutants from the ground surface through 

pipe and channel networks, storage treatment units, and finally to receiving waters. Both

single-event and continuous simulation may be performed on catchments having storm

sewers and natural drainage for prediction of flows, stages and pollutant concentrations.

Each water quality model has its own unique purpose and simulation characteristics. It is 

advisable to thoroughly review downloading and data input instructions for each model. 
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The applicability and usefulness of these models is dependent upon a number of

assumptions. The degree of accuracy of these assumptions determines the usefulness of

the output data. For example, one assumption could be based on certain types of land use 

contributing certain constituents to the catchment runoff. The constituents associated

with each land use have been well studied by many monitoring programs, but are still

highly variable, depending on specific activities on each parcel, history of spills, age of

infrastructure, climate, and many other factors. Although modeling of water quality

parameters is a useful tool to estimate parameter concentrations, model results should not 

be interpreted as exact data. Confirmation of water quality model results should be done 

by monitoring a few storms and/or a few sites, then running the model with the observed 

conditions as input variables and comparing the results. 

A variety of modeling tools are available for modeling water quality these include, but

are not limited to, the following:

• Enhanced Stream Water Quality Model, Windows (QUAL2E)

Simulates the major reactions of nutrient cycles, algal production, benthic and

carbonaceous demand, atmospheric reaeration and their effects on the dissolved oxygen

balance. It is intended as a water quality planning tool for developing total maximum

daily loads (TMDLs) and can also be used in conjunction with field sampling for

identifying the magnitude and quality characteristics of nonpoint sources. 

• AQUATOX: A Simulation Model for Aquatic Ecosystems 

AQUATOX is a freshwater ecosystem simulation model. It predicts the fate of various

pollutants, such as nutrients and organic toxicants, and their effects on the ecosystem,

including fish, invertebrates, and aquatic plants. AQUATOX is a valuable tool for

ecologists, water quality modelers, and anyone involved in performing ecological risk

assessments for aquatic ecosystems.

• SWMM: Storm Water Management Model

The EPA’s Storm Water Management Model (SWMM) is a large, complex model

capable of simulating the movement of precipitation and pollutants from the ground

surface through pipe and channel networks, storage/treatment units, and finally to

receiving water. Both single-event and continuous simulation may be performed on

catchments having storm sewers, combined sewers, and natural drainage for prediction of 

flows, stages and pollutant concentrations (EPA 1995). See 

http://www.ccee.orst.edu/swmm/ for more information on this model.
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• HSPF: Hydrologic Simulation Program – Fortran

The HSPF Model is an EPA developed application for simulation of watershed hydrology 

and water quality. The HSPF model uses historical rainfall, temperature and solar

radiation data; land surface characteristics such as land use patterns; and land

management practices to simulate the processes that occur in watersheds. The result of

this simulation is a continuous recreation of the quantity and quality of runoff from urban 

or agricultural watersheds. Flow rate, sediment load, and nutrient and pesticide 

concentrations are predicted. The HSPF model incorporates the watershed-scale 

Agricultural Runoff Model (ARM) and Non-Point Source (NPS) models into a basinscale analysis framework that includes pollutant transport and transformation in stream

channels.

• WASP5: Water Quality Analysis Simulation Program

The Water Quality Analysis Simulation Program (WASP) is a generalized framework for 

modeling contaminant fate and transport in surface waters. WASP5 is the latest of a

series of WASP programs. Based on the flexible compartment modeling approach,

WASP can be applied in one, two, or three dimensions. WASP is designed to permit easy 

substitution of user-written routines into the program structure. Problems that have been

studied using the WASP framework include biochemical oxygen demand and dissolved

oxygen dynamics, nutrients and eutrophication, bacterial contamination, and organic

chemical and heavy metal contamination (James 2001).

• SLAMM: Source Loading and Management Model

The Source Loading and Management Model (SLAMM) was developed to assist water

and land resources planners in evaluating the effects of alternative control practices and

development characteristics on urban runoff quality and quantity. SLAMM only

evaluates runoff characteristics at the source areas In the watershed and at the discharge

outfall; it does not directly evaluate receiving water responses. However, earlier versions 

of SLAMM have been used in conjunction with receiving water models (HSPF) to

examine the ultimate effects of urban runoff.

SLAMM is different from other urban runoff models. Beside examining land

development practices and many source area and outfall control practices, it contains two 

major areas of improvements. These are corrected algorithms for the washoff of street

dirt and the incorporation of small storm hydrology. Without these corrections, it is not

possible to appropriately predict the outfall responses associated with source area

controls and development practices. (James 2001)
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Estimates of Flow

Flows entering and leaving a BMP may be useful to model if actual monitoring is

prohibitive. Flow can be estimated at varying levels of detail using approaches ranging 

from simple spreadsheets to complex hydraulic simulations of extensive urban drainage

networks. Many of the water quality models presented in the previous section are also the 

best choices for modeling flows. 

The simplest approach is to use the volumetric runoff coefficient approach described

below. 

• Volumetric Runoff Coefficient

The Volumetric Runoff Coefficient is an empirical relationship that provides an estimate

of total volume of runoff based on total volume of rainfall according to the following 

equation:

Volume of Runoff = Volume of Rainfall x Rv - Depression Storage

where,

Rv: Volumetric Runoff Coefficients 

This method is usually applied to smaller catchments such as parking lots, rather than

entire watershed areas.

Where monitoring data have been collected for some calibration period such that an

accurate estimate of the volumetric runoff coefficient and depression storage for the

watershed can be made, this approach coupled with accurate rainfall data may provide

one of the least expensive methods for determining total volume of flow from a

watershed on a storm-by-storm basis. 

Estimates of Rainfall

If a nearby rainfall gauge is not available, rainfall at the monitoring site can be

approximated using available gauges that are located as close as possible and at similar

elevation. A network of gauges in an area can be analyzed to relate latitude, longitude,

and elevation to rainfall. The grid of gauges can be expanded and extrapolated to an area 

lacking any gauges, provided that enough rainfall gauges exist. 

Although raw rainfall data are often sufficient for monitoring needs, statistical evaluation

of the data is often more useful. For example, if rainfall is needed to estimate runoff,

most of the rainfall less than 0.1 inch will infiltrate into the ground and not produce any

runoff. These small events could be eliminated from the data set to allow for a more
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accurate account of actual runoff. Two statistical analysis tools used extensively in

separating and filtering continuous rainfall records, include: 

• SYNOP

SYNOP is a statistical rainfall analysis program that converts hourly data into descriptive 

statistics for individual storm events and provides annual rainfall statistics. The program 

takes an hourly precipitation record from a station, organizes the data into rainfall events, 

and computes the statistics of the storm event parameters. When a complete hourly

record has been organized into a sequence of individual storm events, the mean and

standard deviation may be determined for each of the event parameters (EPA 1989).

• SWMM

The SWMM model will conduct a complete statistical analysis almost identical to the

SYNOP tool. In most cases, SWMM is the preferred analysis tool as it is based on the

same basic approach as SYNOP and it lacks some minor bugs present in SYNOP.

3.2.2 Recommendation and Discussion of Monitoring Frequency

The number of storms to be monitored each year (i.e., monitoring frequency) is an

important consideration in planning your monitoring program. Budget and staff

constraints generally limit the number of storms, locations, and parameters to be

monitored. Program objectives should be weighed in light of available resources to

determine the best mix of monitoring frequency, locations, and parameters. 

The cost of learning more (i.e., conducting more intensive monitoring) should be compared

to the cost implications of moving forward too far and implementing extensive controls

before having learned enough to guide planning, stormwater management commitments,

and/or negotiations with regulatory agencies. The cost of controlling unimportant pollutants 

and/or unimportant sources, or implementing ineffective BMPs could easily exceed the cost 

of monitoring to learn more about actual BMPs' performance under the conditions that

prevail in the system. Clearly, there is a need for balance here, because endless studies

should not be substituted for control actions. 

In general, however, many measurements (i.e., many samples during many events) are

necessary to obtain enough data to be confident that actual BMP performance not just

“noisy data” (e.g., variability artifacts caused by external factors, equipment and operator

errors). Consequently, BMP effectiveness studies can be expensive and time-consuming. 

3.2.2.1 Statistical Underpinnings of Study Design 

Four factors influence the probability of identifying a significant temporal and/or spatial

change in water quality:
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1) Overall variability in the water quality data.

2) Minimum detectable change in water quality (difference in mean concentration).

3) Number of samples collected.

4) Desired confidence level from which to draw conclusions.

Statistical analysis may be conducted to estimate how many events need to be monitored

to achieve a desired confidence in a conclusion (i.e., power analysis). Performing a power 

analysis requires that the magnitude of detectable change, the confidence level, and the

statistical power or probability of detecting a difference are defined. Typically, the

confidence level and power are at least 95% and 80%, respectively, meaning that there is a

5% probability of drawing an incorrect conclusion from the analysis and a 20% probability

that a significant change will be overlooked.

The power analysis often shows that many samples are needed to yield a power of 80% to

90% (i.e., discern a small change). In fact, Loftis et al. (2001) report that achieving a

power of 80% requires double the data required for a power of 50%, and a power of 90%

requires triple the data required for a power of 50%. The exponential increase in data

required to achieve higher statistical power reinforces the need for careful consideration of

the minimum detectable change required (and amount of data required) to achieve project 

objectives. In some cases, project objectives require quantification of small changes in

concentration (e.g., inefficient BMPs or BMPs receiving relatively clean influent), which

may call for larger power, but in many cases, less power (i.e., few samples) may be

sufficient. If available resources prohibit the frequent monitoring of all locations, then

reducing the number of locations or parameters tested may provide sufficient data to

resolve slight differences in concentration at a more reasonable cost. Statistical

confidence in the results of the monitoring program(collecting samples from a significant 

number of events) should be assigned a higher importance than collecting information

from a larger number of locations or testing a multitude of water quality parameters.

3.2.2.2 Factors Affecting Study Design

Based on a review of existing studies, it is apparent that much BMP research in the past

has not considered several key factors. The most frequently overlooked factor is the

number of samples required to obtain a statistically valid assessment of water quality. 

This section focuses on estimating the number of samples required prior to beginning

monitoring activities.

Number of Samples

Stormwater quality may vary dramatically from storm to storm. Therefore, monitoring a 

large number of storms is required if the objective of the program is to obtain accurate

estimates of stormwater pollution in a given catchment (e.g., to determine whether water 
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quality is changing over time or whether a given BMP is effective). However, staff and

budget constraints typically limit monitoring to either a limited sampling methodology

incorporating a smaller set of parameters for many storms, or a more detailed monitoring

approach including a larger set of parameters for a few storms.

Determining the Number of Observations Needed 

Typically a large portion of the costs associated with conducting a BMP monitoring

program are related to collection and analysis of water quality samples. It is imperative

that samples are not only collected in a manner consistent with the guidelines, but also

that an adequate number of samples are collected for statistical validation. Estimates of

the number of samples required to yield statistically valid monitoring results are also

useful for making decisions about the nature and extent of monitoring efforts prior to

implementation. Often goals for a monitoring effort (e.g., to demonstrate that a specific

BMP is achieving a given level of removal of a constituent) may not be consistent with

fiscal limitations of the project. This section provides a method for estimating the

number of samples required for obtaining a statistically valid estimate of both the mean

event mean concentration at a single sampling station and the percent difference observed 

at two stations.

As mentioned above, four factors affect predictions as to whether a sampling program

will collect an adequate number of samples to provide a useful estimate of the mean 

station EMC:

1) Allowable level of error in estimates of mean (i.e., variance)

2) Level of statistical confidence in estimates of the mean

3) Number of samples collected

4) Variability in population trends

A variety of methods are available for estimating the number of observations required to 

predict the range surrounding a sample mean that contains the population mean. EPA

(1993b) presents a nomograph relating the coefficient of variation (COV, defined as the

ratio of the sample standard deviation to the sample mean) to the allowable error in the

estimate of the population mean as a fraction of the sample mean. This nomograph is

given in Figure 3.1 for normally distributed data and a statistical confidence of 95%. 

Figure 3.1 can be generated using Equation 3.2 below. The number of samples required 

(n) is a function of the allowable error in the data mean (E) and the standard deviation (s), 

(or in the case of Figure 3.1, the COV) (Cochran 1963).
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( )

( )

2

2

E

4

n 

s

= Equation 3.2

where,

n: number of samples

s: sample standard deviation

E: allowable error in the data mean

This approach is useful for estimating the number of samples required when sampling at

a single location where an acceptable upper bound for the error is known. However,

Equation 3.2 does not provide an estimate of the number of samples required to

determine if the mean concentrations from two sample sets are statistically significantly

different.

Figure 3.1: Nomograph relating coefficient of variation of a sample set to the 

allowable error in the estimate of the population mean (Pitt 1979).

Consideration of the number of samples required to draw statistically significant

conclusions from data is often ignored until after monitoring work has been completed. 

However, there is great benefit to performing this analysis before initiating a monitoring

program, particularly where the variability of the data is expected to be quite high

because resources may be better spent on control measures than verification of BMP

efficiency.

Appendix C expands the approach described in EPA (1993b) to the analysis of the

number of samples required to conclude that there is a statistically significant difference

between means calculated from sample data selected at random from two populations. 
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Appendix C provides a straightforward method for estimating the number of samples

required to determine, with some degree of confidence, that observed means (such as the 

EMCs resulting from a BMP monitoring program) are statistically significant. 

One assumption of the approach provided in Appendix C is that measured influent and

effluent concentrations are normally distributed having a mean equal to the EMC. 

Collection of water quality sample data at the inflow and outflow of a structural BMP

allows for the determination of a mean EMC and the variance of the data (or log-mean 

and log-variance for log-normally distributed data). The mean and variance (square of

the standard deviation) are the first and second moments of the distribution, respectively. 

These moments completely describe a normal distribution; thus, using the mean and

variance of the distribution corresponding to any probability can be determined. 

Additionally, probabilities are additive so that confidence intervals between any two

probabilities can be determined simply by calculating values of the distribution

corresponding to the upper and lower probabilities of the confidence interval (i.e.,

confidence limits). The most common application is to determine the range of values

surrounding the mean that falls within a specified 95% confidence interval (i.e.,

probabilities of 2.5% and 97.5%, which are the mean plus/minus 1.96 times the standard

deviation).

One test that can be used to evaluate whether the means of two data sets (e.g., influent

and effluent) are statistically different is a hypothesis test (e.g., student t-test), which is

basically a test that quantifies the overlap of two confidence intervals surrounding the

mean. The mean values will be considered different if there is little (as defined by the tstatistic distribution) overlap between the confidence intervals. This document presents

hypothesis testing with the assumption that data sets are large (i.e., are composed of 30 or 

more values). Given this assumption, the Z-statistic can be used in place of the t-statistic, 

which eliminates the need to incorporate the degrees of freedom of a data set into

hypothesis analysis. However, for analysis of small data sets, users should use the tstatistic in place of the Z-statistic (and refer to the student t-test in a standard statistics

text). An iterative solution is required to determine the number of samples needed if the tstatistic, due to its dependence on the number of measurements, is used in place of the Zstatistic (Gilbert 1987).

The confidence interval about the mean for normally distributed data is defined as:

















− Ζ + Ζ

n

C

n

C

s s

a 2 a 2

, Equation 3.3

where,

C = mean concentration

σ = standard deviation for the population of the concentrations

Zα/2 = Z-statistic obtained from a standard normal distribution table
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n = number of measurements

The confidence interval corresponds to a significance level (α), where (1 - α)x100% is

the probability that C will fall within the confidence interval. As α increases, the

confidence interval will become larger (all other variables remaining the same). If the

population standard deviation (σ) is unknown, which is typically the case, then σ can be 

estimated using the sample standard deviation (s). Prior to the collection of field data, the 

standard deviation typically is estimated from existing data sets either from local or

nationally published data on expected quality of stormwater runoff.

The confidence interval is often used to show the likely range containing the population

mean, and for comparing the means for two populations (i.e., influent and effluent). 

However, the confidence interval formula contains the number of samples in the data

sets, and therefore the equation can be solved for the number of samples needed to

achieve a desired confidence interval for an expected difference in population means. 

The derivation of this formula is provided in Appendix C. As Appendix C shows, the

resulting equation is (see the appendix for variable definitions):

( )

2

2 2

%

2 %

























× × −











Ζ + Ζ

=

removal

COV removal

n

a b

 Equation 3.4

n = 2 [(Z1-α + Z1-β)/(μ1 -μ2)]2σ

2

 Equation 3.5

This assumes that the sample sets have identical n, COV, Zα/2, and Z1-β. Assuming the

COVs of the sample sets are equal is a significant assumption because it mandates that

sin/sout equals Cin Cout . This assumption allows for the generation of a simple nomograph 

showing iso-sample number lines on a plot of COV versus percent difference in the

means (see Figure 3.2). If the influent and effluent COVs are not assumed to be equal, n

can be found from Equation 3.6 below:

( )

2

2 %

1 %











 + −

= Ζ

removal

COV COV removal

n

in out

a Equation 3.6

Where COV is defined for influent and effluent data sets.

Zα/2 is a function of the desired level of certainty. For example, to determine a confidence 

interval with 95% certainty (significance level α = 0.05), Zα/2 equals 1.96. Values for

Zα/2 are tabulated in most statistical texts.
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As an example of the application of the confidence interval, consider the case where the

researcher wants to determine if a mean influent concentration is greater than a mean

effluent concentration (assuming effluent concentrations are lower than influent 

concentrations). To do this, the 95% confidence interval of the influent and effluent

EMCs are calculated. If the upper confidence limit (i.e., 97.5 percentile) of the effluent is 

less than the lower confidence limit of the influent (2.5 percentile), then the mean influent 

concentration is not equal to the mean effluent concentration, with 95% confidence.

As mentioned above, the Equation s derived in Appendix C allow for the solution of the

COV, percent removal, or n in terms of the other two variables. Solving for the required 

COV for an estimated percent removal and n is shown in Figure 3.2 (for 95% confidence 

limits and a power of 80%). The primary use of Figure 3.2 is to estimate the n required

to have 95% confidence in a hypothesis test given estimates of COV and percent

removal. It is recommended that Figure 3.2 be used to provide a reasonable estimate of

the number of samples (i.e., events) needed to quantify whether or not a BMP achieves an 

anticipated level of performance (i.e., measured by percent removal). It can be seen from 

Figure 3.2 that as the relative difference between influent and effluent mean event mean

concentrations becomes small, the number of required monitored events becomes quite

large.

Variations of the plot presented in Figure 3.2 are provided in Appendix B for a variety of 

different confidence intervals, powers, and percent differences. These plots were

developed by Pitt and Parmer (1995).

Many commonly used statistical tests (e.g., parametric analysis of variance) are based on the 

assumption that the data are sampled at random from a normally distributed population.

Thus, prior to applying the methods outlined in this section, the limitations imposed by

assumed normality of sample data sets should be fully understood. Several methods can

be used to determine the normality of a data set (or of data that is transformed to be

normally distributed). Some of these tests are the W-test, Probability Plot Correlation

Coefficient (PPCC), and graphical methods; all are useful for the analysis of stormwater

quality data. 

As mentioned previously, researchers have found that stormwater quality data is

generally best fit by a log-normal distribution (EPA 1983; Driscoll et al. 1990;

Harremoes 1988; Van Buren et al. 1996) and theoretical justification for using a lognormal distribution is provided by Chow (1954). Although, Van Buren et al. (1997) and

Watt et al. (1989) found that pond effluent and/or soluble constituents in stormwater may

be better fit using a normal distribution.
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Figure 3.2 Number of samples required using a paired sampling approach to observe a

statistically significant percent difference in mean concentration as a

function of the coefficient of variation (power of 80% and confidence of

95%)
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The following are some properties of the lognormal distribution. If a sample (a data set of N 

observations) is drawn from an underlying population that has a lognormal distribution, the

following apply:

1. The natural logarithm of log-normally distributed data is normally distributed with a

log-mean (μlnK) and log-standard deviation (σlnK) computed from the natural logtransformed data.

2. The arithmetic statistical parameters of the population (mean, median, standard

deviation, coefficient of variation) should be determined from the theoretical

relationships (see Appendix D) between these values and the mean and standard

deviation of the transformed data. 

A few mathematical formulas based on probability theory summarize the pertinent

statistical relationships for log-normal probability distributions. These formulas provide

the basis for forward and reverse conversions between arithmetic properties of

untransformed data (such as measurements of concentration, flow, and load) and

properties of transformed data (values that fall on a normal distribution so that statistical

moments and probabilities can be defined). Appendix D, presents these formulas.

3.2.3 Recommendation and Discussion of Water Quality Parameters and 

Analytical Methods

3.2.3.1 Selecting Parameters

Stormwater runoff may contain a variety of substances that can adversely affect the

beneficial uses of receiving water bodies. To select the parameters to be analyzed for a

given monitoring location, consider the following:

• Permit requirements (if any). Monitoring to comply with a permit may specify the

parameters that must be measured in stormwater discharges. However, monitoring

for additional parameters may help attain overall program objectives.

• Land uses in the catchment area. Land use is a major factor affecting stormwater

quality. Developing a list of the pollutants commonly associated with various land

uses is helpful for deciding what to look for when monitoring.

• Existing monitoring data (if any) for the catchment area. Previous monitoring data

can be helpful in refining the parameter list. However, if there is uncertainty about

the monitoring methods and/or analytical data quality, or if the existing data pertain to 

baseflow conditions or only one or two storms, caution should be used in ruling out
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potential pollutants. For example, an earlier study may have used outdated analytical 

methods which had higher detection limits than current methods.

• Beneficial uses of the receiving water. Information on water quality within a

stormwater drainage system often is used to indicate whether discharges from the

system are likely to adversely affect the receiving water body. For example, if a

stormwater system discharges to a lake, consider analyzing for nitrogen and

phosphorus because those constituents may promote eutrophication.

• Overall program objectives and resources. The parameter list should be adjusted to

match resources (personnel, funds, time). If program objectives require assessing a

large number of parameters (based on a review of land uses, prior monitoring data, 

etc.), consider a screening approach where samples collected during the first one or

two storms are analyzed for a broad range of parameters of potential concern. 

Parameters that are not detected, or are measured at levels well below concern, can

then be dropped from some or all subsequent monitoring events. To increase the

probability of detecting the full range of pollutants, the initial screening samples

should be collected from storms that occur after prolonged dry periods.

A recommended list of constituents (along with recommended method detection limits

for comparing stormwater samples to water quality criteria) for BMP monitoring has

been developed and is presented in Table 3.1 below. Refer to Strecker (1994), Urbonas

and Stahre (1993), and the ASCE Database website (http://www.bmpdatabase.org/) for

more information on BMP monitoring parameters. The choice of which constituents to

include as standard parameters is subjective. The following factors were considered in

developing the recommended list of monitoring parameters:

• The pollutant has been identified as prevalent in typical urban stormwater at

concentrations that could cause water quality impairment (NURP 1983; FHWA 1990; 

and recent Municipal NPDES data).

• The analytical result can be related back to potential water quality impairment.

• Sampling methods for the pollutant are straightforward and reliable for a moderately

careful investigator.

• Analysis of the pollutant is economical on a widespread basis.

• Controlling the pollutant through practical BMPs, rather than trying to eliminate the

source of the pollutant (e.g., treating to remove pesticide downstream instead of

eliminating pesticide use).

Although not all of the pollutants recommended here fully meet all of the factors listed

above, the factors were considered in making the recommendations. When developing a list 
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of parameters to monitor for a given BMP evaluation, it is important to consider the 

upstream land uses and activities. 

The base list represents the most basic arrangement of parameters. There may be

appropriate applications where other parameters should be included. For a discussion of 

why some parameters were not included, see Strecker (1994). 

Table 3.1: Typical urban stormwater runoff constituents and

recommended detection limits

Parameter Units Target Detection Limit

Conventional

PH

Turbidity

Total Suspended Solids

Total Hardness

Chloride

pH

mg/L

mg/L

mg/L

mg/L

N/A

4

4

5

1

Bacteria

Fecal Coliform

Total Coliform

Enterococci

MPN/100ml

MPN/100ml

MPN/100ml

2

2

2

Nutrients

Orthophosphate

Phosphorus – Total

Total Kjeldahl Nitrogen (TKN)

Nitrate – N

mg/L

mg/L

mg/L

mg/L

0.05

0.05

0.3

0.1

Metals-Total Recoverable

Total Recoverable Digestion

Cadmium

Copper

Lead

Zinc

μg/L

μg /L

μg /L

μg /L

0.2

1

1

5

Metals-Dissolved

Filtration/Digestion

Cadmium

Copper

Lead

Zinc

μg /L

μg /L

μg /L

μg /L

0.2

1

1

5

Organics

Organophosphate Pesticides (scan) μg /L 0.05 - .2

Note: This list includes constituents found in typical urban stormwater runoff. Additional parameters may be needed to address site 

specific concerns.
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3.2.3.2 Dissolved vs. Total Metals

Different metal forms (species) show different levels of toxic effects. In general, metals 

are most toxic in their dissolved, or free ionic form. Specifically, EPA developed revised 

criteria for the following dissolved metals: arsenic, cadmium, chromium, copper, lead, 

mercury (acute only), nickel, silver, and zinc. Chronic criteria for dissolved mercury 

were not proposed because the criteria were developed based on mercury residuals in 

aquatic organisms (food chain effects) rather than based on toxicity. For comparisons 

with water quality criteria, it is advised that the dissolved metals fraction be determined. 

If selenium or mercury is of concern, total concentrations should also be measured to 

enable comparison with criteria based on bioaccumulation by organisms. 

The distribution of pollutants between the dissolved and particulate phases will depend 

on where in the system the sample is collected. Runoff collected in pipes with little 

sediment will generally have a higher percentage of pollutants present in the dissolved 

form. Runoff collected in receiving waters will generally have a higher percentage of 

pollutants present in particulate form due to higher concentrations of suspended solids 

that acts as adsorption sites for pollutants to attach to. It is difficult to determine how 

much of the dissolved pollutants found in storm system pipes will remain in the dissolved 

form when they are mixed with suspended sediments in receiving waters. As a result, it 

is difficult to determine the ecological significance of moderate levels of dissolved 

pollutants present within the conveyance system. In addition, hardness values for

receiving waters are often different than those for stormwater. Hardness affects the bioavailability of heavy metals, further complicating the ecological impact of dissolved 

heavy metals. 

If loads to the receiving waters are of concern (e.g., discharge to a lake known to be a 

water quality limited water body) it may be desirable to determine total recoverable 

metals in addition to dissolved metals to assess the relative load from different sources. 

Finally, total recoverable metals data together with dissolved metals data can be used to 

assess potential metals sediment issues. 

3.2.3.3 Measurements of Sediment Concentration

A variety of methods have been employed in stormwater quality studies for quantifying 

sediment concentration. The most frequently cited parameter is “TSS” or total suspended 

solids. The “TSS” label is used, however, to refer to more than one sample collection 

and sample analysis method. The “TSS” analytical method originated in wastewater 

analysis as promulgated by the American Public Health Association. 
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The USGS employs the suspended-sediment concentration (SSC) method (ASTM 2000), 

which was originally developed for the Federal Interagency Sedimentation Project

(USGS 2001). SSC data is often described as TSS data, when in many cases results from 

the two methods may be significantly different. The difference between methods is

sample size – the SSC method analyzes the entire sample while the TSS method uses a

sub-sample. The process of collecting a representative sub-sample containing larger

sediment particles is problematic as large sediment particles (e.g., sand) often settle

quickly. Differences between the results obtained from SSC and TSS analytical methods 

become apparent when sand-sized particles exceed 25% of the sample sediment mass

(Gray et al. 2000). Gray demonstrates that at similar flow rates, sediment discharge

values from SSC data can be more than an order of magnitude larger than those from TSS 

data (USGS 2001) due primarily to larger particles that are often missed in the TSS

method. “The USGS policy on the collection and use of TSS data establishes that TSS

concentrations and resulting load calculations of suspended material in water samples

collected from open channel flow are not appropriate” (USGS 2001). 

It is recommended that both TSS (for comparison to existing data sets) and SSC be

measured.

The discrepancies in sampling methodologies currently employed in the field highlight

the importance of particle size distribution (PSD) analysis as an essential component of

any BMP monitoring study. PSD data provide the information necessary to meaningfully 

interpret the ability of a BMP to remove suspended materials. However, PSD methods

are varied and include (USGS 2001):

• Dry sieve.

• Wet sieve.

• Visual accumulation tube (VA).

• Bottom withdrawal tube.

• Pipet.

• Microscopy.

• Coulter counter.

• Sedigraph (x-ray sedimentation).

• Brinkman particle pize analyzer.

• Laser diffraction spectroscopy.
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• Light-based image analysis.

The investigator must select and use a consistent and appropriate method.

Specific gravity (SG) of sediments is also an important component in determining the

settleability of sediments and is recommended for sediment analysis by ASTM (1997). 

For BMP studies where PSD data are being collected, SG provides additional useful

information about the ability of a particular BMP to remove sediment.

In addition, settling velocities of sediments are highly important and can be either

measured directly or calculated theoretically from SG and PSD data. Settling velocities

give the most useful information for quantifying BMP sediment removal efficiency.

The difficulty of collecting accurate sediment samples underscores the need to fully

understand the conditions under which sediment data were collected and analyzed. 

Regardless of the analytical methods used, the sampling methodology often introduces

the largest bias to sediment data.

3.2.3.4 Analytical Methods

After the parameters have been selected, the analytical methods to be used to measure

them must be chosen. Select analytical methods that will provide results of sufficient

quality to support the intended uses of the data. To determine the quality of data

necessary for a program, consider the following: 

• Appropriate analytical levels. EPA guidance suggests tailoring the analytical level to 

the intended use of the data. EPA has defined five analytical levels:

I. Field screening and analysis using portable instruments

II. Field analysis using more sophisticated portable analytical instruments,

possibly set up in a portable laboratory at the site

III. Analysis performed at an off-site analytical laboratory using EPA Contract 

Laboratory Program (CLP) or equivalent methods, but without the

validation or documentation procedures required for CLP

IV. CLP routine analytical services and complete data reporting packages

V. Analysis by non-standard methods (to achieve very low detection limits or 

measure a specific parameter not included in standard methods) 

Stormwater samples are generally analyzed using Levels I, II, or III. Levels IV and V 

are not used very often for stormwater projects because these levels are intended for

situations requiring low detection limits and high confidence, such as human or

ecological risk assessments or Superfund/MTCA investigations. 
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• Appropriate methods should be selected for the chemicals of concern. These are the

most significant contributors to human health or environmental risk at the site. 

Chenicals of concern are generally the most toxic, mobile, persistent, and/or

frequently occurring chemicals found at the site. Commonly occurring chemicals of

concern in stormwater runoff include metals (cadmium, copper, lead, and zinc),

polycyclic aromatic hydrocarbons (PAHs), and organo-phosphate insecticides (e.g.,

diazinon and chloropyrifos). The latter are included because recent studies in the San 

Francisco Bay area found that diazinon accounted for much of the observed aquatic

toxicity in urban runoff (Cooke and Lee 1993). Other chemicals (e.g., organochlorine 

pesticides and PCBs) should be included if there is reason to believe they are present. 

Note that the potential toxicity of some metals in freshwater systems is affected by

the hardness of the water; thus, water quality standards for cadmium, copper,

chromium, lead, nickel, silver, and zinc are calculated based on water hardness. For

this reason, total hardness should be measured if metals are measured at sites where

fresh water quality standards may apply. 

• Level of concern. This term refers to the chemical concentration that is of concern. 

Typically, state or federal water quality criteria for protection of aquatic life or human 

health are used as the default level of concern for water sample results, and sediment

quality criteria are used as the level of concern for sediment sample results. For

pollutants that do not have state or federal water or sediment quality standards, the

Risk-based Concentration Table developed by EPA Region III (EPA 1994a,b) can be

used as levels of concern for water and soil sample results. 

• Required detection limit/practical quantitation limit. The level of concern directly

affects the data quality requirements because the sampling and analysis methods used 

must be accurate at the level of concern. Sampling variability is often difficult to

control, especially in stormwater. The relative accuracy of most laboratory methods

decreases as concentrations approach the detection limits. For these reasons, the

practical quantitation limit (5 to 10 times the detection limit) should be below the

level of concern, if possible. 

If the objective is to conduct a screening study to identify chemicals that appear to be

present at levels of concern, consider analyzing for a wide range of constituents using

analytical methods with low detection limits. An initial screening analysis can generally

reduce the number of chemicals analyzed in subsequent studies by eliminating those that

were detected below their corresponding levels of concern. 

In cases where it is known that there is a high degree of correlation between the

concentration of the target pollutant(s) and some other parameter (e.g., fine particles, TSS, 

total organic carbon), then it may be possible to use less costly monitoring approaches to

track the substitute, or “proxy” parameter(s). Although this approach can introduce some

uncertainty because it does not track the target pollutants, it is still worthy of consideration. 

If the correlations are known to be strong and the cost differences pronounced, this strategy

may provide a way to obtain much more data (i.e., more frequent observations during more
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storm events and/or at more locations). Such improvements in data quantity could more

than offset the uncertainties introduced by imperfect correlations.

There are many precedents for using proxy parameters as indicators. For example, fecal

coliform are bacteria often used as proxies for pathogens and as an indicator of fecal

contamination. Total organic carbon and COD are sometimes used as proxies for BOD. 

Turbidity is commonly used as a proxy for suspended solids, which in turn, is sometimes

used as a proxy for other pollutants of concern (e.g., metals, PAHs). The important

consideration is that other factors could also account for observed changes in the proxy

parameter relationship to other pollutants. 

In many BMP monitoring programs, there are opportunities to obtain additional information 

at little or no incremental cost (e.g., temperature or pH data). Such information may turn out 

to be valuable to the overall stormwater program at some time in the future and/or to others

programs. 

3.2.4 Recommendation and Discussion of Monitoring Equipment and 

Methods

BMP monitoring can be done using a variety of equipment and methods. The type of

equipment and methods used often directly affect the usability of the data collected. Both 

options and recommended approaches for monitoring are provided in this section.

3.2.4.1 Equipment

Equipment used to monitor BMPs includes a variety of data loggers, primary devices

(e.g., flumes, weirs, and nozzles), secondary devices (e.g., bubblers, pressure transducers, 

and ultrasonic devices), automatic samplers, manual sampling devices, and rain gauges.

These devices and their uses are described below.

Data Loggers

Data loggers are used to monitor signals from various pieces of equipment and store the

impulses that they generate. When data loggers are combined with software to measure

and route signals between instruments and analyze data, they are referred to as “data

acquisition systems” and are often used as the execution center of a monitoring station. 

Most data loggers have several input ports and can accommodate a variety of sensory

devices, such as a probe or transducer (e.g., flow meters, rain gauges, etc.). While

specific design characteristics vary between instruments, overall data logger design is

relatively standard. Some water quality samples have data loggers built into them;

however, they are usually more limited in capabilities (e.g., programmability, 

communication options, etc.) than independent data loggers. 
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Data loggers suitable for stormwater monitoring applications are typically constructed of

weather-resistant materials capable of protecting their internal circuitry from water and

dust hazards. They are designed to operate at extreme temperatures, from as low as 

-55oC to as high as 85oC (-67oF to 185oF). In addition, most models can be securely

mounted in remote locations, providing protection from wind and rain, wildlife, and

vandalism. 

Figure 3.3: Data Logger with Weatherproof Housing (Handar)

Typical data loggers for field use consist of the following components: a weatherproof

external housing (a “case”), a central processing unit (CPU) or microprocessor, a quantity 

of random-access memory (RAM) for recording data, one or several data input ports, a

data output port, at least one power source, and an internal telephone modem. In

addition, most data loggers have an input panel or keyboard and a display screen for field 

programming. The CPU processes the input data for storage in RAM, which usually has 

a backup power source (such as a lithium battery) to ensure that data are not lost in the

event of a failure of the primary power. Data stored in RAM may be retrieved by

downloading to a portable personal computer (PC), or to a host PC via modem. 
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Figure 3.4: Data Logger Without Housing (Campbell Scientific)

Data loggers vary in size from 0.2 to 9 kilograms (0.5 to 20 pounds) or more. Both

portable and fixed data-logging systems are available. For long-term, unattended

monitoring projects, a fixed instrument capable of serving as a remote transmitting unit

(RTU) may be preferable to a portable one. Manufacturers of data loggers suitable for

stormwater monitoring include: Campbell Scientific, Logan, Utah; Global Water

Instrumentation, Fair Oaks, California; Handar, Inc., Sunnyvale, California; In-Situ, Inc., 

Laramie, Wyoming; ISCO, Inc., Lincoln, Nebraska; Logic Beach, Inc., La Mesa,

California; and Sutron Corporation, Sterling, Virginia. 

Programmability

Most data loggers can be programmed to record data at user-selected intervals. For

example, a particular model may be designed to permit a user to select a data recording

frequency from once every two seconds to once every 48 hours, with the choice of

frequencies varying by two-second intervals. The minimum and maximum intervals vary 

from vendor to vendor, and often vary among models offered by the same vendor. In

addition, some data loggers have the ability to record event-related data, such as

minimum and maximum flow rates and event timing and duration. Data loggers can also 

record data simultaneously for several different intervals (15 minutes, storm event, daily). 

Most data loggers are field programmable, meaning that the software is equipped with an 

interface that permits on-site manipulation. However, some less expensive models may

only be programmed at the factory. These models provide the advantage of cost savings 

but provide limited versatility, especially if project requirements change over time. 

In addition, most data loggers possess the capability of remote programming via

telephone modem. These models offer a significant advantage over factory programmed 

and field programmable data loggers because they allow the user to manipulate the

program or monitor its effectiveness remotely. A network of data loggers used in a

multi-site monitoring effort can be reprogrammed more efficiently than by traveling from 

site to site. An example where this functionality would be useful is if a predicted storm

rainfall depth changes after sites are set up, the sampling interval could be adjusted

remotely.

Although many vendors offer data loggers with the capability of remote manipulation via 

modem and PC, the user-friendliness of the various models may vary greatly between
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vendors. Most vendors have developed software packages that are provided free of

charge with the purchase of their data logging systems. These software packages allow

for remote data logger programming, and provide for data manipulation, analysis, and

presentation at the host PC location. The interface environments used by these packages 

varies from DOS-like command lines to menu-driven point-and-click environments. 

Most data loggers that are provided with vendor-developed software packages require an 

IBM-compatible PC with WindowsTM to run the packages. Therefore, this additional cost 

should be considered when evaluating a particular model. Another point of consideration 

is the format in which a particular model logs the data it receives. Some models log data 

in a format that can be converted from ASCII files to any of several commonly available 

spreadsheet or word processing files, while others require the use of their particular

vendor-developed software for data analysis and manipulation. 

Data Capacity

Memory type and capacity vary greatly between instruments. Standard capacity varies

between models and vendors from 8K or less, to more than 200K. In general, one data

point uses 2 bytes of information; therefore, a data logger with 64K of memory could be 

expected to have a maximum data point capacity of 32,000 data points before data

downloading or additional memory would be required. However, some types of data

require as much as 4 bytes of memory per point. It should be noted that when recording

sets of data related to storm events, memory may be exhausted more quickly than

expected. 

The type of memory used by a particular model is also an important consideration. Most 

data loggers use non-volatile RAM, (i.e., memory that is not lost in case of a power

failure). Although this provides insurance that essential data will not be lost, the use of

non-volatile memory may not be necessary if the data logger is equipped with a backup

power source. A backup power source is automatically activated when the primary

power source is lost. Typically, backup power is supplied by a lithium battery, with

protection varying from 1 to 10 years. 

Most models are programmed to stop recording data upon exhaustion of available

memory (“stop when full”). However, some models are equipped with wraparound or

rotary memory, which rewrites over the oldest data when available memory becomes

exhausted. When using rotary memory, it is important to realize that data may be lost if

it is not downloaded before it is written over. 

Data loggers separate from water quality samplers increase the flexibility of the system

because of their increased programmability over those loggers on samplers. Memory

capacity is often an issue (even with the current inexpensive memory) and requires that

careful attention be paid to downloading data before it is overwritten.
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Communications

Models vary in their ability to accept input from more than one source. Some data

loggers are designed with a single analog input channel, while others are designed with

up to 16 channels. In addition, some of the newer models accept digital input data. The 

choice of a particular model should be based upon the number of sensors or probes from 

which the instrument will be required to accept data. 

Data loggers can accept information from many different types of sensors and

transducers. This allows for versatile use of most data logging systems. Some vendors

offer probes and transducers with built-in data loggers; however, these systems typically

cannot accept input data from other sensory devices, and their ability to communicate

output data is often limited. 

With regard to output communications, all data loggers interface with the standard RS232 interface type, and some possess the capability to communicate with other interface

types. In most cases, data can be downloaded on-site to a laptop PC or a unit may be

transported to a lab or office so that the data can be downloaded to a desktop PC. As

indicated earlier, data loggers can be equipped with an internal modem for

telecommunications, allowing a user to download data from a remote host PC without

having to visit the field site. 

In most cases, use of a telephone modem requires an IBM-compatible PC as the host and 

the vendor’s software. Typically, baud rates can be selected by the user. However, some 

models are capable of only a few baud rates, a limitation that should be considered when 

choosing a specific model. Some machines also possess the capability to transmit data

via line-of-sight, UHF/VHF, or satellite radio. These options also allow for remote

manipulation of programming and downloading of data. 

Power Requirements

In general, data loggers are energy efficient devices. Most are powered by an internal

battery, with the option of using external electrical power, if available. Some can also be 

equipped to use solar power. 

Data loggers powered by internal batteries often offer a choice of cell type. Some models 

offer the choice of rechargeable cells or standard 12 volt alkaline cells, while others offer 

either alkaline or lithium batteries. The choice of power source and model selection,

depends upon several factors, including site accessibility, distance, and amount of data to 

be recorded. 

Alkaline cells are less expensive than lithium or rechargeable batteries, but they have a

shorter life and must be replaced more often. While alkaline cells offer a potential power 

life of several months, lithium cells offer a potential power life of several years. 

However, since lithium batteries are considered a hazardous material, data loggers using
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lithium batteries are subject to more stringent shipping requirements than models using

standard alkaline cells. In addition, since alkaline batteries must be replaced and

discarded frequently, the use of alkaline batteries may actually be more expensive than

using rechargeable batteries. Although rechargeable batteries offer less battery waste and 

potential cost savings, the time and cost required to recharge the batteries should be

considered when evaluating power options.

Operating temperature range is another important factor to consider when choosing a

power supply. Lithium expands both the minimum and maximum temperatures at which 

power can be used by the data logger. Under extreme conditions, it may not be feasible

to use a data logger powered by alkaline batteries.

Input

Control Module

Data Logger

Special Sensors

Temperature, 

Conductivity, etc.

Rain 

Gauge

Pump or 

Flow 

Sensors

Output

Rain Modem

Gauge

Communications

Telephone Line Cellular RF(SCADA, etc.)

Composite Discrete

Sampler

Desk Top PC

Figure 3.5: Data Logger Summary
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Flow

Natural channels, engineered open channels, and pipes are used as stormwater conveyances. In

each case, hydraulic considerations dictate the mathematical relationships that can be used to

describe the flow rate at a given point in time. One of the primary hydraulic considerations is

whether the flow configuration represents an “open” or “closed” channel. Open channel flow

has a free water surface, and because the flow is driven by gravity, it varies with depth. Closed

channel flow, in which the flow fills a conduit, is caused by and increases with the hydraulic

pressure gradient. Some stormwater conveyance system pipes may function as open channels

during periods of low storm runoff and as closed channels when the runoff volume becomes

sufficiently large or when water is backed up due to downstream flow conditions (e.g., tide, river 

flooding, etc).

In general, the flow rate in an open channel depends on the depth of flow and several other

factors (Chow 1959) including:

• Geometric shape and changes in shape and slope along the length of the channel (affects

potential for development of turbulence and/or varied flow and therefore the choice of

methods and instruments used for measurement of flow).

• Hydraulic roughness of the conveyance surface, whether natural or manmade (affects the

energy losses of the flow).

• Rate at which the depth of flow changes over time (steady vs. unsteady flow).

• Spatial scale over which the flow rate changes (uniform vs. varied flow).

The measurement of the flow rate in an open channel is more difficult to obtain than that of a full 

pipe, because the free surface will change with respect to time.

Typically, stormwater flow through BMPs will fit the open channel flow configuration. 

However, some BMPs are drained by pipe systems, which may be flowing, full at times. 

Therefore, methods used for measuring flow in full pipes will also be discussed.

Table 3.2 summarizes available flow measurement methods, the requirements for their use,

typical BMP use, and required equipment. Each of these methods is discussed in more detail in

the following sections.
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Table 3.2: Flow Measurement Methods

Method Major 

Requirements 

For Use

Typical BMP 

Use

Required 

Equipment

Volume-Based ß Low flow rates ß Calibrating 

equipment

ß Manual 

sampling

Container and 

stopwatch

Stage-Based 

Empirical 

Equations

ß Open flow

ß Known 

channel/pipe 

slope

ß Channel slope, 

geometry, 

roughness 

consistent 

upstream 

ß Manual or 

automatic 

sampling

Depth Measurer

Stage-Based 

Weir/Flume

ß Open flow

ß Constraint will 

not cause 

flooding

ß Manual or 

automatic 

sampling

Weir/flume and 

depth measurer

Stage-Based 

Variable Gate 

Meter

ß 4-, 6-, or 8-inch 

pipes only

ß Not typically 

used for 

BMPs

ISCO Variable 

Gate Meter

Velocity-Based ß None ß Automatic 

sampling

Depth measurer 

and velocity 

meter

Tracer Dilution ß Adequate 

turbulence and 

mixing length

ß Typically used 

for calibrating 

equipment

Tracer and 

concentration 

meter

Pump-Discharge ß All runoff into 

one pond

ß Not typically 

used for BMPs

Pump
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Volume-Based Methods

The concept behind volume-based flow measurement is simple: one collects all the flow over a

short period of time, measures the volume, and divides the collected volume by the length of the 

time period: 

Q = V/T Equation 3.7

where,

Q: flow, m3/s (ft3/s)

V: volume, m3 (ft3)

T: time, s

A stopwatch can be used to measure the period required to fill a receptacle of known quantity to 

a predetermined level. The receptacle must be large enough that it requires some accurately

measurable period of time to fill. The receptacle could be a bucket, a drum, or a larger container 

such as a catch basin, holding tank, or some other device that will hold water without leakage

until the measurement is made.

This method is easy to understand, requires relatively simple equipment, and can be very

accurate at low rates of flow. At higher rates of flow, collection of all the runoff from typical

BMP conveyances (an essential component of the method) will probably become infeasible. 

This method is most useful for conducting limited research and for calibrating equipment. 

Stage-Based Methods

Flow rate can be estimated from the depth of flow (i.e., water level or stage) using wellunderstood, empirically derived mathematical relationships. That is, for a set hydraulic

configuration, the relationship between stage and flow is known. The most commonly used

empirical relationship, the Manning Equation, is appropriate for open channels in which flow is

steady-state (i.e., the flow rate does not vary rapidly over time) and uniform (the depth of flow

does not vary over the length of the channel) (Gupta 1989). In automated stormwater sampling

the Manning Equation is commonly used to estimate the flow rate of the flow stream. 
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Manning’s Equation

The variables required for the Manning Equation (Equations 3.8 and 3.9) are the slope of the

energy grade line (usually assumed to be the slope of the channel bottom), the cross-sectional 

area of the flow, the wetted perimeter, and an empirical roughness coefficient, which takes into

account channel material, age, and physical condition.

1 1.486 Q =

n

AR2/3S

1/2 Q =

n

AR2/3S

1/2

Equation 3.8 Equation 3.9

where,

Q: flow, m3/s

n: Manning roughness coefficient 

(dimensionless)

A: cross sectional area, m2

R: hydraulic radius, m = A/(wetted 

perimeter)

S: slope of the channel, m/m

where,

Q: flow, ft3/s

n: Manning roughness coefficient 

(dimensionless)

A: cross sectional area, ft2

R: hydraulic radius, ft =A/(wetted perimeter)

S: slope of the channel, ft/ft

The Manning Equation truly applies only to steady and uniform flow but can provide a

fairly accurate estimate of flow rates if certain conditions are met. The channel slope and 

cross-sectional geometry must be constant for some distance upstream of the site, the

exact distance varying with overall system hydraulics (a rule of thumb is a length of

twenty channel diameters upstream). Flow conditions at the site should not be affected

by downstream features (i.e., no backflow effects). The cross-sectional area and wetted

perimeter are both geometric functions of the channel shape and the depth of flow. The

“roughness” of the conveyance walls can be described by a roughness coefficient. 

Additional information on applicability and values for Manning's roughness coefficients

for common channel types are provided in most hydraulics texts (Chow 1959; Gupta

1989).

Use of the Manning Equation assumes that the slope of the channel bottom is accurately

known. Monitoring studies using this technique to estimate flow rates often rely on asbuilt drawings to determine channel slope. Because these drawings vary in accuracy, 

direct measurement of the slope of the channel bottom and verification of hydraulic

conditions is recommended.

The flow rate of stormwater runoff tends to be unsteady. This is due to changes in the

intensity of precipitation and the dynamic nature of overland flow, which causes the flow 

rate to vary with time, either gradually or rapidly. Depending on the frequency with
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which the depth of flow is measured, rapid fluctuations in flow rate will be missed and

the total runoff volume from a storm event will be miscalculated.

Other Empirical Stage-Flow Relationships

Another empirical relationship used to estimate flow is the Chézy Equation (Gupta 

1989):

Q / A = C RS Equation 3.10

where,

Q: flow, m3/s (ft3/s)

A: cross-sectional area, m

2

 (ft2)

R: hydraulic radius, m (ft)

S: slope of the energy grade line, m/m (ft/ft)

C: flow coefficient, m1/2/s (ft1/2/s)

Under open channel flow, the coefficient “C” can be defined as:

n

R

C

1/ 6

= Equation 3.11

where,

n: Manning’s Roughness Coefficient

When “C” is substituted into Chézy’s Equation, the resulting Equation is identical to the 

Manning Equation. 

A failure of both the Manning and Chézy Equations is that they imply that the Manning

“n” value is constant for a given channel. However, it is known that for natural channels 

“n” may vary greatly with respect to flow (Ponce 1989). Therefore, when considering

applying these equations to a natural channel, one should first evaluate the alluvial

material in the channel and the magnitude of flows expected. It may be desirable to

select another flow measurement approach for natural channels with highly varied

surfaces and flow rates.

Stage Based Method Using Weirs and Flumes

The accuracy with which flow is estimated can be improved by using a weir or flume to

create an area of the channel where the hydraulics is controlled (control section). Each

type of weir or flume is calibrated (i.e., in the laboratory or by the manufacturer) such

that the stage at a predetermined point in the control section is related to the flow rate

using a known empirical equation (for examples, see Stevens 1991). 
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Stage-Based Variable Gate Meters

A relatively new development in flow metering technology is ISCO Inc.’s (Lincoln, NE) 

Variable Gate Metering Insert. Discharge flows through the insert and under a pivoting

gate, creating an elevated upstream level that is measured with a bubbler system. The

meter uses an empirical relationship to calculate the discharge rate based on the angle of

the gate and the depth of flow upstream of the gate. This approach can be used only

under conditions of open channel flow in circular pipes. Currently the system is only

available for pipe diameters of 10.16, 15.24, and 20.32 cm (4, 6, and 8 inches). The

Variable Gate Metering Insert was designed to measure the flow rate under fluctuating

flows and should be effective at both very high and very low flow rates. Its main

limitation is the size of the conveyance for which it is designed. The insert may be useful 

for sampling very small catchment areas. Again, problems with debris accumulation can 

occur. 

Velocity-Based Methods

The continuity method is a velocity-based technique for estimating flow rate. Each

determination requires the simultaneous measurement of velocity and depth of flow.

Flow rate is calculated as the sum of the products of the velocity and the cross-sectional 

area of the flow at various points across the width of the channel:

Q = Ai *Vi Equation 3.12

where,

Q: flow, m3/s (ft3/s)

Ai: cross-sectional area of the flow at section i, m2 (ft2)

Vi: mean velocity of the flow at section i, m/s (ft/s)

The sections i = 1-n are planar segments of a cross-section of the flow where n is the

number of points across the width of the channel. In stormwater runoff applications, the

conveyance is small enough that a single cross-sectional area and estimate of average

velocity is typically used to estimate flow rate. That is, it is not necessary to segment the 

cross-sectional area of the flow. The accuracy of this method is dependent on the ability

of a sensor to measure velocity over a range of flow.

Although this method is useful for calibrating equipment, it is more sophisticated and

expensive than the stage-flow relationships previously discussed. In addition, this

method is suitable only for conditions of steady flow. That is, water level must remain

essentially constant over the period required for obtaining velocity measurements. This

is not generally a problem in small conveyance systems when instruments that make

measurements rapidly are employed. 

Additional relationships, developed for pipes that are flowing full, are the DarcyWeisbach equation and the Hazen-Williams equation. These equations are used in
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systems where pressurized flow (i.e., pipes flowing full; no free water surface) is present 

and can be found in Gupta (1989).

Tracer Dilution Methods

Tracer dilution methods can be used where the flow stream turbulence and the mixing

length are sufficient to ensure that an injected tracer is completely mixed throughout the

flow stream (USGS 1980; Gupta 1989). Tracers are chosen so that they can be

distinguished from other substances in the flow. For example, chloride ion can be

injected into fresh water, and dyes or fluorescent material can be used if turbidity is not

too high.

Dilution studies are well suited for short-term measurements of turbulent flow in natural

channels and in many manmade structures such as pipes and canals. However, these

methods are better suited to equipment calibration than to continuous monitoring during a 

storm event. Two dilution methods can be used to determine flow rate as described

below. 

Constant Injection Rate Tracer Dilution Studies 

A known concentration of tracer is injected at a constant rate into a channel. The

concentration of the tracer in the flow is measured at a downstream point over time. 

After some time period has passed, the tracer becomes completely mixed in the flow so

that the downstream concentration reaches steady state. Flow is calculated from the

initial tracer concentration, the tracer injection rate, and the steady-state downstream

concentration. 

Total Recovery Tracer Dilution Studies

A discrete “slug” of tracer is injected into the channel. Near-continuous measurements of 

tracer concentration in the flow are taken at a downstream point until the plume has

entirely passed. Flow is calculated from the volume and concentration of injected tracer

and the total area under the concentration-time curve.

Pump Discharge Method

In some cases, the overall discharge rate for a catchment may be measured as the volume 

of water that is pumped out of a basin per unit time while holding the water level in the

basin constant. This method can be applied at sites where flow runs into a natural or

manmade basin from several directions or as overland flow. If the pump is precalibrated,

the number of revolutions per minute, or the electrical energy needed to pump a given

volume, may be used as a surrogate for measuring the pumped volume during a

stormwater runoff event. Application of this method requires considerable knowledge of 

the installed pump's performance. Because this setup (i.e., all of the runoff from a

catchment flows into one pond or basin which can be pumped out) is not usually
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encountered in the field as the only available monitoring method, pumps are not

discussed further in this manual.

3.2.4.2 Automatic Sampling Techniques

Selection of Primary Flow Measurement Device

This section provides an overview of the process of selecting a primary flow

measurement device.

Changes to surface hydrology due to urbanization result primarily from the increases in

impervious areas (roofs, streets, parking lots, etc.) and the increased hydraulic

conveyance of the flow channels. The naturally occurring channels are often

straightened, deepened, and lined in addition to the installation of storm sewers, drains,

and gutters. Without detention storage, the resulting hydrograph has a higher peak

discharge and shorter duration. This necessitates the ability of a primary flow device to

accurately measure large discharge rates for storm events with high precipitation

intensities. Due to the highly variable nature of storm events, low runoff rates will result 

from the smaller storm events. Analysis of long-term rainfall records indicates that 

smaller storm events generally account for the majority of stormwater runoff and

resulting pollutant loads. Therefore it is essential that the primary device selected is also 

capable of accurately measuring the lower range of the expected flows. The potential for 

a wide range of flow rates resulting from stormwater runoff makes the assessment of the 

required range of discharge rates an important consideration for selection of a flow

measurement device.

Flow measurements are critical to monitoring stormwater BMPs. Accurate flow

measurements are necessary for accurate composting of samples used to characterize

storm runoff and for the estimation of volumes (including pollutant loads) treated in the

BMP. Many methods are available to estimate the flow in open channels: volume-based 

methods, velocity-based methods, empirical equations, and tracer-dilution methods. 

While these methods are all valid ways to measure the flow in open channels, they are

not potentially as accurate as the use of a primary flow measurement device. Researchers 

monitoring flows pertaining to stormwater BMP effectiveness are encouraged to use

primary flow devices where possible. 

Types of Primary Flow Measurement Devices 

Primary flow measurement devices fall into the general categories of flumes and weirs. 

Primary flow measurement devices allow for accurate measurement of discharge rates by

creating a channel geometry in which the hydraulics are controlled (control section). 

Primary devices are calibrated (i.e., in the laboratory or by the manufacturer) to relate the 

stage at a predetermined point in the control section to the discharge rate using a known

empirical equation (for examples, see Stevens 1998). These types of measurement 

devices are called depth (or stage) based methods because the discharge through the

device is directly related to the depth (stage or head) of the flow. The relationship
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between the depth of flow and the discharge is called the rating. Tables referred to as

rating curves are available for all standard flumes and weirs. 

Weirs

A weir is an obstruction (usually a vertical plane) built or placed across an open channel

(or within a pipe under open channel flow) so that water flows over the weir's top edge or 

through a well-defined opening in the plane. Many types of weirs can be used to measure 

discharge; the three most common are the rectangular, trapezoidal (or Cipolletti weir),

and triangular weirs. The weir opening (i.e., the rectangular, trapezoidal, or triangular

opening) is called the “notch.” Each type of weir has a specific discharge equation for

determining the flow rate through the weir.

Weirs are generally low in cost, easy to install (relative to flumes), and can be quite

accurate when used correctly. A weir can be used to regulate flow in a natural channel

with irregular geometry, a situation where Manning’s Equation, for example, would not

provide reliable estimates for the flow rate. However, a weir will back water up in

channels by creating a partial dam. Weirs are generally used for flow measurements with 

relatively large head available to establish free-flow conditions over the weir. A weir is

intended to back up water by creating a partial dam. During large storm events, backedup water could cause or worsen flooding upstream, particularly in a closed conduit. 

Some jurisdictions prohibit the use of weirs for this reason. When evaluating the

suitability of a monitoring site for a weir, it is important to determine whether the system 

was “over designed.” That is, will the conveyance be able to move the design capacity

after weir installation. In the case where the downstream depth of flow is greater than the 

crest of the weir, a different stage-flow relationship for the weir will apply.

Sediments and debris that accumulate behind a weir can alter the hydraulic conditions,

changing the empirical relationship between flow depth and discharge rate. Weirs are

often not a good choice where representative suspended sediment samples are desired. 

Weirs should be inspected regularly and accumulated sediment or debris removed. If

high amounts of sediment or debris occur in the flow, then use of a flume may be more

appropriate as they generally avoid sedimentation problems.

Flumes

A flume is a specially built reach of channel (sometimes a prefabricated insert) with a

converging entrance section, a throat section, and diverging exit section. 

Because the velocity of water accelerates as it passes through a flume, the problem of

sedimentation associated with weirs (see below) is avoided; however, problems with

debris accumulation may still occur. Another benefit is that flumes introduce a lower

headloss than weirs, resulting in a reduced backwater effect. A flume may be more

expensive and difficult to install than a weir due to its more complex design; however,

where applicable, flumes can provide accurate results and significantly reduced

maintenance.
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The most common types of flumes are the Parshall, the Palmer-Bowlus, the HS, H, and

HL flumes and the trapezoidal flume.

Figure 3.6: Parshall flume (Plati-Fab Inc.)

The area or slope (or both) of the flume is different from that of the channel, causing an

increase in water velocity and a change in the level of the water flowing through the

flume (Grant 1989). Stage-flow relationships have been established for a variety of

flume configurations (USGS 1980; Gupta 1989; Stevens 1991). 

Figure 3.7: H-flume (Tracom Inc.)
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Considerations for Selection of Primary Flow Measurement Device

Consideration should be given to the following items when selecting a primary flow

measurement device.

Range of Flows 

Triangular thin-plate weirs have a large range in their ability to measure flows because of 

the 2.5-power relationship between flow depth and flow rate. That is, relative to other

devices, flow increases quite rapidly as a function of head. The range of flow rates that

can be measured accurately can vary by a factor (ratio of largest flow to smallest flow

rate) of 200 for fully contracted weirs to around 600 for partially contracted 90o notches 

that can utilize the allowable range of head (ASTM 1995).

For rectangular thin-plate weirs, the range is typically about a factor of 90 and increases

to about 110 for full-width weirs. These ranges depend somewhat on the crest length to

channel width ratio. These results are based on a minimum head of 0.1 ft (0.03 m) and a 

suggested (although not absolute) maximum head of 2 ft (0.6 m). However, the rangeability of smaller rectangular weirs can be significantly less (ASTM 1995). 

The range in flow measurement for Parshall flumes varies widely with size. The range of 

Palmer-Bowlus and other long-throated flumes depends on the shape of the throat crosssection and increases as the shape varies from rectangular toward triangular. For typical

Palmer-Bowlus flumes of trapezoidal section, the range of flow rates that can be

measured accurately generally varies by a factor of 30. The USGS has developed and

tested a modified Palmer-Bowlus flume (USGS 1985) for use in circular pipes that carry

highway stormwater runoff. This flow can occur under either open or pressurized

channel flow. This flume has been designed to measure the discharge under pressurized

flow by using two bubbler sensors, which detect the hydraulic pressure change between

upstream and downstream locations on the flume. This system was found to be one of

the most accurate after calibration is performed. However the range between low and

high flows that can be measured accurately using a Palmer-Bowlus flume is not as large

as some other types of devices.

In cases in which there is a need for measurement of extreme flow ranges along with

sediment transport capability, which is often the case for stormwater runoff, the H, HS, or 

HL flumes should be considered. The range of flows that can be measured accurately

using H-type flumes can exceed three orders of magnitude; for example, a 3 ft H flume

can measure flows between 0.0347 cfs at 0.10 ft of head to 29.40 cfs at 2.95 feet of head.

For some cases when low flows are expected to occur for an extended period but will

ultimately be superseded by much larger flow rates, the interim use of removable small

flumes inserted inside larger flumes can provide a method for accurate measurement of

the range of flows.
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Flow Rate 

As mentioned in the beginning of the section, one of the most important factors

influencing the selection of a primary device is the flow capacity necessary to

accommodate runoff. Small and moderate flows are generally best measured with thinplate weirs, with the triangular notches most appropriate for the smallest flows (ASTM

1995). Small Parshall and Palmer-Bowlus flumes are also available to measure low

flows. The flumes do not have issues related to sediment passage and head loss as do

thin-plate weirs, but this comes at some sacrifice in potential accuracy (ASTM 1995). 

Flumes and broad-crested weirs are generally the best choices for the measurement of

large discharges. 

Accuracy

Weirs are generally recognized as more accurate than flumes (Grant and Dawson 1997). 

A properly installed weir can typically achieve accuracies of 2 to 5% of the rate of flow,

while flumes can typically achieve accuracies of 3 to 10% (Spitzer 1996). The ASTM

cites lower errors for weirs ranging from about 1 to 3% and Parshall and Palmer-Bowlus 

flumes with typical accuracies around 5%. However, the overall accuracy of the flow

measurement system is dependant on a number of factors, including proper installation,

proper location for head measurement, regular maintenance, the accuracy of the method

employed to measure the flow depth, approach velocities (weirs), and turbulence in the

flow channel (flumes). It should be noted, however, that the largest source of error in

flow measurement of stormwater results from inaccuracies related to low flow or

unsteady flow. Improper construction, installation, or lack of maintenance can result in

significant measurement errors. A silted weir or inaccurately constructed flume can have 

associated errors of ±5 to 10% or more (Grant and Dawson 1997). Circumstances present 

in many stormwater monitoring locations can result in errors well in excess of 100%.

Potential inaccuracies in the method used to measure the depth of flow will tend to

increase the error in flow measurement as the flow depth approaches the minimum head. 

For primary devices operating near minimum head, even a modest error can have a

significant effect on the measured flow rate. Therefore, it is important to select sizes or

combinations of primary devices that avoid prolonged operation near minimum head

(Spitzer 1997). 

Cost

The important factor of cost consideration should include manufacturing, installation, and 

operational costs. Weirs are often considerably less expensive to fabricate than flumes

due to simpler design and material requirements (Grant and Dawson 1997). Weirs are

also usually easier and less expensive to install, although installation of flumes designed

for insertion into a pipe (e.g. Palmer-Bowlus and Leopold-Lagco) are generally

straightforward. Despite the higher initial costs of flumes, the relatively low maintenance 

requirements may outweigh this with time (Grant and Dawson 1997). Consideration
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should be given to the expected sediment loads in the flow to be measured for likely

accumulation and maintenance requirements for weir installations.

Head Loss and Flow Characteristics

The head difference that is required for a weir or flume to operate properly may be an

important selection criterion. Examples include, when the elevation difference is not

adequate to maintain the required flow or when the upstream channel cannot contain the

backwater.

For the same flow conditions, thin plate weirs typically require the largest head

difference, Parshall flumes require an intermediate amount of head, and the long-throated 

flumes require the least (ASTM 1995).

Weirs are typically gravity fed and must be operated within the available head of the

system. Flumes also require a certain head range in which the discharge liquid level is

low enough that it does not exert back pressure on the liquid in the throat of the flume, 

otherwise the flume will be in a submerged condition, and two head measurements will

be required to determine the flow rate. 

Operation of a weir is sensitive to the approach velocity, often necessitating a stilling

basin or pond upstream of the weir to reduce the fluid velocity. Operation of a flume is

sensitive to turbulence or waves upstream from the entrance to the flume, which can

require a section of straight channel upstream of the flume.

Sediment and Debris 

Flumes tend to be self-cleaning because of the high flow velocity and the lack of any

obstruction across the channel (Spitzer 1997). A flume is therefore generally more suited 

to flow channels carrying solids than is a weir. 

Debris accumulation is likely to occur behind a weir especially due to the presence of a

stilling basin to reduce flow velocities to an acceptable rate. Debris accumulation behind 

a weir can affect flow measurement. This requires periodic inspection and maintenance

to remove debris. To allow periodic removal of deposits, it is recommended that the weir 

bulkhead be constructed with an opening beneath the notch to sluice accumulated

sediments (Spitzer 1997). 

Flumes, while typically not susceptible to problems due to sedimentation, can have debris 

accumulate in the throat portion of the flume and require periodic maintenance (although 

generally less frequently than weirs).

Construction Requirements

The Parshall flume is usually the most difficult device to construct due to the relatively

complex shape and the possible need to excavate the channel floor to accommodate the

sharp downward slope of the throat. Because this flume is an empirical device it is
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necessary to closely follow the design specifications (ASTM 1995). The discharge

coefficients for long-throated flumes can be obtained theoretically which allows for some 

departure from the prescribed dimensions. Many types of flumes are available in

prefabricated sizes up to several feet in width.

Weirs are generally easier to construct than flumes. The most difficult task is the

fabrication of the notch edges, which require a sharp edge so the nappe is free flowing.

Selection of Secondary Flow Measurement Device

A variety of instruments may be used to measure water depth. Because some techniques 

are relatively cumbersome, they are more useful for calibrating equipment than for

routine or continuous data collection during storm events. The equipment required for

each technique and the associated advantages and disadvantages for sampling runoff at

BMP sites are described below. Table 3.3 summarizes available equipment for

measuring depth of flow, major requirements for use, and typical use within a BMP

monitoring program.

Table 3.3: Equipment for measuring depth of flow

Method Major Requirements For Use Typical Use in a BMP Monitoring

Program

Visual Observations Small number of sites and events to 

be sampled.

No significant health and safety 

concerns

Manual sampling

Float Gauge Stilling well required Manual or automatic sampling

Bubbler Tube Open channel flow.

No velocities greater than 5 ft/sec

Automatic sampling

Pressure Transducer Better if remains submerged Automatic sampling

Ultrasonic Depth Sensor Open channel flow.

No significant wind, loud noises, 

turbulence, foam, steam, or floating 

oil & grease

Automatic sampling

Ultrasonic Uplooking No sediments or obstructions likely

to cause errors in measurement.

Automatic sampling

Radar/Microwave Similar to Ultrasonic Depth Sensor

but can see through mist and foam

Automatic sampling

3-D Point Measurement Highly controlled systems. 

Typically not useful in the field

Automatic sampling

Pressure Probe Open channel flow.

No organic solvents or inorganic 

acids & bases

Automatic sampling
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Float Gauge

A float gauge consists of a float that is free to move up and down in response to the rising and

falling water surface in a channel. Prior to an actual stormwater sampling event, the site is

calibrated to establish an initial reference depth. During the storm, the float rises and falls with

changes in water surface elevation, and a device attached to the float records the magnitude of

these changes. The changes in water surface elevation are converted to depth of flow by the float 

gauge. A data logger can record the depth of flow, and if capable of performing mathematical

equations, can also determine the flow rate. The data can also be used as input to appropriate

software to compute the flow rate.

In some applications, use of a float gauge requires a stilling well. A stilling well is a reservoir of 

water connected to the side of the conveyance that isolates the float and counterweight from

turbulence in the main body of the flow. The need to retrofit an existing channel or conduit with 

a stilling well, a potentially expensive and time-consuming process, is the principal drawback of 

this technique. However, this method may be useful if sampling is conducted at a site where a

float gauge and stilling well have previously been installed.

Bubbler Tube

Bubbler tubes are used by some types of automated flow meters to measure the depth of flow. 

Compressed air (or gas) is forced through a submerged tube attached to the channel invert (i.e.,

bottom of the channel). A pressure transducer measures the pressure needed to force a bubble

out of the tube. This pressure, in turn, is linearly related to the depth of the overlying water:

P = ρh Equation 3.13

where:

P: hydrostatic pressure, N/m2 (lb/ft2)

ρ: specific weight of water, N/m3 (lb/ft3)

h: depth of water, m (ft)

Bubbler tubes are commonly integrated with a flow meter, or a data logger that is capable of

performing mathematical calculations. This approach allows the measurement of depth to be

immediately converted to a flow. These real-time inputs along with a program that tracks

accumulated flow volumes can be used to trigger the collection of samples for flow-weighted 

compositing by an automated sampler. 
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Figure 3.8: Bubbler flow meter (ISCO)

Bubbler tubes are simple to use and are not usually affected by wind, turbulence, foam, steam, or 

air-temperature gradients. Accuracy is not lost under dry conditions in a conveyance between

runoff events (some other types of probes must remain submerged). Although they are generally 

reliable, bubblers are susceptible to error under high velocity flow. That is, as flow velocity

increases to over 1.5-1.8 m/s (5-6 ft/s), a low pressure zone is induced around the mouth of the

bubbler tube, interpreted by the flow meter as a drop in flow rate. These instruments therefore,

should not be used in channels where the slope of the bottom exceeds 5-7 percent. Sediments

and organic material can also plug bubbler tubes. Some units are periodically purged with

compressed air or gas to prevent this problem, but visual inspection and periodic maintenance

are recommended for any unit installed in the field. Bubblers are commonly available in

integrated systems, such as those manufactured by ISCO and American Sigma, but are also sold

as independent devices.

Ultrasonic Depth Sensor

An ultrasonic depth sensor consists of a sonar-like device mounted above the surface of the

water at a known distance above the bottom of the channel. A transducer emits a sound wave

and measures the period of time taken for the wave to travel to the surface of the water and back 

to a receiver. This time period is converted to a distance and then converted to a depth of flow,

based on measurements of the site configuration. As with bubbler tubes, an ultrasonic sensor can 

be integrated into a flow meter or interfaced with a data logger. An ultrasonic depth sensor and

data logger can provide the real-time flow data necessary to trigger an automated sampler to

collect a stormwater sample for flow-weighted compositing.
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Figure 3.9: Ultrasonic-depth sensor module (ISCO)

Some manufacturers have built redundancy into their ultrasonic depth-measuring instruments. 

Redundancy helps to ensure that useful data will be collected even if some of the sensors in the

array become fouled with grease, surface-active materials, or organisms. Experience has shown

that this type of fouling can occur during storm events. Because an ultrasonic sensor is mounted 

above the predicted surface of the water, it is not exposed to contaminants in the runoff (unless

the depth is greater than anticipated or installed in a pipe that reaches fully pressurized flow). 

However, ultrasonic signals can be adversely affected by wind conditions, loud noises,

turbulence, foam, and steam, and they will require periodic inspection and maintenance. 

Ultrasonic signals can also be affected by changes in density associated with air temperature

gradients; however, some manufacturers build a compensation routine into their instruments. 

Background noise can interfere with a sensor's ability to accurately measure water depth. For

example, an ultrasonic sensor was used in Portland, Oregon to measure the depth of flow at an

urban stormwater sampling site located in a manhole, in which runoff from an arterial pipe

splashed down into the main conveyance. To dampen the effect of the interfering signal, the

ultrasonic sensor was retrofitted with a flexible noise guard.

Pressure Probe

A pressure probe consists of a transducer, mounted at the bottom of the channel, that measures

the hydrostatic pressure of the overlying water. This hydrostatic pressure is converted to a depth 

of flow. Some pressure probes have a built-in thermometer to measure the temperature of the

water, allowing for temperature compensation in the depth of flow calculation. As with bubblers 

and ultrasonic probes, the pressure probe can be integrated into a flow meter or interfaced with a 

data logger to provide real-time inputs to an automated sampler. If the instrument is fitted with a 

thermometer, the temperature data used for compensation can possibly also be input to memory

and retrieved as additional useful data.
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Figure 3.10: Pressure transducers (In-Situ Inc.)

Submerged probes are not adversely affected by wind, turbulence, foam, steam, or air

temperature gradients. However, because contaminants in the water may interfere with or

damage the probe, periodic inspection and maintenance is recommended. Dry conditions

between storms can affect the accuracy of the probe, as can sudden changes in temperature.

Ultrasonic “Uplooking”

This depth of flow sensor is mounted at or near the bottom of the channel or pipe. It uses

ultrasonic signals to determine the depth of the flow. This sensor is very accurate unless

interference occurs. However, according to a vendor, this equipment is not recommended for

stormwater applications because the sensor is likely to become covered by sediments and debris. 

This then interferes with the signal and does not allow the sensor to work properly. 

Radar/Microwave

A variation of the ultrasonic method is a non-water contacting instrument that emits and

reprocesses electromagnetic waves in the radar/microwave spectrum. By altering the wavelength 

of the electromagnetic signal, problems associated with foam, mist, and rapid changes in air

temperature and pressure are eliminated or significantly reduced.

A radar/microwave sensor is used in the same manner as an ultrasonic “downlooking” sensor for 

measuring fluid levels in tanks. Based on experience, this device does not present a significant

advantage over other methods of level measurement, since foam and mist are not typically a

large concern during stormwater monitoring. 

Radar/microwave sensors have not been extensively tested by manufacturers for this type of

application, and there is no existing literature that shows them being used for stormwater

monitoring. 
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Equipment for Measuring Velocity

Use of the continuity equation for measuring flow requires the estimation of average velocity as 

well as depth. The velocity of flow may be measured using visual methods (i.e., the float-andstopwatch and the deflection, or drag-body methods), tracer studies, the use of instruments such

as rotating-element current meters and pressure, acoustic, ultrasonic (Doppler), and

electromagnetic sensors. Electromagnetic sensors have been found to be the most accurate. 

Among these methods, many are more useful for the calibration of automated equipment than for 

continuous data collection. Only the ultrasonic and electromagnetic methods are recommended

for measuring velocity during a storm. In the following text, velocity measurement methods

potentially suitable for calibration are described (more details are available in USGS 1980). 

More extensive discussions, including advantages and disadvantages related to sampling

activities, are provided for the ultrasonic and electromagnetic sensors.

Methods Suitable for Calibration

The most important aspect of any calibration method is its ability to obtain accurate results with

a high degree of certainty and repeatability. A variety of methods have been employed in the

past. The most common methods are described in this section. Table 3.4 summarizes the

available methods.

Table 3.4: Velocity measurement methods suitable for calibration

Method Comments

Tracer Studies Recommended Method. Where applicable, one 

of the best calibration methods. Requires 

complete mixing of tracer with flows.

Rotating-Element Current Meters Useful for larger flows that do not rapidly vary 

with time. Typically useful for large systems 

with appreciable flows. Low flows are difficult to 

monitor. 

Pressure Sensors Not useful for velocities above 1.5-1.8 m/sec or 

in pipes with steep slopes (>5%).

Acoustical Sensors Not applicable to most monitoring locations. 

Large flow rates are typically required. Base flow 

required to observe complete storm hydrograph. 

Typically applicable only to large channels.

Float-and-Stopwatch Rarely accurate enough for calibration purposes. 

Not recommended for most situations.

Deflection (or Drag-Body) 

Method

Rarely accurate enough for calibration purposes. 

Not recommended for most situations.
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Tracer Studies

Tracer methods have been developed to measure flow velocity under uniform flow (USGS

1980). As described in the flow measurement methods section, for Total Recovery Tracer

Dilution studies, a discrete slug of tracer is injected into the flow. Concentration-time curves are 

constructed at two downstream locations. The time for the peak concentration of the dye plume 

to pass the known distance between the two locations is used as an estimate of the mean velocity 

of the flow. This method is not practical for continuous flow measurement, but is useful for site 

calibration.

Rotating-Element Current Meters

A current meter or current meter array can be used to measure the velocity at various points

throughout a flow stream. The measured point velocities can be combined to estimate a mean

velocity for the flow. As with the deflection or drag-body method, if employed for longer

periods, a current meter inserted into the flow will accumulate debris causing it to malfunction

and possibly break away. This method should therefore only be used for short-term 

measurements such as during equipment calibration or to develop a rating curve. Two types of

readily available instruments that meet USGS standards are the type AA Price and Pigmy current 

meters. 

Pressure Sensors

A pressure sensor or transducer measures the dynamic pressure head at a given point in the flow. 

The dynamic pressure is a measure of the point velocity and can be used to estimate the mean

velocity of the flow. A common example of a pressure sensor is the pitot tube used on an

airplane or on some boat speedometers.

The same caution described for bubbler tubes must be applied to pressure sensors. That is, as the 

velocity of the flow increases above 1.5-1.8 meter/second (5-6 feet/second), a low pressure zone

is induced across the sensor, interpreted by the flow meter as a drop in flow rate. These

instruments should not be used in channels where the slope of the bottom exceeds 5 to 7 %. 

Acoustical Sensors

An acoustical sensor emits a sound wave under water across a channel and measures the time

required for the signal's return. Transit time is correlated with channel width. The relative

positions of the emitting and receiving sensors are used to estimate velocity. A minimum depth 

of flow is required. This type of sensor can only be used at sites with sufficient base flow to

provide the medium in which the sound wave travels. If there is no base flow, the lower portions 

of the rising and falling limbs of the hydrograph will be lost.
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Float-and-Stopwatch Method

In this method, the time it takes for a float to move a known distance downstream is determined. 

Velocity is calculated as the distance traversed divided by the travel time. The characteristics of 

a good float are: an object that floats such that it is partially submerged, allowing some

averaging of velocity above and below the surface of the water; an object that is easily observed

and tracked; an object that is not easily affected by wind; and an object that does not cause

problems if not recovered. Citrus fruits such as oranges, limes, or lemons are commonly used as 

floats. Ping-pong and styrofoam balls float well but are too light and are easily blown by the

wind (they may also pose environmental problems if not recovered).

In a variation of this method, a vertical float with a weighted end is used. The vertical float

provides a better measure of mean velocity over the depth of the water column than a float

moving primarily at the surface. In addition, it can be designed to minimize bias due to wind.

In most cases, this method is not accurate enough to be of significant utility in stormwater

monitoring studies and is particularly inaccurate for very deep systems and where there is a

significant difference in velocity across the water surface (e.g., in natural channels). 

Deflection (or Drag-Body) Method

In this method, the deflection or drag induced by the current on a vane or sphere is used as a

measure of flow velocity. This method is only practical for short-term, real-time measurements, 

such as equipment calibration, because an object of this size inserted into the flow will

accumulate debris, causing it to change the hydraulic form, provide inconsistent data, and

(possibly) break away. 

Methods Most Suitable for Continuous Velocity Monitoring

Ultrasonic (Doppler) Sensors

An ultrasonic sensor applies the Doppler principle to estimate mean velocity. A sound wave,

emitted into the water, reflects off particles and air bubbles in the flow. The shift in frequency of 

waves returning to the sensor is a measure of the velocity of the particles and bubbles in the flow 

stream. The instrument computes an average from the reflected frequencies, which is then

converted to an estimate of the average velocity of the flow stream. 
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Figure 3.11: Area velocity sensors module (ISCO)

The sensor is mounted at the bottom of the channel. However, because the ultrasonic signal

bounces off suspended particles, the signal may be dampened (i.e., not able to reach portions of

the flow stream) when suspended solids concentrations are high. The sensor may also be

mounted on the side of the channel, slightly above the invert. Combined with the appropriate

hardware and software, the sensor can filter out background signals associated with turbulence in 

the flow.

Ultrasonic Doppler sensors can be used under conditions of either open channel or pressurized

flow. When combined with the hardware and software required for real-time flow measurement, 

data logging, and automated sampling, and when properly calibrated, this system is capable of

greater accuracy than one relying on a stage-flow (i.e., Manning’s Equation) relationship. The

ultrasonic sensor-based system may be more expensive but the additional expense may be

justified by program objectives. Without routine maintenance, the accuracy of ultrasonic sensors 

may decrease due to fouling by surface-active materials and organisms. 

Electromagnetic Sensors

Electromagnetic sensors work under the principle stated in Faraday's Law of electromagnetic

induction; that is, a conductor (water) moving through an electromagnetic field generates a

voltage proportional to its velocity. This instrument, mounted at or near the channel bottom,

generates the electromagnetic field and measures the voltage inducted by the flow. Although

velocity is measured at only a single point, that measurement is used to estimate the average

velocity of the flow stream. 

Electromagnetic sensors can be pre-calibrated for many types of site configurations. The sensor

is usually mounted at the channel invert but can be mounted on the side of a channel, slightly

above the invert, if high solids loadings are expected. A built-in conductivity probe senses when 

there is no flow in the conveyance. 

These types of instruments are not sensitive to air bubbles in the water or changing particle

concentrations, as is the ultrasonic sensor, but can be affected by extraneous electrical “noise.” 

As with the ultrasonic system, when an electromagnetic sensor is combined with the hardware

and software required for real-time flow measurement, data logging, and automated sampling,

and when properly calibrated, it may be capable of greater accuracy in specific circumstances

than a system relying on a stage-discharge relationship. On the other hand, the electromagnetic
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sensor-based system may also be more expensive, but the additional expense may be justified by 

program objectives. 

Acoustic Path

These sensors are used to determine the mean velocity of streams and rivers, and where they are 

applicable, they have been found to be one of the most accurate flow measurement systems. The 

method consists of an array of sensor elements that are installed at an even elevation across the

channel. The number of sensor elements used is dictated by the channel width (larger channels

require more sensors). Due to the sensor array’s height above the channel bottom, its use is

generally limited to larger channels that have a base flow present. It is not practical for smaller

diameter conveyances with no base flow, which may be found at a BMP site. Additionally,

stormwater conduits for BMP runoff can be small enough that a single point measurement for

velocity provides a reasonable estimate for the average velocity. For these reasons, acoustic path 

sensors are rarely applicable to BMP monitoring situations. 

Water Quality Sample Collection Techniques

Grab Samples

The term “grab sample” refers to an individual sample collected within a short period of time at a 

particular location. Analysis of a grab sample provides a "snapshot" of stormwater quality at a

single point in time. Grab samples are suitable for virtually all of the typical stormwater quality

parameters. In fact, grab samples are the only option for monitoring parameters that transform

rapidly (requiring special preservation) or adhere to containers, such as oil and grease, TPH, and 

bacteria. 

The results from a single grab sample generally are not sufficient to develop reliable estimates of 

the event mean pollutant concentration or pollutant load because stormwater quality tends to

vary dramatically during a storm event. Nevertheless, grab sampling has an important role in

many stormwater monitoring programs for the following reasons:

• A single grab sample collected during the first part of a storm can be used to characterize

pollutants associated with the "first flush." The first part of a storm often contains the

highest pollutant concentrations in a storm runoff event, especially in small catchment areas

with mostly impervious surfaces, and in storms with relatively constant rainfall. In such

cases, the first flush may carry pollutants that accumulated in the collection system and

paved surfaces during the dry period before the storm. Thus, the results from single grab

samples collected during the initial part of storm runoff may be useful for screening-level 

programs designed to determine which pollutants, if any, are present at levels of concern. 

However, this strategy may be less effective in areas subject to numerous low-intensity, long 

duration storms with short inter-event times, because “first flush” effects are less obvious

under such weather conditions. 
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• Some measurable parameters, such as temperature, pH, total residual chlorine, phenols,

volatile organic compounds (VOCs), and bacteria transform or degrade so rapidly that

compositing can introduce considerable bias. (Note: Grab sampling is the typical method

for VOCs because VOCs can be lost through evaporation if samples are exposed to air during 

compositing. However, as discussed in Section 3.2.1 some automated samplers can be

configured to collect samples for VOC analysis with minimal losses due to volatilization).

• Some pollutants, such as oil and grease and TPH, tend to adhere to sample container surfaces 

so that transfer between sampling containers must be minimized (if program objectives

require characterization of the average oil and grease concentration over the duration of a

storm, obtain this information from a series of grabs analyzed individually).

To estimate event mean concentrations or pollutant loads, you could collect a series of grab

samples at short time intervals throughout the course of a storm event. There are several

different approaches for obtaining information from a series of grab samples. One approach

would be to analyze each grab sample individually. If the samples are analyzed individually, the 

results can be used to assess the rise and fall of pollutant concentrations during a storm and to

estimate event mean concentrations of pollutants. This approach can be particularly useful if the 

monitoring objective is to discern peak pollutant concentrations or peak loading rates for

assessing short-term water quality impacts. Analyzing each grab separately adds significantly to 

laboratory costs; consequently, this approach is rarely used except when program objectives

require detailed information about changes in constituent concentrations over the course of a

storm. 

Composite Samples

Another approach is to combine appropriate portions of each grab to form a single composite

sample for analysis, but this is generally impractical if there are more than a few stations to

monitor. Moreover, manual monitoring can be more costly than automated monitoring if your

program encompasses more than a few storm events. For these reasons, many monitoring

programs have found that the use of automated monitoring equipment and methods are more

appropriate for compiling composite samples than manual monitoring. If detecting peak

concentrations or loading rates is not essential, composite sampling can be a more cost-effective 

approach for estimating event mean concentrations and pollutant loads. A composite sample is a 

mixture of a number of individual sample "aliquots." The aliquots are collected at specific

intervals of time or flow during a storm event and combined to form a single sample for

laboratory analysis. Thus, the composite sample integrates the effects of many variations in

stormwater quality that occur during a storm event. Composite samples are suitable for most

typical stormwater quality parameters, but are unsuitable for parameters that transform rapidly

(e.g., fecal coliform, residual chlorine, pH, volatile organic compounds) or adhere to container

surfaces (e.g., oil and grease). 

The two basic approaches for obtaining composite samples are referred to as time-proportional 

and flow-proportional. A time-proportional composite sample is prepared by collecting
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individual sample "aliquots" of equal volume at equal increments of time (e.g., every 20

minutes) during a storm event, and mixing the aliquots to form a single sample for laboratory

analysis. Time-proportional samples do not account for variations in flow; pollutant

concentrations in sample aliquots collected during the portion of the storm with lower flows are

given the same "weight" as sample aliquots collected during higher flows. Consequently, timeproportional composite samples generally do not provide reliable estimates of event mean

concentrations or pollutant loads, unless the interval between sample aliquots is very brief and

flow rates are relatively constant. 

Flow-weighted composite samples are more suitable for estimating event mean concentrations

and pollutant loads. The event mean concentration is discussed in detail in Section 2.5.3. A

flow-weighted composite sample can be collected in several ways (EPA 1992):

1. Constant Time - Volume Proportional to Flow Rate - Sample aliquots are collected at

equal increments of time during a storm event, and varying amounts of each aliquot are

combined to form a single composite sample. The amount of water removed from each

aliquot is proportional to the flow rate at the time the aliquot was collected. This type of 

composite sample can be collected using either manual or automated techniques. 

2. Constant Time - Volume Proportional to Flow Volume Increment - Sample aliquots

are collected at equal increments of time during a storm event, and varying amounts from 

each aliquot are combined to form a single composite sample. The amount of water

removed from each aliquot is proportional to the volume of flow since the preceding

aliquot was collected. This type of compositing is generally used in conjunction with an 

automated monitoring system that includes a continuous flow measurement device. It

can be used with manual sampling in conjunction with a continuous flow measurement

device, but this combination is uncommon. 

3. Constant Volume - Time Proportional to Flow Volume Increment - Sample aliquots of 

equal volume are taken at equal increments of flow volume (regardless of time) and

combined to form a single composite sample. This type of compositing is generally used 

in conjunction with an automated monitoring system that includes a continuous flow

measurement device. 

Select the flow-weighted compositing method most suitable for your program based on the

monitoring technique (manual or automated) and equipment you plan to use. Compositing

Methods 2 and 3 are more accurate than Method 1 because Methods 2 and 3 use the total volume 

of flow based on continuous flow measurement to scale the sample volume; in contrast, Method 

1 uses a single instantaneous rate measurement to estimate the flow over the entire sampling

interval. However, if you intend to use manual methods, compositing Method 1 is generally the 

most practical choice. If automated equipment is to be used, Method 3 is generally preferred

because it minimizes the need for measuring and splitting samples, activities that can increase

the chance for sample contamination. If you plan to use automated methods, review the

equipment manufacturer's specifications and instructions to select the compositing method most

appropriate for that particular make and model. 
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Storm events affect stream flows for variable lengths of time depending on the storm duration

and antecedent conditions and catchment characteristics. Runoff may persist for a period of a

few hours to one to two days. This suggests runoff rarely persists long enough to be considered 

comparable to chronic exposure duration. Discrete sampling over the course of the storm event

will provide concentration information that can be used to determine how long water quality 

criteria were exceeded during the storm. Alternatively, discrete samples can be composited on a 

time-weighted basis over time scales comparable to the acute and chronic water quality criteria

exposure periods (one hour and four days) respectively. However, the latter would likely include 

dry-weather flows since few storms last four days. For catchments which are relatively small (a

few acres), it is recommended one or more one-hour composite samples be collected during the

first few hours of flow by collecting and combining three or more grab samples. 

Flow-weighted composite sampling can be used for comparison with water quality objectives

(for example, if flow-weighted composites are collected to measure loads). However, it should

be recognized that a flow-weighted sample would contain more water from peak flows than from 

the initial part of the storm. Results from Santa Clara Valley Nonpoint Source Monitoring

Program indicated that for a large watershed with significant suspended sediment concentrations 

(200 - 400 mg/L), peak total metals concentrations are generally 1.5 times the flow-weighted 

composite concentrations (WCC 1993). Results from monitoring a smaller, highly impervious

industrial catchment with the lower suspended sediment concentrations were more variable, and

no conclusions could be drawn as to the relationship between flow-composite concentrations and 

grab samples due to difficulties in grab sampling runoff that only occurred during precipitation. 

Automatic Sampling

Automated monitoring involves sample collection using electronic or mechanical devices that do 

not require an operator to be on-site during actual stormwater sample collection. It is the

preferred method for collecting flow-weighted composite samples. Automated monitoring is

generally a better choice than manual monitoring at locations where workers could be exposed to 

inadequate oxygen, toxic or explosive gases, storm waves, and/or hazardous traffic conditions.

Also, automated methods are better than manual methods if you are unable to accurately predict

storm event starting times. Automated samplers can be set so that sampling operations are

triggered when a pre-determined flow rate of storm runoff is detected. Conversely, manual

monitoring relies on weather forecasts (and considerable judgment and good luck) to decide

when to send crews to their monitoring stations. It is very difficult to predict when stormwater

runoff is likely to begin; consequently, manual monitoring crews may arrive too early and spend 

considerable time waiting for a storm that begins later than predicted, or they may arrive too late 

and miss the "first flush" from a storm that began earlier than predicted. If the automated

equipment is set to collect flow-weighted composite samples using the constant volume-time 

proportional to flow method, it reduces the need to measure samples for compositing. 

If you have determined that field-measured "indicator" parameters (e.g., turbidity, conductivity,

dissolved oxygen, pH) are sufficient for your monitoring objectives, consider using electronic

sensors and data loggers. Using electronic sensors and data loggers, you can obtain nearcontinuous measurements of indicator parameters at reasonable cost. 
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BMP monitoring can be an especially useful application for some automated systems (e.g.,

continuous flow recorders, auto samplers, continuous monitoring probes) for the following reasons:

• Automated systems can provide data covering virtually the entire volume of runoff that passes

through the BMP (i.e., they are not likely to miss or leave out small events and the beginnings

and ends of other events).

• Automated systems are well suited to providing data sets that are useful (recognizing that 

performance evaluations are generally based on the differences between inlet and outlet

concentration data sets, both of which are inherently noisy).

• The information obtained from good performance monitoring programs can be very valuable 

by protecting against inappropriate BMP applications. Therefore, the cost of using

automated systems is often justifiable.

Automatic Sampling Equipment

An automated sampler is a programmable mechanical and electrical instrument capable of

drawing a single grab sample, a series of grab samples, or a composited sample, in-situ. The

basic components of an automated sampler are a programming unit capable of controlling

sampling functions, a sample intake port and intake line, a peristaltic or vacuum/compression

pump, a rotating controllable arm capable of delivering samples into sample containers and a

housing capable of withstanding moisture and some degree of shock. Commonly used brands

include: ISCO, Lincoln, Nebraska; American Sigma, Medina, New York; Manning, Round

Rock, Texas; and Epic/Stevens, Beaverton, Oregon. 

An automated sampler can be programmed to collect a sample at a specific time, at a specific

time interval, or on receipt of a signal from a flow meter or other signal (e.g., depth of flow,

moisture, temperature). The sampler distributes individual samples into either a single bottle or

into separate bottles which can be analyzed individually or composited. Some automated

samplers offer multiple bottle configurations that can be tailored to program objectives. 

Important features of automated samplers include:

• Portability.

• Refrigeration.

• Volatile organic compound (VOC) sample collection (if needed).

• Alternative power supplies.
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Figure 3.12: Automatic sampler (American Sigma Inc.)

Portable samplers are smaller than those designed for fixed-site use, facilitating installation in

confined spaces. If a suitable confined space is not available or undesirable (e.g., because of

safety issues), the sampler can be housed in a secure shelter at the sampling site. Portable

samplers can use a 12V DC battery power supply, solar battery, or AC power. 

Although none of the portable samplers currently available are refrigerated, ice may be added to 

the housing of some units to preserve collected samples at a temperature as close to 4°C as

possible. The objective of this cooling is to inhibit pollutant transformation before the sample

can be analyzed. Refrigerated samplers hold samples at a constant temperature of 4°C. 

However, their large size and requirement for a 120V AC power prohibit most field installations. 
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Figure 3.13: VOC sampler (ISCO)

An automated sampler designed for VOCs is currently available from ISCO. The bladder pump 

used by this instrument minimizes physical disturbance of the sample (as opposed to the physical 

disturbances imparted by peristaltic vacuum pumps), reducing the loss of volatile compounds. 

The VOC sampler distributes the sample into sealed 40-ml sample bottles, as required by EPA

protocol. However, at present, the caps for the sample bottles are not compatible with automated 

laboratory equipment, requiring more handling in the laboratory. 

In typical installations for BMP sampling, for each of the types of samplers described above, an 

intake line is bracketed to the channel bottom. The intake tubing should be mounted as

unobtrusively as possible, to minimize disturbance of the site hydraulics. Generally, the

optimum position for the intake is to the channel bottom. However, if high solids loadings are

expected and potential deposition could occur, the intake can be mounted slightly higher on one

side of the channel wall. Typically, a strainer is attached to the intake to prevent large particles

and debris from entering the tubing. The strainer is usually installed so that it faces upstream,

into the flow. This configuration minimizes the development of local turbulence that could

affect representative sampling of constituents in the particulate phase. 

Two types of pumps are incorporated into automated samplers for typical water quality sampling 

(i.e., not VOC sampling): peristaltic and vacuum/compressor. A peristaltic pump creates a

vacuum by compressing a flexible tube with a rotating roller, drawing a sample to the pump that 

is then pushed out of the pump. Field experience with peristaltic pumps has shown that their

reliability in drawing a consistent sample volume is greatly reduced as the static suction head

(i.e., distance between the flow stream surface and the sampler) increases. It may be possible to

increase the efficiency of these samplers by placing the pump closer to the sample source,
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reducing the suction head. In general, the sampler itself should be installed no more than 6

meters (20 feet), and preferably less, above the channel bottom. If the sampler is to be installed 

at greater than 20 feet above the channel invert, it may be necessary to use a remote pump that is 

placed closer to the flow stream to ensure reliable sample collection. 

The degree to which sampler lift affects the concentration of total suspended solids and other

pollutant parameters (especially coarser materials) is not well known. That is, the mean transport 

velocity achieved by the peristaltic pump is sufficient to draw suspended solids; however, the

pulsed nature of the flow may allow suspended solids to settle back down through the pump

tubing during transport. In work performed by the USGS (FHWA 2001), it was found that

suspended solids concentrations did not vary with pumping height (0 to 24 feet); however,

sample volumes delivered to sample bottles did vary from sample to sample at high lift heights

for some of the older sampler models. 

Another concern with peristaltic pumps is their incompatibility with TeflonTM-lined tubing in the 

pump assembly. Compression of the intake tubing by the rollers tends to create stress cracks and 

small recesses in the lining where particles can accumulate. Under these circumstances, some

pollutant concentrations could be underestimated and the cross-contamination of samples can

occur. Although TeflonTM-lined tubing is preferable because it reduces the potential loss of

pollutants through surface interactions, this advantage cannot be accommodated with a peristaltic 

pump. 

A vacuum/compressor pump draws a sample by creating a vacuum. This type of pump can

create a higher transport velocity in the intake tube and provide a more steady and uniform

discharge than a peristaltic pump. However, the higher intake velocity can scour sediments in

the channel near the sampler intake, resulting in disproportionately high concentrations of

suspended solids. 

After a sampler is installed, it must be programmed to collect the desired sample size. 

Calibration of peristaltic pumps is achieved by one of two methods: automatic or timed. In

automatic calibration, the actual volume of sample drawn is measured using a fluid sensor

located at the pump and the known pump speed. In timed calibration, the volume is determined 

from the number of revolutions of the peristaltic pump and the time taken for the sample to travel 

from its source to the sample container. Calibration by this latter method is site specific, 

incorporating the pump speed, the head (vertical distance above the sample source), and the

length and diameter of the intake tubing. The Manning and Epic samplers, which employ

vacuum pumps, permit adjustment for specific sample volumes via a fluid level device in a

chamber. This chamber can cause sample cross-contamination, as it cannot be flushed as the

tubing can.

Overland Flow Sampler

An overland flow sampler is a non-automated sampler that can be used to take discrete grab

samples or a continuous sample over some duration. This type of sampler may be useful for

collecting stormwater samples for certain types of BMPs (upstream of catch basins). One

manufacturer's (Vortox, Claremont, California) unit within this class of samplers consists of an
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upper ball valve, a lower ball valve (through which runoff enters), and a sample container. The

upper valve can be adjusted to control the rate of intake, allowing continuous sampling of storm 

events of different durations, provided depth of flow is not highly variable. The lower ball valve 

seals and closes the intake when the water level reaches the top of the container. 

Overland flow samplers (manufactured by Vortex) are available in two sizes: 3 liters (0.8

gallon) and 21 liters (5.5 gallons). They can be set into existing sumps or in the ground, but they 

must be installed with the top of the sampler flush with the ground surface.

This instrument is inexpensive and simple to operate. Since the overland flow is not

concentrated, there are no other methods for collecting this flow. However, this sampler is not

capable of taking flow or time-weighted composites or of sampling the entire flow during a large 

storm event. In fact, there is no way of knowing what part of the storm was actually sampled,

especially where flow depths are variable. Recently, the USGS developed and began testing an

automated overland flow sampler that may be capable of time-weighted composite sampling. 

In-situ Water Quality Devices, Existing Technology

The concentration of most pollutants in stormwater runoff is likely to vary significantly over the 

course of a given storm event. Some of this variability can be captured through the collection of 

multiple samples. The ideal data set would contain not just multiple samples, but also a

continuous record of constituent concentrations throughout a storm, capturing both the timing

and magnitude of the variations in concentration. Given the availability of other continuous data, 

this approach might allow better correlation with potential causative factors. Unfortunately, the 

laboratory costs for even a near-continuous data set would be prohibitive. USGS determined that 

between 12 and 16 individual samples resulted in a mean that was within 10 to 20 percent of the 

actual event mean concentration (FHWA 2001). In-situ monitoring devices offer a possible

solution to obtaining a continuous record of water quality; however, at this time, they are only

practical for a limited set of parameters.

In-situ water quality probes have been adapted from equipment developed for the manufacturing 

and water supply/wastewater industries. In-situ water quality monitors attempt to provide the

desirable near-continuous data set described above at a relatively low cost, eliminating (or

reducing) the need for analysis of samples in the laboratory.

In general, water quality monitors are electronic devices that measure the magnitude or

concentration of certain specific target constituents through various types of sensors. Discrete

measurements can be made at one minute or less intervals. Most monitors use probes that

provide a controlled environment in which a physical and/or electrochemical reaction can take

place. The rate of this reaction is typically driven by the concentration of the target constituent in 

the flow. The rate of reaction, in turn, controls the magnitude of the electrical signal sent to the

display or a data-logging device.
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Probes to detect and measure the following physical and chemical parameters are currently

available for practical use in the field:

Physical parameters

Temperature

Turbidity

Chemical parameters

pH

Oxidation-reduction potential (redox)

Conductivity

Dissolved oxygen

Salinity

Nitrate

Ammonia

Resistivity

Specific conductance

Ammonium

There are some potential probes for heavy metals, but given the complexities associated with

highly variable solids concentrations and other factors, studies have found that they are not

practical for field application (FHWA 2001). Instruments can be configured to measure the

concentrations of several of these parameters simultaneously (i.e., multi-parameter probes) and

provide data logging and PC compatibility. Manufacturers of this type of instrument include

YSI, Inc., Yellow Springs, Ohio; ELE International, England; Hydrolab, Austin, Texas; Solomat, 

Norwalk, Connecticut; and Stevens, Beaverton, Oregon. 

In many cases, the electrochemical reaction that drives a probe's response is sensitive to changes 

in temperature, pH, or atmospheric pressure. Where appropriate, monitors are designed to

simultaneously measure these associated properties. Data on the target constituent are then

corrected through a mathematical routine built into the probe's microprocessor (e.g., dissolved

oxygen probes are compensated for temperature and atmospheric pressure, pH probes for

temperature and ammonia probes for pH), or are adjusted in a spreadsheet after downloading to a 

personal computer.

Despite the advantage of these instruments for measuring near-continuous data, they require

frequent inspection and maintenance in the field to prevent loss of accuracy due to fouling by oil 

and grease, adhesive organics, and bacterial and algal films. Therefore, these instruments should 

always be cleaned and calibrated before use. Because water quality probes are designed to

operate while submerged in water, exposure of the electrochemically active probe surface to air

should be minimized. 
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In-situ Water Quality Devices, Future Technologies

There are several in-situ water quality devices that are used by industry but are not currently

applicable to stormwater monitoring. However, as the technology advances they may become

applicable and therefore are discussed in this section. 

Ion-Selective Electrodes

An ion-selective electrode places a selectively permeable membrane between the flow and an

internal solution of known ionic strength. The voltage differential across the membrane is

proportional to the difference in ionic strength between the two solutions. Ion-selective probes

are currently available for the ionic forms of a number of parameters, including ammonia,

ammonium, copper, lead, nitrate, and nitrite. 

An ion-selective electrode is specific to the targeted ion and will not measure other ions or other 

complexed forms. For example, depending on the target parameter, a nitrate-selective electrode 

will not measure the concentration of nitrite in the flow. However, these instruments are

sensitive to interference from other ions, volatile amines, acetates, surfactants, and various weak 

acids. At present, the degree of interference can be judged only by comparing the performance

of the probe to that of one in a reference solution, a procedure likely to prove unwieldy in the

field. Consequently this type of probe is not typically used for stormwater monitoring. 

On-Line Water Quality Analyzers

On-line water quality analyzers are spectrometers, similar to those used in analytical laboratories. 

A light source that generates a known intensity of light over a range of wavelengths (i.e.,

ultraviolet or infrared) is transmitted through a sample introduced into a flow cell. The

instrument collects light absorbency information at multiple wavelengths and produces a light

absorbency signature (manufacturer's specifications, Biotronics Technologies, Inc., Waukesha,

Wisconsin, and Tytronics, Inc., Waltham, Massachusetts). The instrument is calibrated using 30 

or more randomly varied mixtures of standards; the ultraviolet (UV) light-absorbency 

characteristics of a sample are then compared to a baseline calibration file of known “UV

signatures.” 

On-line analyses are used in the water treatment and wastewater industries. Until recently, online spectrometric analyzers were impractical for stormwater field use. The state of technology 

of these systems was comparable to that in the field of computers 20 years ago: large machines 

requiring a controlled laboratory environment were operated by highly trained specialists. 

However, an increased demand for portability, the increased power and decreased cost of

microprocessor technology, the development of new statistical and mathematical analysis

software, and the availability of standardized control systems (i.e., communication interfaces,

actuators, and programmable controllers) have fostered the emergence of a new generation of

instruments. 
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Three types of spectrometers are currently available or under development for environmental

applications: 

• Ultraviolet-Array Spectroscopy (UVAS) employs a broad spectrum light generated by a

Xenon lamp and delivered to the sample through fiber optic cables. Light is transmitted

through the sample in specially designed optical probes. The light transmitted through the

sample is collected and returned to the analyzer where it is dispersed into wavelengths and

projected onto a photodiode detector array. Current applications are the detection of multiple 

contaminants (metals, nitrates, organics, and aromatic hydrocarbons) in groundwater, the

detection of metals (chromium, zinc, and mercury) in industrial wastewater, and water

treatment quality parameters (copper, iron, molybdate, triazole, phosphorate) in industrial

processes and cooling waters.

• Liquid Atomic Emission Spectrometry (LAES) employs a photodiode detector array similar 

to that used in UVAS. A high-energy arc is discharged directly into the liquid as the source

of excitation and the resulting atomic light emission is analyzed by special pattern

recognition techniques. Qualitative analysis is derived from the detection of emission lines

and quantitative analysis is a function of intensity. Use of LAES has been demonstrated for

the analysis of metals, hydrogen, and sulfur.

• Like UVAS, Near Infrared (NIR) analysis employs the transmission of light through a liquid. 

This technology has been used extensively in the food processing industry and is under

evaluation for application elsewhere.

To date, portable on-line analyzers have not been tested extensively for use in stormwater or

BMP monitoring. The “ChemScan” analyzer, manufactured by Biotronics Technologies, Inc., is 

reported to adjust automatically for changes in the turbidity of the flow and fouling of the optical 

windows, features which suggest applicability to stormwater situations. According to the

manufacturer, routine maintenance is limited to a periodic baseline correction and occasional

chemical cleaning of the flow cell. 

Particle Size Analyzers

There is a particle size analyzer available that can be installed in-situ. It employs laser

diffraction to determine the particle size distribution. However, the unit costs approximately

$30,000, is 3 feet long and 5 inches in diameter, and is required to be submerged. Currently it is 

not applicable for stormwater monitoring.

Research is currently being conducted on applying ultrasonics for particle size analysis. 

However, it is presently not available for stormwater application. 
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In-situ Filtration and Extraction System

Axys Environmental Systems, Ltd., British Columbia, Canada manufactures an in-situ filtration

and extraction system for monitoring trace organics, metals, and radionuclides in stormwater. 

These systems retain the target pollutant on a resin filter as a portion of the flow passes through. 

After the storm event, the filter is taken to the laboratory and the pollutant is removed through

solid phase extraction. The filtration system is comprised of a microprocessor, a pump, a flow

meter, and a DC power supply. A prefilter for suspended solids can be attached if levels high

enough to clog the resin filter are anticipated. Pollutants trapped in the prefilter can also be

extracted and analyzed.

These systems can be programmed so that samples of the flow pass through the filter at equal

time intervals, or so that signals from an external flow meter trigger flow- or time-weighted 

composite sampling. As with other types of automated samplers, the sampling history is stored in 

internal memory.

Filtration and extraction systems reduce the potential for contamination of a sample during

handling in the field and eliminate the need to transport large volumes of water to an analytical

laboratory. The detection limit of the samples depends on the amount of water flowing through. 

Because large volumes of water can be passed through the system, even very small

concentrations of pollutants can be detected. On the other hand, where suspended sediment

concentrations are high, the prefilter may become clogged as a large volume of water passes

through it. Metals can be lost from the filter if the pH drops to 6.0 or lower, and resin filters are 

available for only a limited number of pollutants. Due to the potential for clogging, this

methodology may not be useful for BMP monitoring sites. 

Remote Communications with Automatic Equipment

The ability to remotely access the memory and programming functions of automated samplers is 

a highly desirable feature for large stormwater sampling networks. Although this feature

increases the capital cost for a system, it can greatly reduce the expertise and training necessary

for field crews because many of the technical aspects of equipment set-up and shut-down can be 

conducted by a system supervisor remotely. 

Currently, modem communication is an available option to most commercially produced

automated samplers. However, there are several common drawbacks that may be encountered

with the communication systems currently offered by manufacturers:

• Full access to all sampler programming features is limited. This means that trained field

crews may still be necessary to ensure sampler programming is correct.

• For multiple instrument systems (i.e., separate flow meter and automated sampler)

communication and complete operation of both components through one modem system is

generally not available.
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Remote communication for both samplers and flow meters is a rapidly advancing technology,

and companies like American Sigma and ISCO are developing systems that address the problems 

described above. 

Manual Sampling

Manual monitoring involves sample collection and flow measurement by personnel using handoperated equipment (e.g., bailer, bottle). For a monitoring program that is modest in scope (i.e.,

relatively few sampling sites and storm events), manual methods for obtaining grab and

composite samples may be preferable to those employing automated equipment. Also, if your

program requires monitoring large streams, you may need to use manual methods in order to

collect cross-section composites. The principal advantages to manual sampling are its relatively

low capital cost and high degree of flexibility. In addition to the capital outlay required for the

purchase of automated samplers, other costs, such as installation, training personnel to use the

samplers correctly, and field maintenance and operations (replacing batteries, interrogating data

loggers, retrieving and cleaning sample jars) can be substantial.

Manual sampling is usually preferred under the following circumstances:

• When available resources for equipment purchase/installation (e.g., funds, personnel, time) are

very constrained and/or there is not the political will to invest in a program, despite the inherent 

value of the resultant information.

• When the target pollutants are ones that do not lend themselves to automated sampling or

analysis (e.g., oil and grease, volatile organic compounds, bacteria).

• When the physical setting of the BMP does not allow the use of automated systems.

However, manual monitoring may not be feasible if:

• Monitoring personnel are not available after normal working hours.

• Monitoring personnel have strict job descriptions that do not include sampling.

• The organization's insurance policy doesn't cover stormwater monitoring activities.

• Managers and monitoring personnel are not able to deal with sick days, vacations, and

competing priorities.

Manual sampling is generally less practical than automated monitoring for large-scale programs 

(e.g., monitoring programs involving large numbers of sites or sampling events over multiple

years). It is difficult to collect true flow-weighted composites using manual methods. Under

these circumstances, labor costs and logistical problems can far outstrip those associated with

automated equipment. For the same reason, manual sampling is seldom practiced if specific

program objectives require that samples be composited over the entire duration of a storm, which 

is recommended for BMP monitoring. 
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Manual equipment can be used in collecting grab samples, composite samples, or both, as 

described below.

Manual Grab Sampling Equipment

Manual sampling techniques and equipment have been reviewed in more detail by Stenstrom and 

Strecker (1993). If site conditions allow, a grab sample can be collected by holding the

laboratory sample bottle directly under the lip of an outfall or by submerging the bottle in the

flow. A pole or rope may be used as an extension device if field personnel cannot safely or

conveniently approach the sampling point. Alternatively, a clean, high-density polyethylene

bucket may be used as a bailer and sample bottles may be filled from the bucket. Care should be 

taken not to stir sediments at the bottom of the channel. 

As described earlier, the concentrations of suspended constituents tend to stratify within the flow 

stream depending on their specific gravity and the degree to which flow is mixed by turbulence. 

Use of a discrete-depth sampler for multiple samples should be considered when constituents

lighter or heavier than water are targeted, or if the flow is too deep and/or not well mixed enough 

to be sampled in its entirety (Martin et al. 1992). However, stormwater BMPs often drain

relatively small catchments and contain fairly shallow flows. Collection of depth-integrated 

samples at these sites is not usually performed.

Given the extremely low detection limits that laboratory analytical instruments can achieve,

leaching of water quality constituents from the surface of a bailing device or sample bottle can

affect water quality results. Sample bottles of the appropriate composition for each parameter

are usually available from the analytical laboratory. Depending upon the pollutant to be

analyzed, bailers and discrete-depth samplers should be made of stainless steel, TeflonTM coated 

plastic, or high-density polyethylene. When in doubt, a laboratory analyst should recommend an 

appropriate material type for the collection device.

Manual Composite Sampling Equipment

If grab samples will be composited based on flow rate (i.e., grab samples collected during high

flow contribute more to the composited sample than those collected during low flow), some

receptacle for storing the individual grab samples prior to compositing will be required. The use 

of polyethylene jugs, or the polyethylene cubes with screw-on caps manufactured for shipping

chemicals, is recommended. These can be shaken to remix the sample prior to pouring out the

required volume. The volume required from each receptacle can be measured in a graduated

cylinder and poured into a bucket for compositing. Both the cylinder and the bucket should be

made from a TeflonTM-coated plastic or high-density polyethylene and should be cleaned prior to 

use.
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3.2.4.3 Error Analysis and Measurement Accuracy

Every measurement has an unavoidable uncertainty due to the precision of the measuring tool,

the accuracy of the calibration, and the care with which the measurement is made. If all other

sources of error are minimized or removed, then the uncertainty in the measurement is generally

on the same order of the smallest numerical value that can be estimated with the measuring

instrument. The true value is typically contained in the range of values reflecting the

experimental uncertainty of the measurement. Calculating the mean of multiple measurements if 

the measurement errors are random in nature and not systematic can provide a better estimate of 

the true value. 

Indeterminate (random) errors result from instrument precision, calibration, and inaccuracies in

the measuring process. The size and magnitude of indeterminate errors cannot be determined

(hence the name) and result in different values from a measuring process when the process is

repeated. There are several ways indeterminate errors can be introduced, including operator

error, variation in the conditions in which the measuring process is conducted, and the variability 

of the measuring instrument. 

Determinate (systematic) errors have an algebraic sign and magnitude and result from a specific

cause introducing the same error into every measurement. Determinate errors are more serious

than indeterminate errors because taking the average of multiple measurements cannot reduce

their effects. This is because determinate errors have the same sign and magnitude, which

prevents positive and negative errors from off setting each other. Causes of this type of error can 

include operator bias, (consistent) operator error such as incorrect reading of the instrument, or

improper calibration of the measuring instrument. 

Expressing Errors 

Absolute and relative methods are the standard forms for expressing errors. Absolute error is

expressed as a range of values reflecting the uncertainty in the measurement and is reported in

the same units as the measurement. Measured values followed by the ± sign express the absolute 

error.

Relative (or fractional) error is expressed as the ratio of the uncertainty in the measurement to the 

measurement itself. This is difficult to estimate, because it is a function of the true value of the 

quantity being measured, which is unknown, otherwise the error estimate would be zero. 

Typically this error estimate utilizes the measured value as the “true” value.

The type of measurement and instrumentation can provide an indication of the appropriate form 

of expressing the error. For example, a pressure probe used to measure depth of flow is likely to 

have the accuracy of the instrument expressed as a relative percent, while readings on a staff

gauge would have an absolute error related to the markings on the gauge. In these instances the 

reported depth measurements would be expressed in the same manner as the precision of the

measuring instrument.
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Propagation of Errors

Quite often, measurements taken of one or more variables are used in equations to calculate the

value of other variables. For example, to calculate the area of a rectangle, the length and width

are usually measured. For a cube, the length, width, and height are measured to calculate the

volume. Each measurement has a potential error associated with it and, as a result, the variable

calculated from the individual measurements will also contain some error. The magnitude of the 

error in the calculated variable can be of a different order than the error associated with any one

of the measurements depending on the algorithm that describes their relationship. 

A detailed discussion of the propagation of errors and methods for calculating estimates of errors 

as a result of propagation are provided in Appendix A.

3.2.5 Recommendation and Discussion of Storm Criteria

The establishment and application of appropriate storm selection criteria can be a challenging aspect 

of planning BMP monitoring programs. Ideally, one would want to obtain data from all phases of

all storms for as long a study period as possible, for the following reasons:

• To know what the BMP does during periods of very low flow, normal flow, and very high

flows. Some BMPs' performance varies dramatically with throughput rate (some may even

release pollutants that had been previously trapped).

• To estimate performance on the basis of differences of relatively noisy data sets (i.e., inlet

versus outlet data). This intensifies the value of large volumes of credible data (not just a few 

samples from portions of a few storms).

• To characterize the water quality of dry weather flows for some BMPs with significant wet

storage and/or base flows. This is particularly important when the wet volume of the BMP is

large relative to the storm event. The comparison of inflow to outflow during a storm event is

not valid because the outflow may have little or no relationship to the incoming storm. This

mistake has been made often in past studies.

Despite the desire for extensive and high quality data, there is still a need to tailor your methods to

be consistent with available resources. The types of storms to be monitored and optimal temporal 

distribution of monitoring events also should be considered during project planning (Caltrans

1997). 

3.2.5.1 Storm Characteristics

The application requirements for NPDES permits that require monitoring specify that

"representative" storms must be monitored. As defined in the regulations, a "representative"

storm must yield at least 0.1 inch of precipitation; must be preceded by at least 72 hours with less 

than 0.1 inch of precipitation; and, if possible, the total precipitation and duration should be

within 50 percent of the average or median storm event for the area. Programs that are not part 
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of the NPDES permit application process or in fulfillment of an NPDES permit may have other

requirements. 

In general, it is desirable to monitor a broad range of storm conditions rather than just

“representative” storms as they are really not representative in many cases. For example, in the

Pacific Northwest, it is often difficult (and rare) to identify storms where there has been a 72-

hour dry period prior to the storm. 

Because the initial objective of the monitoring is to consider a "worst-case" picture, it is

desirable to select storms with the highest pollutant concentrations rather than a representative

mix of storms. Worst-case conditions are likely to occur after long antecedent dry periods (72

hours to 14 days). Therefore, if feasible, storms should be selected with antecedent periods

greater than 72 hours. Few relationships between storm volume and water quality have been

observed. Lacking any basis for storm volume selection for worst-case conditions, and

acknowledging that storm characteristics are highly dependent on climatic region, the following

may be used as a starting point:

Rainfall Volume: 0.10 inch minimum

No fixed maximum

Rainfall Duration: No fixed maximum or minimum

Typical Range: 6 to 24 hours

Antecedent Dry Period: 24 hours minimum

Inter-event Dry Period: 6 hours

If these criteria prove inappropriate for your situation, you can develop site-specific storm event

criteria by analyzing long-term rainfall records using EPA’s SYNOP or another appropriate

analytical program such as EPA’s SWMM model (which incorporates the features of SYNOP). 

It should be noted that biasing the storm selection to the "worst case" would not provide a

representative sample of the population of all types of storm events. The resulting data should be 

used in screening mode and not to estimate statistically derived exceedance frequencies. The

level of effort required to sample all representative types and combinations of storm conditions

in order to generate reliable population statistics is beyond the resources of most agencies. For

this reason, it is recommended a "worst case" approach be taken. Often permits require that you 

monitor "representative" storms that have been predefined. Operationally and practically, storm 

event criteria may need to be further defined beyond the regulatory definition. The use of a

probability of rainfall above a certain magnitude, during a specific period, based on a

quantitative precipitation forecast (QPF) serves as a good indication of when and how to

mobilize for monitoring efforts. QPFs for a geographic area can be obtained from the National

Weather Service and site specific information can be obtained from private weather consultants. 
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3.2.6 Recommendation and Discussion of QA/QC

Prior to sample collection, you should prepare a Quality Assurance/Quality Control (QA/QC) 

plan that describes the sample collection and laboratory analysis procedures. The first step in

preparing a QA/QC plan is to determine the data quality objectives (DQOs) appropriate to your

program. Ideally, the QA/QC plan should be prepared by someone with a good understanding of 

chemical analytical methods, field sampling procedures, and data validation procedures. Select

an analytical laboratory that has been accredited to perform the analyses required for your

program. The analytical laboratory should provide its input to ensure the plan is realistic and

consistent with the laboratory's operating procedures. 

It is recommended that the QA/QC plan should summarize the project organization, data quality

objectives, required parameters, field methods, and laboratory performance standards for the

measurements. A typical QA/QC plan for stormwater monitoring may include the following

sections:

1. Project Description

2. Project Organization and Responsibility

3. Data Quality Objectives

4. Field Methods

- sample collection methods

- field QA procedures such as equipment cleaning and blanks

- collection of field duplicate samples

- sample preservation methods

- type of bottles for subsampling

5. Laboratory Procedures

- constituents for analysis

- laboratory performance standards (e.g., detection limits, practical quantitation limits,

objectives for precision, accuracy, completeness)

 -analysis method references

- frequency and type of laboratory QA samples (e.g., laboratory duplicates, matrix spikes 

and spike duplicates, laboratory control samples, standard reference materials)

- data reporting requirements 

- data validation procedures

- corrective actions

It is important that you develop your QA/QC plan in concert with your field personnel and your

analytical laboratory. If you have not already done so, you should visit the monitoring locations 

to verify that the selected monitoring methods are feasible. Inform your managers of any

modifications to either the DQOs or laboratory performance standards due to field or laboratory

constraints. 
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Potential Sources of Error

This section describes some potential sources of error that can occur in the process of sampling

or transferring monitoring results to a database. These common errors can be specifically

addressed in the QA/QC plan to increase awareness and potentially reduce their occurrence.

In many cases error is introduced in the process of transferring or interpreting information from

the original data records. These errors most likely result from typographical errors or format and 

organizational problems. In most cases, water quality data are returned from the lab in some

tabular format. Data are then entered into a database, typically with separate records for each

monitoring station and each storm event. The inconsistency of data formats between monitoring 

events can considerably increase the potential for errors in entering data into the database and

subsequently interpreting and using the processed (digital) data.

Where errors in data are present in the processed information, format is often a causative factor. 

In some circumstances interpretation of the data presented is not possible due to missing

explanations of the data format; in these cases, data should be excluded. It has been found that

missing records typically have to do with inadvertent skipping of a column or row of data. Errors 

in data or parameter type, that were not typographical, typically resulted from misalignment of

rows or columns. Supporting information and useful summaries of parameters, such as

characteristics of the watershed, are often included as text in a general information column, or in 

a report or record external to the water quality database. In addition to making the extraction of

this supporting information laborious, checking for errors in information not formatted succinctly 

can also be quite cumbersome.

In addition to these “paper” errors, many other opportunities abound for introduction of other

errors, including errors in interpretation and reporting of supporting information (e.g., 

misreading of maps, poor estimates of design, watershed, and environmental parameters, etc.)

and reporting of information from previous studies that may have been originally incorrect.

In addition to potential reporting errors, all field collected and/or laboratory analyzed data on

flow and water quality are subject to random variations that cannot be completely eliminated. 

These variations are defined as either “chance variations” or “assignable variations.” Chance

variations are due to the random nature of the parameters measured; increased testing efforts and 

accuracies cannot eliminate these variations. Although assignable variations cannot be

eliminated altogether, these variations can be reduced and the reliability of the data increased. 

Assignable variations are those errors that result from measurement error, faulty machine

settings, dirty containers, etc. Increasing both the length of a study and/or the number of storms

sampled can reduce the assignable variations and increase the reliability of the data (Strecker

1992). Many monitoring studies take place over relatively short periods and have a small

number of monitored storms during those periods. Thus the resultant data sets are often

susceptible to both of these types of variations in addition to any reporting errors.
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Prepare Health and Safety Plan

As part of the QA/QC plan, the health and safety of personnel involved in the monitoring

program should be considered. Aside from ensuring quality results and efficient implementation 

of monitoring procedures, human health and safety are a priority.

The health and safety of field personnel should be considered throughout development of your

monitoring program. You should select monitoring locations and methods that have the lowest

potential for health and safety problems. You should then prepare a health and safety plan. The 

first step is an assessment of the physical and chemical hazards likely to be associated with each 

monitoring activity. Some of the potential considerations include:

• Wet (and possibly cold) weather conditions.

• Physical obstructions that complicate access to the site and sample collection point (e.g.,

steep slopes, dense blackberry bushes).

• Traffic hazards.

• Manholes (i.e., confined space entry, including toxic, explosive, or otherwise unsafe

conditions).

• Flooding and fast moving water.

• Dim lighting.

• Slippery conditions.

• Contact with water that could be harmful (e.g., caustic, pathogenic).

• Lifting and carrying heavy and bulky pieces of equipment, including carboys and sample

bottles filled with water.

Based on the hazard assessment, identify the appropriate equipment and procedures to protect

field personnel from the potential hazards you have identified. Also, consider adjusting your

monitoring locations and/or methods if necessary to minimize the risk of health and safety

problems. 
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3.2.6.1 Sampling Methods

Proper sampling methods are essential in conducting a BMP monitoring program in order to

ensure resulting data are meaningful and representative of the water and other media being

processed by the BMP. Sampling methodologies and techniques that maintain and confirm the

integrity of the sample are discussed below. 

Grab Sample Collection Techniques

During moderate flow events, grab samples can be collected at some stations simply by

approaching the water to be sampled and directly filling up the bottles, being careful not to loose 

any preservative already contained in the bottle. It is important also to be aware of surface

conditions of the sampled water body, avoiding layers of algae and debris and areas of dense

vegetation if possible. The bottle cap should be handled carefully, making sure not to introduce

any extraneous dirt, water, debris or vegetation while filling the bottle; bottle caps should not be

placed on the ground facing downward. 

Low flow events may not provide sufficient flows to allow filling of bottles directly. In this

case, sample collectors may be used to collect the low flow runoff and transfer the water into the 

sample bottles. These sample collectors are typically cup to bucket sized containers with a wide 

mouth and no neck, allowing the collector to be placed close to the bottom surface of the flow

path and then filled with the small depth of flow. Sample collectors must be compatible in

material with the sample bottles and the constituents to be analyzed. Sample collectors made of 

stainless steel, teflon or glass could be considered after investigating the compatibility of these

materials with each constituent to be analyzed. After each sample bottle has been filled, and

before the next monitoring site is to be sampled, the sample collector should be rinsed

thoroughly with deionized water to prevent cross-contamination between sites. At least four

rinses with deionized water are necessary, followed by filling the sample collector several times

with new monitoring site runoff before finally using the collector to fill the sample bottles.

During high flow events, runoff may be unsafe to approach directly to collect the sample. 

Modified sample collectors can be designed to allow remote sampling. Many stainless steel

buckets or cookware (asparagus cookers) have handles to which ropes may be tied at a length

that allows the sample collector to be lowered into the runoff and raised back up after filling with 

water. These sample collectors with rope are ideal to use if sampling a creek from a bridge or

sampling an outfall from a creek bank. In addition, modified sample collectors will work well to 

sample runoff in a manhole, eliminating the need to enter the confined space during higher

flows. The advantage of the rope and bucket device is that a significant length of rope can be

attached to the sample bucket to allow for sampling from great heights, yet the rope can be coiled 

and stored compactly. If a sturdier sampling device is needed, sample collectors may be

attached to a pole using tape or rope and lowered into the runoff. Again, cross-contamination 

between sample sites should be prevented by rinsing the sampling collector with deionized water 

and new sample water several times.
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Contamination/Blanks

Control over sample contamination is critical when attempting to measure concentrations of

compounds at the parts-per-billion level. Contamination can be introduced either during the

bottle/equipment preparation steps or during the sample collection, transport, or analysis steps. 

Control over all of these steps can be achieved through the use of standardized equipment cleaning

procedures, clean sampling procedures, and clean laboratory reagents. The level of contamination

introduced during each of these steps is determined by analysis of different types of blank samples. 

Each of these different types of blanks is described below: 

• Method Blanks are prepared by the laboratory by analysis of clean Type II reagent water. 

They are used to determine the level of contamination introduced by the reagents and

laboratory processing. 

• Source Solution Blanks are determined by analysis of the deionized or Type II reagent

water used to prepare the other blanks. The source solution blank is used to account for 

contamination introduced by the deionized water when evaluating the other blanks. 

• Bottle Blanks are prepared by filling a clean bottle with source solution water and

measuring the solution concentration. Bottle blanks include contamination introduced by 

the source solution water and sample containers. By subtracting the source solution

blank result, the amount of contamination introduced by the sample containers can be

determined. 

• Travel Blanks are prepared by filling a sample container in the laboratory with Type II

reagent water and shipping the filled water along with the empty sample containers to the 

site. The travel blank is shipped back with the samples and analyzed like a sample. The 

bottle blank result can be subtracted from the travel blank to account for contamination

introduced during transport from the laboratory to the field and back to the laboratory.

• Equipment Blanks are usually prepared in the laboratory after cleaning the sampling

equipment. These blanks can be used to account for sample contamination introduced by

the sampling equipment, if the bottle blank results are first subtracted.

• Field Blanks account for all of the above sources of contamination. Field blanks are

prepared in the field after cleaning the equipment by sampling Type II reagent water with

the equipment. They include sources of contamination introduced by reagent water,

sampling equipment, containers, handling, preservation, and analysis. In general, field

blanks should be performed prior to or during the sample collection. Because the field blank 

is an overall measure of all sources of contamination, it is used to determine if there are any 

blank problems. If problems are encountered with the field blank, then the other

components of the sampling process should be evaluated by preparation of other blanks in

order to identify and eliminate the specific problem.
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EPA's recent guidance on the use of clean and ultra-clean sampling procedures for the collection of 

low-level metals samples (EPA 1993a,b) should be considered to ensure bottles and equipment are

cleaned properly and samples are collected with as little contamination as possible. While ultraclean techniques throughout are likely not necessary for stormwater runoff samples, some of the

laboratory procedures should be employed. For example, metals levels in highway runoff are

typically much greater than introduced errors associated with in-field clean sampling techniques. 

These techniques are typically employed in receiving waters where their applicability is more

relevant. 

Reconnaissance and Preparations

Reconnaissance and preparation is an important component of any field sampling program. Proper

reconnaissance will help field operations to go smoothly and ensure field personnel are familiar

with the sampling locations. 

Site Visits

During the planning stage, a site visit should be performed by the field personnel, prior to

conducting sampling. The purpose of the site visit is to locate access points where a sample can be 

taken and confirm that the sampling strategy is appropriate. Because of the transient nature of

meteorological events, it is possible sites may need to be sampled in the dark. For this reason, the

actual persons involved in the field sampling should visit the site during reconnaissance as a

complement to a training program for the monitoring effort. 

The training program should include:

• A discussion of what the programs goals are and why their efforts are important.

• Familiarization with the site.

• Training on the use and operation of the equipment.

• Familiarization with field mobilization, sampling, and demobilization procedures.

• Health and safety requirements.

• QA/QC procedures.

Laboratory Coordination

Coordination with the laboratory is a critical step in the planning and sampling process. The

laboratory should be made aware of specific project requirements such as number of samples,

required laboratory performance objectives, approximate date and time of sampling (if known),

required QA/QC samples, reporting requirements, and if and when containers or ice chests will

be required. Laboratory personnel should be involved early in the process so they can provide
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feedback on methods and performance standards during the planning phase. Notifying the

laboratory that stormwater sampling is planned is also important to allow the laboratory to plan

for off-hours sample delivery and to set-up any analysis with short holding times. 

Sample Containers/Preservation/ Holding Times

EPA recommends that samples be collected and stored in specific types of sample container

materials (e.g., plastic, glass, Teflon). For analysis of certain parameters, addition of specific

chemical preservatives is recommended to prolong the stability of the constituents during storage. 

Federal Register 40 CFR 136.3 lists recommended sample containers, preservatives, and maximum

recommended holding times for constituents. Sample holding times should be compared to

recommended maximum holding times listed in the Federal Register. Laboratory quality control

sample data should be compared to target detection limits as well as precision and accuracy goals

and qualified according to EPA functional guidelines for data validation (EPA 1988). 

If composite sampling procedures are to be used to collect one large sample that will be subsampled 

into smaller containers, the composite sample bottle should be compatible with all of the

constituents to be subsampled. In general, the use of glass containers will allow subsampling for

most parameters (with the exception of fluoride). 

Sample volumes necessary for the requested analysis should be confirmed with the laboratory prior 

to sample collection. Extra sample volume should be collected for field and laboratory QA/QC

samples. As a general guide, if one station is to be used for both field and laboratory QA/QC

measurements, four times the normal volume of water should be collected. 

Recommended Field QA/QC Procedures

Listed below are the recommended quality control samples and field procedures. 

Field Blanks

Field blanks should be prepared at least once by each field sampling team to prevent or reduce

contamination introduced by the sampling process. It is recommended that field blanks be routinely 

prepared and analyzed with each sampling event. In addition, it is desirable to prepare field blanks

prior to the actual sampling event as a check on procedures. This will ensure field-contaminated 

samples are not analyzed. Additional field blanks should be prepared if sampling personnel,

equipment, or procedures change. 

Field Duplicate Samples

Field duplicate samples should be collected at a frequency of 5% or a minimum of one per event,

whichever is greater. Field duplicate samples are used to provide a measure of the

representativeness of the sampling and analysis procedures. These types of duplicates are

recommended, but often not done due to expense.
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Field Sample Volumes

Sufficient sample volumes need to be collected to enable the required laboratory QA/QC analysis to 

be conducted. In general, one station should be targeted for extra sample volume collection and

identified on the chain-of-custody as the laboratory QA/QC station. If possible, this station should

be the one where the data quality is most critical.

Chain of Custody

All sample custody and transfer procedures should be based on EPA-recommended procedures. 

These procedures emphasize careful documentation of sample collection, labeling, and transfer

procedures. Pre-formatted chain-of-custody forms should be used to document the transfer of

samples to the laboratory and the analysis to be conducted on each bottle. 

Recommended Laboratory QA/QC Procedures

Method Blanks

For each batch of samples, method blanks should be run by the laboratory to determine the level of 

contamination associated with laboratory reagents and glassware. Results of the method blank

analysis should be reported with the sample results.

Laboratory Duplicates

For each batch of samples, one site should be used as a laboratory duplicate. For the laboratory

duplicate analysis, one sample will be split into two portions and analyzed twice. The purpose of

the laboratory duplicate analysis is to assess the reproducibility of the analysis methods. Results of

the laboratory duplicate analysis should be reported with the sample results. 

Matrix Spike and Spike Duplicates

Matrix spike and spike duplicates should be used to determine the accuracy and precision of the

analysis methods in the sample matrix. Matrix spike and spike duplicate samples are prepared by

adding a known amount of target compound to the sample. The spiked sample is analyzed to

determine the percent recovery of the target compound in the sample matrix. Results of the spike

and spike duplicate percent recovery are compared to determine the precision of the analysis. 

Results of the matrix spike and spike duplicate samples should be reported with the sample results.

External Reference Standards

External reference standards are artificial standards prepared by an external agency. The

concentrations of analytes in the standards are certified within a given range of concentrations. 

These are used as an external check on laboratory accuracy. One external reference standard
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appropriate to the sample matrix should be analyzed and reported at least quarterly by the

laboratory. If possible, one reference standard should be analyzed with each batch of samples. 

3.2.7 Recommendations for Data Management

A monitoring program may generate a considerable amount of information in a wide variety of

forms. Before you begin monitoring, you should establish procedures for managing the data you 

expect to generate and for presenting the results. 

Data management is an important component of your overall stormwater quality program. You

need to be able to store, retrieve, and transfer the diverse hard copy and electronic information

generated by your monitoring program. Before you begin monitoring, you should establish:

• A central file to accommodate the hard copy information your program is expected to

generate and practical dating and filing procedures to help ensure that superseded

information is not confused with current information.

• A database to accommodate digital information such as results of laboratory analyses,

information recorded by data loggers (e.g., flow, precipitation, in-situ water quality

measurements), maps in CAD or GIS, spreadsheets, etc. It is recommended that data be

stored and reported according to the protocols described in Section 4 of this Manual.

In many cases, the laboratory can provide the analytical results in an electronic format (i.e., an

“Electronic Data Deliverable” or EDD) that you can input directly to your database. This can

save time and reduce the potential for data entry errors. You should work with the analytical 

laboratory to determine if electronic data transfer makes sense for your program. 

If you do not have one, you may want to consider instituting an electronic filing system to help

ensure that draft reports (including text, tables, and graphics) and unvalidated analytical data can 

be easily distinguished from final reports and validated data. 

After data from the field and/or laboratory have been received and the originals have been stored 

in the project file, they may be routed to designated staff members who will perform one or more 

of the activities. These activities include data validation, calculations and analysis, and data

presentation.

Data reports should be reviewed for completeness as soon as they are received from the laboratory. 

Reports should be checked to ensure all requested analyses were performed and all required QA

data are reported for each sample batch. If problems with reporting or laboratory performance are

encountered, corrective actions (re-submittal of data sheets or sample re-analysis) should be

performed prior to final data reporting or data analysis. 

3.2.7.1 Database Requirements

This section provides general guidance on storing data and is based on QA/QC procedures

developed for the ASCE/EPA National Stormwater Best Management Practices Database. 
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Databases provide a significant level of control over the types of data that are valid for a

particular field. These “rules” limit the format and structure of individual fields. For example

any field where a date is present should be entered in the mm/dd/yyyy format. In addition, drop 

down boxes with lookup tables of relevant values can be used extensively in a database in order 

to maintain consistency between records. 

Additional fields can be included on forms in order to allow comments to be provided in each

data table. Water quality information can be entered in a tabular format where one row is used

for each sample and one column for each constituent. Macros can then be written to parse the

tabular format into a one-record-per-constituent format similar to that used in the National

Stormwater Best Management Practices Database (Database). 

Analysis of Database Links

In creating a complex database, records are often linked between tables. Once all data have been 

entered into a database, a check of the established links should be done between the tables

storing event data for flow, precipitation, and water quality. The start and stop date and time of

each water quality record can be checked against the date and time of the linked flow and

precipitation event. This can be conducted using a combination of database queries by

identifying dates that do not pair up. All dates that do not match should be flagged and the links 

should be checked by hand. This process ensures internal consistency between the separate

tables in the database. Where any errors are encountered, the original document should be

consulted. 

Analysis of Outlying Records

An analysis of the data contained in database tables can be done to identify outlying values that

resulted from typographical errors during data entry (e.g., wrong decimal place), unit errors (e.g., 

mg instead of μg), and incorrectly assigned STORET Codes. Two types of outlying records can 

appear in the database: data entry errors (i.e., manifestations of the data extraction process) and

real outlying values (i.e., values present in a study’s original documents). The efforts conducted 

during outlier analysis seeks to identify and correct data entry errors. The assumption in looking 

for outlying errors is that recorded water quality parameter values lie within an expected

reasonable range. Values that are outside of this range may be incorrectly entered into the

database and deserve close attention. This method is particularly useful for identifying errors in

units. 

The usefulness of identification of outliers varies from constituent to constituent. For example

any mistyped entries are easily identified in pH or temperature data. If one digit is off in pH or

temperature data it is quite obvious, and, thus, there is a greater degree of confidence in the

quality of the data based on an outlier analysis of pH or temperature than for other water quality

parameters. Unfortunately, on the other end of the scale are other parameters such as Fecal

Coliform. Even an error in excess of two orders of magnitude is not readily identified in a series 

of Fecal Coliform records, and thus an outlier analysis provides little or no additional

information about the quality of Fecal Coliform records. 
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Sample Comparisons Between Original Documents and Final Data Set

Finally, to better quantify the quality of the data stored in a data set, sample comparisons can be 

made of the data set with the original source documents. A percentage of all records can be

checked in order to assess data quality. All errors identified in these documents should be

flagged and corrected. The sample comparisons conducted provide insight into overall quality of 

the data entry process. 

Digital Conversion of Data 

In the event that data is provided in a digital format that is different from the designated

ASCE/EPA BMP Database format (see Section 3.4 of this Guidance), conversion of the data is

necessary. Data can be easily imported between database, spreadsheet, and word processing

software in more recent versions of most software. However, this data should be carefully

evaluated and checked for transition errors. Often, different programs will automatically round

numbers to a certain decimal and then truncate the remaining digits. Evaluation and comparison

between the original document or database and the converted data is recommended for all

records to ensure that the quality of the data is maintained. 

Double Data Entry and Optical Character Recognition

Before data entry begins, both digital and hard copy data extraction/entry forms should be

created along with instructions for the data entry process. These forms should be based directly

on the database table structure. This methodology will allow the data collection and entry

process to take place in a consistent, uniform environment. 

To improve the quality of data entry during any process that requires hand entry of large data

sets, it is typically necessary to implement a double entry procedure with automated flagging and 

formal correction of all inconsistencies. This method should be considered as a potential part of 

any data entry protocols. This is one of the few systematic methods for ensuring very small error 

rates. In circumstances where significant understanding of the source of the data is required on

the part of the data entry personnel, the cost of this approach could be prohibitive.

In some cases, optical character recognition (OCR) can be used effectively to increase the speed

of data entry. In cases where OCR is used, all results should be hand checked to ensure data

quality. The data resulting from OCR typically contains a smaller number of errors compared to 

hand entered data, depending on format of data.

3.3 Phase III - Implementation of Monitoring Plan

3.3.1 Training of Personnel

Each member of the monitoring team must receive whatever training is necessary to properly

perform his or her assigned roles. Generally, the first step is for each team member (including

back-up personnel) to review the monitoring plan and health and safety plan. Next, the team

members attend an initial orientation session that includes a "dry run" during which team
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members travel to their assigned stations and simulate monitoring, sample documentation,

packaging, etc., under the supervision of the instructor (usually the principal author of the

monitoring plan). Health and safety precautions should be reinforced during the dry run. 

Periodic "refresher" orientation sessions should be conducted after long dry periods, or when the 

monitoring team composition changes.

3.3.2 Installation of Equipment

If you plan to use manual monitoring techniques, equipment installation may be unnecessary. If 

you plan to use automated monitoring methods, you must install the sampling and flow

measurement equipment at the monitoring locations. Equipment installation procedures vary

depending on the specific equipment and the configuration of the monitoring location. Follow

the equipment manufacturer's instructions for installation. Some general recommendations for

equipment installation are listed below:

• Personnel must follow the health and safety plan when installing equipment. Some

monitoring locations may require use of protective clothing, traffic control, combustible gas 

meters, and special training in confined space entry procedures.

• Bubbler tubes, pressure transducers, and velocity sensors typically are mounted on the

bottom of the channel in the middle of the channel cross-section, facing upstream. Ultrasonic 

depth sensors typically are mounted above the water surface.

• In most cases, the automated sampler intake tube is mounted facing upstream and parallel to

the flow in order to reduce any flow distortion that could bias the sampling of suspended

solids. The intake often is covered with a strainer to prevent clogging.

• Probes, sensors, and intake lines usually are anchored to the pipe or channel. The intake

tubing should be anchored throughout its length so that it will not bend, twist or crimp under 

high flows.

• Weirs and flumes must be secured to the bottom of the pipe or channel. If the monitoring

location is in a swale, the weir or flume cutoff walls must be buried in each bank so that the

structure extends all the way across the channel and all flow is directed through the weir or

flume.

• If not installed inside a manhole vault, the flow meter and automated sampler should be

placed in a sturdy shelter to protect the equipment from vandalism and other damage.

• If batteries are used as the power supply, install fresh batteries at the frequency

recommended by the manufacturer or before each anticipated storm monitoring event.
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3.3.3 Testing and Calibrating Equipment

Water quality probes (e.g., pH, conductivity), automated samplers, and flow meters must be

periodically calibrated in order to ensure reliable operation and credible results. Typical

calibration procedures are summarized in this section; however, you should always follow the

manufacturer's instructions when calibrating a specific monitoring device. 

Calibration of pH meters, conductivity meters, dissolved oxygen meters, and other water quality

instruments generally involves two steps:

1. Use the instrument to measure a known standard and determine how much the

instrument's measurement differs from the standard. 

2. Adjust the instrument according to the manufacturer's instructions until it

provides an accurate measurement of the standard.

Automated sampling equipment should be calibrated after installation to ensure it pumps the

correct volume of sample. The condition of the sampler pump and intake tubing, the vertical

distance over which the sample must be lifted, and other factors can affect the volume drawn. 

Therefore, you should test the sampler after installation and adjust the sampler programming if

necessary to be sure the system consistently draws the correct sample volume.

Flow meters can be affected by the hydraulic environment in which they are placed;

consequently, they should be calibrated after installation to ensure accuracy. Because sediments, 

debris, and other materials carried by stormwater can damage or clog bubbler tubes and pressure 

transducers used for depth measurements, they must be frequently inspected and calibrated by

checking the flow depth with a yard stick or staff gauge. Ultrasonic velocity sensors and other

instruments that measure flow rate must also be inspected and checked against velocity

measurements made using a current meter.

3.3.4 Conducting Monitoring

After you have completed the advance preparations described above, you are ready to begin

monitoring. 

The general steps for automated monitoring are:

1. Perform routine inspection and maintenance to help ensure that the equipment will

function properly when a storm event occurs.

2. Keep track of precipitation. After each storm, check the local rainfall records (or

preferably a rain gauge at or near the center of the basin) to see if the amount of

precipitation and the antecedent dry period met your pre-determined criteria. 
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• If the storm did not meet your criteria, remove the sample bottles from the sampler

and replace them with clean bottles. Empty the sample bottles and arrange for them

to be cleaned.

• If the storm criteria were met, remove the sample bottles. Check them to be sure they 

received the proper amount of sample. Check the sampling times against the storm

duration to see how much of the storm was sampled. If this meets your criterion,

complete the sample labels, chain-of-custody form and other field documentation,

then deliver the samples to the laboratory for analysis.

3. If the sampler overfilled or underfilled the sample bottles, refine the sampler

programming.

4. Reset the sampler and inspect all of its systems for possible damage or clogging so that it 

will be ready to sample the next storm.

The general steps for manual monitoring are:

1. The monitoring team leader or another designated person tracks the weather forecasts.

2. When the weather forecasts indicate that a potentially acceptable storm is approaching,

the monitoring team leader contacts the monitoring team and the analytical laboratory. If 

any of the primary team members are unavailable, the monitoring team leader arranges

for back-ups. The team members check their instructions, communications protocols,

monitoring equipment, and supplies to ensure they are ready. 

3. The monitoring team leader contacts NOAA (or some other meteorological service, if

better information is available) to get updated forecasts as the storm approaches. When

the forecasts indicate that the storm is likely to start within the next few hours, and it still 

appears likely to meet the storm selection criteria, the team leader directs the team

members to proceed to their assigned monitoring stations so that they arrive before the

predicted start time. The team leader also alerts the lab that samples are likely to be

delivered soon.

4. The team members travel to their assigned locations and start collecting samples and

taking flow measurements as soon as possible after stormwater runoff begins. They fill

out the sample labels, chain-of-custody forms, and other field documentation. 

5. During monitoring, the team members may contact the team leader (usually by cellular

phone) to ask questions, notify him or her of changing conditions, receive direction, etc.

6. After samples have been collected, they are shipped or delivered to the analytical

laboratory.

7. If the lab is to prepare flow-weighted composite samples, the monitoring team members

must use the flow data they collected to determine the amount of each sample to be used
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to form the composite. Usually, the team will calculate the amounts using a spreadsheet

and fax the completed spreadsheet to the lab.

If you are using manual methods, you will need to maintain a vigilant "weather watch.” This is

essential if you wish to monitor the initial runoff from a storm event. You need some advance

notice of an impending sampling event in order to have enough time to contact the monitoring

team, arrange for back-ups if the primary members are unavailable, notify the analytical

laboratory, work out communications protocols, pick up ice, and travel to the monitoring

locations. Also, if your are able to obtain reasonably accurate estimates of storm start times, you 

can reduce the amount of stand-by time for your monitoring team. Finally, a close weather

watch can help reduce the risk of a "false start" which can occur when a predicted storm fails to 

materialize or turns out to be a brief shower.

3.3.5 Coordinate Laboratory Analysis

Most stormwater monitoring programs involve laboratory analysis. Exceptions include (1) field

screening programs that rely solely on visual observations and field test kits, and (2) programs

that rely on "in-situ" monitoring of indicator parameters (e.g., pH, dissolved oxygen, turbidity)

using probes and data loggers. 

It is a good idea to involve laboratory personnel in identifying the analytical methods

establishing communications protocols and QA/QC protocols. Typically, the laboratory will

provide the pre-cleaned sample bottles and distilled/deionized water used for monitoring.

Your mobilization protocols should include notifying the laboratory when a storm monitoring

event appears imminent. They should also include contacting the laboratory shortly after the

monitoring event to ensure that the samples were received in good condition and to answer any

questions the lab may have regarding the analyses to be conducted. Also, it is a good idea to

periodically contact the laboratory while the analyses are being conducted. Frequent

communication with the laboratory helps reduce the risk of incorrect analysis and other potential 

unpleasant "surprises."
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3.4 Phase IV - Evaluation and Reporting of Results

3.4.1 Validate Data

You should evaluate the quality or adequacy of the laboratory analytical results before you

interpret the results. This evaluation is known as “data validation” or data quality review. The

basic steps are listed below.

1. Check that all requested analyses were performed and reported. Check that all requested

QA/QC samples were analyzed and reported. 

2. Check sample holding times to ensure that all samples were extracted and analyzed within the 

allowed sample holding times. 

3. Check that the laboratory’s performance objectives for accuracy and precision were achieved. 

This includes a check of method blanks, detection limits, laboratory duplicates, matrix spikes and 

matrix spike duplicates, laboratory control samples, and standard reference materials. 

4. Check that field QA/QC was acceptable. This includes a check of equipment blanks, field

duplicates, and chain-of-custody procedures. 

5. Check that surrogate recoveries were within laboratory control limits.

6. Assign data qualifiers as needed to alert potential users of any uncertainties that should be

considered during data interpretation.

If the laboratory and field performance objectives were achieved, further data validation is not

generally needed. Specifics of the instrument calibration, mass spectral information, and run

logs are not usually recommended for review unless there is a suspected problem or the data are 

deemed critical. If performance objectives were not achieved (e.g., due to contaminated blanks,

matrix interference, or other specific problems in laboratory performance), the resulting data

should be qualified. EPA functional guidelines for data validation (EPA 1994a,b) should be used 

as a guide for qualifying data.

3.4.2 Evaluate Results

After the chemical data have been validated, you should perform a preliminary data evaluation. 

The main purpose of the preliminary evaluation is to determine whether you have obtained

enough information of sufficient quality to meet BMP assessment goals. If the answer is no, you 

should continue monitoring until you have collected sufficient information. If the answer is yes, 

you should proceed with the definitive evaluations that are best suited to your specific objectives.
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3.4.2.1 Preliminary Data Evaluation

After the analytical results have been validated, consider graphing the flow and rainfall data vs. 

time for each storm event in order to produce a storm hydrograph (flow rate versus storm

duration). It is often helpful to plot rainfall volume versus storm duration on the same graph. In 

addition, you should denote the times when the grab or composite samples were collected. This

information can be very helpful in interpreting the chemical results.

Generally, stormwater quality variability is so high that statistical evaluation is not worthwhile 

until you have monitored several events (at least four). You should conduct an initial statistical

analysis using the validated chemical data. This analysis will provide summary statistics that

indicate how well your sample results represent stormwater quality at a given site. Summary

statistics include sample mean, variance, standard deviation, coefficient of variation, coefficient

of skewness, median, and kurtosis. Stormwater quality typically exhibits a lognormal

distribution (EPA 1983; WCC 1989). Therefore, you should calculate these descriptive statistics 

based on an assumed lognormal distribution. Non-detects should be included in calculating the

initial statistics using a maximum likelihood estimator approach. 

The initial statistical analysis can help you determine whether it will be useful to statistically test 

various hypotheses regarding the existing data set. For example, if the standard deviations are

several times larger than the means (i.e., the coefficient of variation is 3 or more), hypothesis 

testing may not be worthwhile. You may need to conduct additional monitoring to compensate

for the observed variability and allow statistically significant differences to be discerned. 

3.4.2.2 Definitive Evaluations

If your initial statistical analysis indicates that your samples are representative of water quality at 

the site(s) in question, you should conduct additional statistical analyses (or perhaps modeling)

as needed to answer the key questions about your stormwater catchment area. 

Consider the initial statistics when selecting the statistical procedure(s) you will use to answer

the key questions about your stormwater catchment area. For example, if the data set does not

appear to follow a normal or lognormal distribution, or if the data set contains a high proportion 

(i.e., >15%) of non-detects, non-parametric tests may be more appropriate than parametric tests. 

The results of your monitoring program may also serve as input to a water quality model. 

Loadings can be calculated using SUNOM (previously the simple model, Schueler 1987), or one 

of several dynamic models. The simple model estimates the mean pollutant loading from a

particular outfall or subbasin to a receiving water. A dynamic model takes into account the

variability inherent in stormwater discharge data including variations in concentration, flow rate, 

and runoff volume. A dynamic model can therefore be used to calculate the entire frequency

distribution for the concentration of a pollutant and the theoretical frequency distribution (i.e.,

the probability distribution) for loadings from the outfall or subbasin. Thus, the modeler can

describe the effects of observed discharges on receiving water quality in terms of the frequency

by which water quality standards are likely to be exceeded. Dynamic models include EPA's 
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Stormwater Management Model (SWMM) and Hydrologic Simulation Program Fortran (HSPF), 

the U.S. Army Corps of Engineers' Storage, Treatment, Overflow, Runoff Model (STORM), and 

Illinois State Water Survey's Model QILLUDAS (or Auto-QI) (EPA 1992).

3.4.3 Report Results

The results of your monitoring program should be presented in one or more reports. The

appropriate report frequency and content depends on your monitoring program objectives and

your audience. If you are monitoring to comply with a permit, the permit will generally specify

the minimum frequency and content of the reports. 

Most monitoring programs involve two types of reports: status (or progress) reports and final

reports. To determine the appropriate frequency of status reports, consider your monitoring

frequency and objectives, particularly any permit requirements. Many programs produce status 

reports on a quarterly or semi-annual basis. A typical status report may contain the following

information:

• Summary of work accomplished during the reporting period

• Summary of findings

• Summaries of contacts with representatives of the local community, public interest

groups, or state federal agencies

• Changes in key project personnel

• Projected work for the next reporting period

You should prepare more comprehensive reports at the end of the monitoring program (for shortterm programs) or at the end of each year (for multi-year programs). Consider including the

above-listed information and the following information in your annual or final report:

• Executive summary

• Monitoring program background and objectives

• Monitoring station descriptions, analytical parameters, analytical methods, and method

reporting limits

• Summary descriptions of the conditions and stations, equipment inspections and

calibrations, etc.

• Sample collection, precipitation, and flow measurement methods
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• Flow, precipitation, and water quality results and data validation information

• Qualitative and statistical data evaluations/hypothesis testing as required for your specific 

program objectives (see Section 3.4.2 and Appendix I)

• Summary and conclusions, including any caveats or qualifying statements that will help

the reader understand and use the reported information in the appropriate context

• Recommendations regarding management actions (e.g., changes in monitoring program,

implementation of BMPs)

3.4.3.1 National Stormwater BMP Database Requirements

This section is designed to provide guidance for consistent reporting of results collected from

BMP monitoring studies. The protocols described are based on those specified in the National

Stormwater Best Management Practices Database, which has been developed by the Urban

Water Resources Research Council of ASCE under grant funding from EPA to serve as a tool for 

data organization and reliable comparison of BMPs. Minimum requirements for acceptance in

the National Database are outlined in this section, and standard format examples that can be used 

as templates for reporting results of stormwater monitoring studies are provided.

The National Stormwater BMP Database was developed to provide a scientifically sound tool for 

the determination of the effectiveness of BMPs under various conditions for a range of design

parameters. The data fields included in this database have undergone intensive review by many 

experts and encompass a broad range of parameters including test site location, watershed

characteristics, climatic data, BMP design and layout, monitoring instrumentation, and

monitoring data for precipitation, flow and water quality. In order to effectively compare the

performance of different BMPs under a variety of conditions, a set of “required” database fields

were identified. These “required” fields are considered the minimum requisites for acceptance

into the National Stormwater BMP Database. The database requirements vary with the different 

types of BMPs, and special requirements exist for unique hydraulic conditions. Database

requirement categories and fields are as follows:

1) Information required for all BMPs (Table 3.5)

• General Test Site Information

• Watershed Information

• Monitoring Station Information

• Precipitation Data

• Flow Data

• Water Quality Data
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Table 3.5: National Stormwater BMP Database requirements for all BMPs

Data Element Description

General Test Site Information

BMP Test Site Name Name that site is known by locally.

City City closest to test site.

State State where test was performed.

Zip Code Zip code of the test site.

Country Country where the test site is located.

Altitude Altitude to nearest 100 ft or 30 m.

Sponsoring and Monitoring Agencies for Test Site

Address Includes monitoring and sponsoring agency name and contact 

information.

Watershed Information

Subject Watershed Name Name that watershed is referred to locally.

Total Watershed Area Topographically defined area drained by system.

Percent (%) Impervious Area Total percent of impervious surface in watershed.

Regional Climate Station (US) Regional climate station in US that is most relevant to test site.

Land Use Information Description of land uses (only required for non-structural BMPs).

Monitoring Stations

Station User-defined name for subject monitoring station.

Identify Upstream BMP BMP upstream of the monitoring point (if any).

Identify Relationship to 

Upstream BMP

Identify the relationship of the monitoring station to the upstream 

BMP (i.e. inflow, outflow or not applicable).

Identify Downstream BMP BMP downstream of the monitoring point (if any).

Identify Relationship to 

Downstream BMP

Identify the relationship of the monitoring station to the 

downstream BMP (i.e. inflow, outflow or not applicable).

Monitoring Instrumentation

Monitoring Station Name Select monitoring station where the instrument is located.

Precipitation Data

Monitoring Station Name Identify monitoring station where precipitation event was 

monitored.

Storm Runoff and Base Flow Data

Monitoring Station Name Select monitoring station where flow event was monitored.

Type of Flow Base flow or stormwater runoff.

Flow Start Date Month, day and 4-digit year (e.g. 01/01/1998).

Total Bypass Volume (if any) Total runoff volume minus runoff volume influent to BMP.

Total Storm Flow Volume into or 

from BMP

Total runoff volume minus the bypass volume.

Dry Weather Base Flow Rate Flow rate during dry-weather conditions.

(Table continued on the following page)
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Water Quality Sampling Event

Monitoring Station Name Select monitoring station where samples were collected.

Related Flow-Event Select flow data corresponding to water quality data.

Date Water Quality Sample

Collected

Month, day and 4-digit year the water quality sample was 

collected.

What Medium Does the Instrument 

Monitor

e.g. Groundwater, surface runoff.

Water Quality Parameters STORET water quality parameters analyzed.

Value Value of measured constituent. 

Unit Units of measured constituent.

Qualifier Select STORET qualifier code.

2) Data required for structural BMPs (Table 3.6)

Table 3.6: National Stormwater BMP Database requirements for structural BMPs

Data Element Description

Structural BMP Information

Structural BMP Name Common name by which BMP is referred to locally.

Structural BMP Type Select the type of BMP being monitored at the site (drop-down 

list).

Date Facility Was Put Into Service Month, day and 4-digit year facility became operational.

Number of Separate Inflows Number of inflows into the facility.

Describe the Type and Design of 

Each BMP Outlet

Description of the outlet configuration (i.e. Perforated riser).

Is the BMP Designed to Bypass 

When Full?

Select “Overflow” or “bypass” characteristics of BMP.

BMP Drawing Plan view and profile of BMP (in bitmap format for database).

3) Information required for non-structural BMPs (Table 3.7)

Table 3.7: National Stormwater BMP Database requirements for non-structural BMPs

Data Element Description

Non-structural BMP Information

Non-structural BMP Type Type of non-structural BMP (e.g. educational, maintenance 

practices, etc.).

Non-structural BMP Name The name by which the non-structural BMP is referred to 

locally.

Date Test Began Month, day and 4-digit year.

Describe the Quantity or Measure of 

the BMP Being Practiced

Measure of the educational, maintenance, recycling or source 

control BMP.
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4) Individual structural BMP requirements (Table 3.8) for:

• Detention Basins.

• Grass Filter Strips.

• Infiltration Basins.

• Media Filters.

• Porous Pavement.

• Retention Ponds.

• Percolation Trenches and Dry 

Wells.

• Wetland Channels and Swales.

• Wetland Basins.

• Hydrodynamic Devices.

Table 3.8: National Stormwater BMP Database requirements for individual structural BMPs

Data Element Description

Detention Basin Design Data

Water Quality Detention Volume The volume of runoff that is captured and released over time.

Water Quality Detention Area (when 

full)

The area of water surface in basin at full water quality detention 

volume.

Water Quality Detention Basin

Length

Distance between inflow and outflow (average for multiple inflows).

Detention Basin Bottom Area Area of the bottom of the detention basin, including bottom stage 

area.

Brim-full Volume Emptying Time Emptying time of water quality detention volume.

Half Brim-full Volume Emptying 

Time

Emptying time of lower half of water quality detention volume.

Bottom Stage Volume (if any) The volume of the lower “bottom stage” of the detention basin.

Bottom Stage Surface Area The surface area of the lower “bottom stage” of the detention basin.

Is there a Micro Pool? “Yes” or “No” indication of micropool.

Forebay Volume Volume of the forebay portion of the detention basin.

Forebay Surface Area Surface area of the forebay portion of the detention basin.

Describe Vegetation Cover Within 

Basin

List and description of types of vegetation on the basin sides and 

bottom.

Flood Control Volume (if any) Volume in excess of water quality detention volume.

Design Flood Return Periods Design return period if basin is designed for flood control.

Grass Filter Strip Design Data

Grass Strip Length Length of strip in the direction of flow.

Grass Strip Slope Slope of the strip along the flow path.

Flow Depth During 2-Year Storm Design depth of flow during the 2-year peak flow.

2-Year Peak Flow Velocity Design flow velocity during the 2-year peak flow.

Describe Grass Species and 

Densities

List of grass species and their densities.

Is Strip Irrigated? “Yes” or “no” indication of irrigation.

(Table continued on the following page)
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Infiltration Basin Design Data

Capture Volume of Basin The design runoff capture volume of the basin.

Surface Area of Capture Volume 

(When Full)

The area of the water surface in the infiltration basin, when full.

Infiltrating Surface Area The plan area of the surface used to infiltrate the water quality 

volume.

Depth to Seasonal High 

Groundwater Table

Depth from basin bottom to seasonal high groundwater table.

Depth to Impermeable Layer (if any) Depth from basin bottom to impermeable layer, if is present.

List of Plant Species List of plant species and densities on infiltrating surface.

Describe Granular Material on 

Infiltrating Surface (if any)

Description of granular material depth and porosity.

Media Filter Design Data

Permanent Pool Volume, Upstream 

of Filter Media (if any)

Volume of the permanent pool, if pool is part of filter basin.

Permanent Pool Surface Area Area of water surface of permanent pool.

Permanent Pool Length Distance between inflow and outflow (average for multiple inflows).

Surcharge Detention Volume The design water quality detention volume, including the volume 

above the filter.

Surcharge Detention Volume 

Surface Area

The surface area of the design water quality capture volume.

Surcharge Detention Volume's 

Design Drain Time

The drain time (in hours) of the water quality capture volume.

Surcharge Detention Volume 

Design Depth

Depth of water quality capture volume.

Media Filter Surface Area Surface area of the media filter.

Angle of Sloping or Vertical Filter Inclination of filter in degrees above the horizontal plane.

Number of Media Filter Layers Number of layers of different filter material in BMP.

Describe Depth and Type of Each 

Filter Media Layer

Description of the type and depth of media used in the filter.

(Table continued on the following page)
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Porous Pavement Design Data

Porous Pavement Surface Area Surface area of porous pavement.

Depth to Seasonal High 

Groundwater Table

Depth from pavement surface to seasonal high groundwater table.

Depth to Impermeable Layer (if any) Depth from pavement surface to impermeable layer, if present.

Infiltration Rate Rate of infiltration for site soils under saturated conditions. 

Type of Granular or Other Material 

Used Below Pavement

Description of the type and depth of each granular material layer 

under the porous pavement.

Porosity of Granular Material (%) The volumetric portion of the filter material that is not occupied by 

solid matter, expressed as a percent of the total filter volume.

Total Storage Volume Above 

Pavement (if any)

The volume of water stored in depressions or as a result of 

attenuation (if any) above the porous pavement surface.

Estimated Drain Time of the 

Storage Volume Above the 

Pavement (if any)

Drain time of holding areas above pavement, if any.

Total Storage Volume Under 

Pavement (if any)

Net available volume of pore spaces in the granular materials 

beneath the porous pavement.

Estimated Drain Time of Storage 

Volume Under Pavement

Total emptying time for water stored in granular materials.

Does Porous Pavement Have 

Underdrains?

“Yes” or “no” indication of presence of underdrains.

Retention Pond Design Data

Volume of Permanent Pool Volume of permanent pool in structure.

Permanent Pool Surface Area Area of water surface of permanent pool.

Permanent Pool Length Length of the permanent pool measured along the axis between the 

inflow and outflow. For more than one inflow, take an average.

Littoral Zone Surface Area The surface area of the bank above the permanent pool that is 

periodically covered with water during a storm event.

Water Quality Surcharge Detention 

Volume (when full)

Water quality detention volume above permanent pool.

Water Quality Surcharge Area 

(when full)

The surface area (plan view) of the water quality surcharge 

detention volume.

Water Quality Surcharge Basin

Length

Length of the water quality surcharge pool measured along the axis 

between the inflow and outflow. For more than one inflow, take an 

average.

Brim-full Emptying Time for 

Surcharge

Emptying time of water quality detention volume down to the 

permanent pool.

Half Brim-full Emptying Time for 

Surcharge

Emptying time of lower half of surcharge detention volume down to 

the permanent pool.

Forebay Volume Volume of the forebay portion of the detention basin.

Forebay Surface Area Surface area of the forebay portion of the detention basin.

Describe Vegetation Cover Within 

Basin

List and description of vegetation on basin sides and floor.

Flood Control Volume (if any) Volume in excess of the retention basin water quality surcharge 

detention volume.

List Design Flood Return Period (in 

years)

Design return periods if pond was designed for flood control.

(Table continued on the following page)
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Percolation Trench and Dry Well Design

Percolation Trench/Well Surface 

Area

The surface area of the top of the percolation trench/well.

Percolation Trench/Well Length Length of percolation trench or diameter of the well.

Percolation Trench/Well Depth The depth of trench or well that is exposed to permeable soils.

Depth to Seasonal High 

Groundwater Table

Depth below the bottom of the trench or well to the seasonal high 

groundwater table.

Depth to Impermeable Layer (if any) Depth below the bottom of the trench or well to impermeable layer, if 

impermeable layer is present.

Depth and Type of Each Soil Layer 

Adjacent to and Below Trench/Well

Description of the stratification and the depth of each layer of soils at 

the BMP site.

Type of Gradation of Granular 

Materials Used in Trench/Well

Description of the type and depth of granular material used in the 

trench or well.

Was Geotextile Used Above 

Granular Trench Fill?

“Yes” or “no” indication of geotextile use above granular fill.

Was Geotextile Used on the Side of 

Granular Fill?

“Yes” or “no” indication of geotextile use on sides of granular fill.

Was Geotextile Used on the Bottom 

of Granular Fill?

“Yes” or “no” indication of geotextile use below granular fill.

Give Porosity (%) of the Granular 

Fill

The volumetric portion of the granular material that is not occupied 

by solid matter, expressed as a percent of the total volume.

Total Storage Pore Volume in 

Trench

Volume of available pore space in the trench or well.

Describe Type of Geotextile Used Description of types and locations of geotextile fabrics.

Hydraulic Conductivity of Adjacent 

Soil

Hydraulic conductivity of the soils adjacent to the trench or well.

Groundwater Flow Gradient Slope of the local groundwater table without influence from the BMP.

Wetland Channel and Swale Design Data

Length of Channel/Swale Length of channel or swale from stormwater inflow to outflow point.

Longitudinal Slope of 

Channel/Swale

Measured slope between grade control structures in swale.

Bottom Width of Channel 

/Swale

Average width between side slopes.

Side Slope of Channel Swale Average slope of swale sides.

2-Year Flow Design Depth in 

Channel/Swale

Average depth of water in channel/swale during 2-yr flow.

2-Year Peak Design Flow Velocity Design velocity for 2-yr flow.

Type of Plant Species in Wetland

Zone or Swale

List and description of plant species, percent of cover and densities.

(Table continued on the following page)
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Wetland Basin Design Data

Volume of Permanent Pool Volume of permanent pool in structure.

Permanent Pool Surface Area Surface area of permanent pool.

Permanent Pool Length Length of the permanent pool of water, measured at the water 

surface along the axis of the inflow and outflow (average for multiple 

inflows).

Water Quality Surcharge Detention 

Volume (when full)

Water quality detention volume above permanent pool.

Water Quality Surcharge Area 

(when full)

The surface area of the water quality surcharge detention volume.

Water Quality Surcharge Basin 

Length

Water quality surcharge basin length, measured at the water surface 

along the axis of the inflow and outflow (average for multiple 

inflows).

Brim-full Emptying Time for 

Surcharge

Emptying time of water quality detention volume down to the 

permanent pool.

Half Brim-full Emptying Time for 

Surcharge

Emptying time of lower half of surcharge detention volume down to 

the permanent pool.

Forebay Volume Volume of the forebay portion of the detention basin, when full.

Forebay Surface Area Water surface area of the forebay portion of the detention basin.

Describe Vegetation Cover Within 

Basin

Description of types of vegetative cover within the basin.

Flood Control Volume (if any) Volume in excess of the water quality detention volume.

List Design Flood Return Period (in 

years)

Design return period if basin is designed for flood control.

Wetland Surface Area The surface (plan view) area of the total wetland.

Percent of Wetland Pond with 12 

inches Depth

Percent of wetland surface area with less than 12 inches of standing 

water.

Percent of Wetland Pond with12-24" 

Depth

Percent of wetland surface area with 12-24 inches of standing water.

Percent of Wetland Pond with 24-

48" Depth

Percent of wetland surface area with 24-48 inches of standing water.

Percent of Wetland Pond with >48" 

Depth

Percent of wetland surface area with greater than 48 inches of 

standing water.

Percent of Wetland Basin's Area 

That is Meadow Wetland

Percent of wetland surface area with meadow wetlands (no standing 

water).

List All Known Plant Species in the 

Wetland

List of plant species, percent of cover and densities.

Hydrodynamic Devices

Volume of Permanent Pool Volume of permanent pool in structure.

Permanent Pool Surface Area Surface area of the permanent pool.

Permanent Pool Length Distance between inflow and outflow (average for multiple inflows).

Water Quality Surcharge Detention 

Volume (when Full)

Water quality detention volume above permanent pool.

Inlet Chamber Volume (if any) Volume of the inlet chamber portion of the hydrodynamic device.

Brim Full Emptying Time for 

Surcharge

Emptying time of water quality detention volume down to the 

permanent pool.

Half Brim Full Emptying Time for 

Surcharge

Emptying time of lower half of surcharge detention volume down to 

the permanent pool.
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5) Requirements for non-structural and structural BMPs that are based on minimizing directly 

connected impervious areas (Table 3.9).

Table 3.9: National Stormwater BMP Database requirements for non-structural BMPs and 

structural BMPs that are based on minimizing directly connected impervious areas

Data Element Description

Watershed Information

Total Length of Grass-Lined 

Channel

Total length of natural and grass-lined channels in watershed.

Total Watershed Area Disturbed Total watershed area that is actively disturbed or under construction.

Percent Irrigated Lawn and/or 

Agriculture in Watershed

Percent of lawn or agricultural areas that are irrigated.

Percent of Watershed Served by 

Storm Sewers

The percent of watershed served by storm sewers.

Average Runoff Coefficient Based on area-weighted average.

Soil Type NRCS soil type.

Type of Vegetation Type of vegetation predominant in pervious area.

Roads and Parking Lots

Total Paved Roadway Area Total area of paved roads, streets and alleys in watershed..

Total Length of Curb/Gutter on 

Paved Roads

Total length of curb/gutter on paved roads.

Total Unpaved Roadway Area Total unpaved roadway area.

Total Length of Curb/Gutter on 

Unpaved Roads

Total length of curb/gutter on unpaved roads.

Percent of Paved Roads Draining to 

Grass Swales/Ditches

Percent of paved roads draining to swales/ditches.

Percent of Unpaved Roads Draining 

to Grass Swales/Ditches

Percent of unpaved roads draining to swales/ditches.

Type of Pavement on Roads, 

Streets and Alleys

Description of type of pavement (i.e. concrete, asphalt, etc.).

Total Paved Parking Lot Area Total area of paved parking lots in the watershed.

Total Length Curb/Gutter on Paved 

Lots

Total length curb/gutter on paved lots.

Total Unpaved Parking Lot Area Total unpaved parking lot area.

Total Length Curb/Gutter on 

Unpaved Lots

Total length of curb/gutter on unpaved lots.

Percent Paved Lot Area Draining to 

Grass Swales

Percent of paved lot area draining to swales.

Percent Unpaved Lot Area Draining 

to Grass Swales

Percent of unpaved lot area draining to swales.

Type of Pavement in Parking Lots Type of pavement in parking lots.
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6) Requirements for structural BMPs that are based on minimizing directly connected 

impervious areas (Table 3.10)

Table 3.10: National Stormwater BMP Database requirements for structural BMPs that are 

based on minimizing directly connected impervious areas

Data Element Description

Watershed Information

Storm Sewer Design Return Period Most common design return period for the storm sewers in the 

watershed.

Average Watershed Slope Average unit less slope of the watershed (i.e. ft/ft, in/in).

NRCS Hydrologic Soil Group Dominant NRCS hydrologic soil group.

3.4.3.2 Standard Format Examples

The purpose of this section is to provide standard format examples that can serve as a guidance

tool for developing monitoring plans and promoting consistent reporting and documentation of

stormwater monitoring studies. These forms include, but are not limited to, the required data

entry fields for the National Stormwater BMP Database. The database requirements were used

as a guideline for development and organization of forms because of its ability to aid in

consistently evaluating BMP effectiveness under different conditions. The following sections

provide standardized document formats that can be used as a template when performing a BMP

monitoring study. Each form is categorized based on the sub-sections presented in the National 

Stormwater BMP Database.

General Test Site Information

The general test site information form provides data to aid in the identification of the testing

location. Location information is important because it enables identification of the general

climatic conditions under which a BMP was evaluated. Data reported on this form also provides 

a cross-link with other national EPA databases. The general test site information form includes

data about the sponsoring and monitoring agencies conducting the study and georeferencing

information for exact identification of the site location. A detailed description of the data

element fields for the general test site information form is available in Table 3.11. The General

Test Site Information form, Form A, follows:
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Table 3.11: General test site form data element descriptions

Data Element Description

BMP Test Site Name1 Name that the site is known by locally (e.g., Shop Creek, First Bank).The site 

may contain more than one BMP, but ONLY if the watersheds tributary to 

these BMPs are virtually identical.

City1 City closest to the test site. The site does not have to be within the city limits.

County County in which test site is located.

State1State where test was performed (2 characters).

 Zip Code1Zip code of the test site.

Country1 Country where the test site is located (2 characters).

Time Zone Time zone in which the BMP test site is located off-set in hours from 

Greenwich Mean Time. For example, in the United States, Eastern Time is -5, 

Central Time is -6, Mountain Time is -7 and Pacific Time is -8.

Georeferencing Information

USGS Quadrangle Map 

Name

U.S. Geological Survey (USGS) 7.5-minute map on which the site can be 

located. This information should be provided for U.S. sites only.

Principal Meridian Local or international meridian from which the degrees of longitude locating 

the BMP test site are measured.

Range Range identifies the site distance and direction (east or west) from the 

selected principal meridian. For example, Range 60 West (R60W). This 

information can be found on a U.S. Geological Survey quadrangle map (U.S. 

sites only).

Township Townships are located by their distance and direction (north or south) from a 

selected baseline. For example, Township 2 North (T2N) (U.S. sites only).

Section Section is a land area usually containing one square mile (640 acres) that can 

be identified on a U.S. Geological Survey quadrangle map. There are 36 

sections in a given township and range numbered from 1 to 36 (U.S. sites 

only) .

Quarter-Quarter-Quarter 

section

Quarter-Quarter-Quarter section should be provided to locate the BMP test 

site on a U.S. Geological Survey quadrangle map. U.S. sites only.

Latitude Latitude is the North-South coordinate that locates the project to the nearest 

second on the globe relative to the equator. The degree, minute and second 

measures of the latitude can be obtained from a U.S. Geological Survey 

Quadrangle Map.

Longitude The East-West coordinate that locates the project to the nearest second on 

the globe relative to the selected principal meridian. The degree, minute and 

second measures of the latitude can be obtained from a U.S. Geological 

Survey (USGS) Quadrangle.

Altitude1Elevation above mean sea level provided to the nearest 100 feet from a U.S. 

Geological Survey quadrangle map or to the nearest 30 meters for studies 

outside of the United States.

Sponsoring and Monitoring Agency Information

Agency Type1Agency type, such as city, county, state, industry, federal, special district, 

council of governments, authority, consultant, or other.

Address1Address information including agency name, department (if any), street or 

post office address, city, state, zip code, country, phone, fax and e-mail. 

1

– National Stormwater BMP Database requirement for all BMPs
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Form A
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 159 April 25, 2002

Watershed Information

The watershed form contains important information about the physical and relational

characteristics of the watershed where the BMP was monitored. Watershed characteristics play a 

significant role in the quantity and type of pollutants in stormwater runoff. The form includes

information on the physical characteristics of the watershed, parking lots and roads, streams and

land uses. This information plays a significant role in comparing BMP performance under

various watershed conditions. If multiple watersheds were examined at a single test site then

additional watershed information forms can be completed for each watershed. Table 3.12

provides descriptions of the watershed form data elements, and the watershed form is presented

as Form B.

Table 3.12: Watershed form data elements description

Data Elements Description

Subject Watershed Name1 Name by which the watershed is referred to locally. 

Hydrologic Unit Code The U.S. Geological Survey (USGS) 8-digit hydrologic unit code (HUC) which 

represents a geographic area containing part or all of a surface drainage basin 

or distinct hydrologic feature. 

EPA Reach Code EPA-designated RF1 or RF3 river reach with which the station is associated. 

Sites will either have an RF1 code or an RF3 code, but not both. 

Unit System (S.I. or U.S. 

Standard)

The unit system used for measurement for the study. The unit system should 

be consistent for all reported data.

Physical Characteristics

Total Watershed Area1Topographically defined area drained by an urban system, channel, gulch, 

stream, etc., such that all outflow is directed to a single point. 

Total Length of Watershed Length of the watershed along the main drainage path to the furthest point on 

the watershed divide. 

Total Length of GrassLined Channel 5Total length of grass-lined and natural channels in the watershed. This is the 

portion of the storm drainage network in the watershed that is not conveyed in 

concrete channels, storm sewers or pipes. 

Total Watershed Area 

Disturbed 5

Total watershed area that is actively disturbed or under construction. This 

parameter may be useful in indicating the types and levels of pollutant loads in 

stormwater. 

Percent (%) Irrigated Lawn 

and/or Agriculture in 

Watershed 5

Percent of watershed area that is irrigated.

Percent (%) Total 

Impervious Area in 

Watershed1

The percent of the total watershed that is impervious can be determined as 

the total impervious area divided by the total area of the watershed. Common 

impervious surfaces include, but are not limited to, rooftops, walkways, patios, 

driveways, parking lots, storage areas, concrete or asphalt paving, gravel 

roads, packed earthen materials, and macadam or other surfaces that 

similarly impede the natural infiltration of urban runoff. Rainfall on impervious 

areas can cause rapid overland flow to drainage inlets. 

Percent (%) of Total 

Impervious Area (above) 

that is Hydraulically 

Connected

Parameter calculated by dividing the hydraulically connected impervious area 

by the total impervious area. An example of hydraulically connected 

impervious area includes building rooftops that drain onto paved areas. 

Percent (%) of Watershed 

Served by Storm Sewers5

The percentage of watershed area served by storm sewers (typically higher in 

urbanized areas than in rural areas). 

(Table continued on the following page)
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Data Elements Description

Storm Sewer Design 

Return Period (yrs)6

Most common design storm return period for the storm sewers in the 

watershed provided in years. For example, most storm sewers in the 

watershed may be designed to handle flows generated by the 25-year storm. 

Average Watershed 

Slope6

Average unitless slope of the watershed (i.e., ft fall/ft run or m fall/m run--

unitless). Slope for each linear reach can be determined as the elevation 

difference for the reach divided by the length of the reach, and the average 

slope for the watershed can be calculated as a weighted sum of the slopes of 

individual reaches.

Average Runoff Coefficient 

5

Rational Method runoff coefficient. If data permits, calculate the average of 

individual storm runoff coefficients using each storm’s runoff volume divided 

by its rainfall volume. Otherwise determine as area-weighted average for 

watershed land uses. 

NRCS Hydrologic Soil 

Group6

Dominant Natural Resource Conservation Service (NRCS--formerly Soil 

Conservation Service) hydrologic soil group--A, B, C, or D.

Soil Type5 NRCS soil type--(c)lay (s)ilt, s(a)nd. Clay particles are smaller than 0.002 

millimeters (mm) in diameter. Silt particles are between 0.002 and 0.05 mm in 

diameter. Sand particles range from 0.05 mm to 2.0 mm.

Type of Vegetation5Type of vegetation predominant in pervious areas (i.e. grass turf, dry land 

grasses, etc.).

Roads

Total Paved Roadway 

Area5

Total area of paved roads, streets and alleys in the watershed. Associated 

paved shoulders should be included in this area. 

Total Length Curb/Gutter 

on Paved Roads5

Total length of curb & gutter along paved roads, streets, and alleys.

Total Unpaved Roadway 

Area5

Total area of unpaved roads, streets, and alleys in the watershed. Unpaved 

shoulders should be included in this area. 

Total Length Curb/Gutter 

on Unpaved Roads5

Total length of curb & gutter along unpaved roads, streets, and alleys. 

% Paved Roads Draining 

to Grass Swales/Ditches5

Parameter calculated by dividing the length of paved roads, etc., draining to 

grass swales and ditches by the total length of paved roads, streets and 

alleyways in the watershed.

% Unpaved Roads 

Draining to Grass 

Swales/Ditches5

Percentage of unpaved roads, street and alley areas draining to grass 

swales/ditches that can be calculated by dividing the length of unpaved roads, 

etc., draining to grass swales and ditches by the length of unpaved roads, 

streets and alleyways in the watershed.

Type of Pavement on 

Roads, Streets and Alleys5

Pavement Type. Can be (C)oncrete,(A)sphalt, or a Mix of (B)oth.

Parking Lots

Total Paved Parking Lot5

Area

Total area of all paved parking lots within the watershed.

Total Length Curb/Gutter 

on Paved Lots5

Total length of curb & gutter along paved parking lots.

Total Unpaved Parking Lot 

Area5

Total area of all unpaved parking lots within the watershed. 

Total Length Curb/Gutter 

on Unpaved Lots5

Total length of curb & gutter along unpaved parking lots. 

% Paved Lot Area 

Draining to Grass Swales5

Percentage of parking lot areas draining to grass swales or ditches. This can 

be calculated by dividing the total parking lot area draining to swales by the 

total parking lot area.

(Table continued on the following page)
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Data Elements Description

% Unpaved Lot Area 

Draining to Grass Swales5

Percentage of unpaved parking lot areas draining to grass swales or ditches. 

This can be calculated by dividing the total unpaved parking lot area draining 

to swales by the total unpaved parking lot area.

Type of Pavement in 

Parking Lots

Can be (C)oncrete,(A)sphalt, or a Mix of (B)oth. Additionally, provide the 

percentages of porous concrete, porous asphalt and porous modular 

pavement present relative to the total paved parking lot area.

Land Uses

Land Use Information3Should be provided for each land use present in the watershed. The percent 

of each land use in the watershed, categorized according to % Light Industrial, 

% Heavy Industrial, % Multi-family Residential, % Office Commercial, % 

Retail, % Restaurants, % Automotive Services, % Rangeland, % Orchard, % 

Vegetable Farming, etc.

1

– National Stormwater BMP Database requirement for all BMPs

3

– National Stormwater BMP Database requirement for all Non-Structural BMPs

5

– National Stormwater BMP Database requirement for Non-Structural and Structural BMPs that are based on minimizing 

directly connected impervious areas

6

– National Stormwater BMP Database requirement for Structural BMPs that are based on minimizing directly connected 

impervious areas 
Urban Stormwater BMP Performance Monitoring

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Form B

Sheet 1 of 2
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A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 163 April 25, 2002

Sheet 2 of 2
Urban Stormwater BMP Performance Monitoring

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 164 April 25, 2002

Structural BMP Information

The purpose of the structural BMP form is to provide general BMP information inherent to all

structural BMP types. Structural BMPs include constructed facilities or measures to help protect 

receiving water quality and control stormwater quantity. Representative practices include

structures for storage, infiltration and filtration. Structural BMP information requested includes 

items such as date of installation, various design parameters, design drawings, and rehabilitation

and maintenance frequencies. Structural BMP form data elements and the form are presented in 

Table

 3.13: and Form C, respectively.

Table 3.13: Structural BMP form data elements description

Data Element Description

BMP Name2The name by which the BMP is referred to locally.

Type of BMP Being 

Tested2

The type of structural BMP being tested at the site. Major categories of 

structural BMPs include detention basins, retention ponds, wetland channels 

and swales, wetland basins, hydrodynamic devices, percolation trenchs and 

dry wells, media filters, grass filter strips, porous pavement and infiltration 

basins.

What date was the BMP 

facility put into service?2 

Month, day and 4-digit year (e.g., 04/05/1998) when BMP became 

operational. If the exact day is unknown, use the first day of the month.

How many separate inflow 

points does the facility 

have? 2

Number of separate inflow points. For example, a wet pond may receive flow 

from two (2) storm sewers and one (1) natural drainage, for a total of three (3) 

separate inflow points.

Is the BMP designed to 

bypass or overflow when 

full?2

 Identifies ‘Bypass” or “Overflow” when full..

Describe the type and 

frequency of maintenance, 

if any 

Type of frequency and maintenance. Practices include: Tree/Shrub/Invasive 

Vegetation Control, Mowing, Algae Reduction, Sediment Removal/Dredging, 

Litter/Debris Control, Erosion Control/Bank Stability, Inlet Cleaning, Outlet 

Cleaning, Media Replacement/Regeneration, Pump Cleaning/Repair, Valve 

Cleaning/Repair, Pipe Cleaning/Repair, General Maintenance, Odor Control, 

Mosquito Control, Vector Control.

What was the last date 

that the facility was 

rehabilitated, if any?

Month, day and 4-digit year (e.g., 04/05/1998) of most recent rehabilitation. If 

the exact day is unknown, use the first day of the month. 

Describe the type of 

rehabilitation, if any 

Description of rehabilitation activities such as structural modification or major 

repair. 

Describe the type and 

design of each BMP 

outlet2

Outlet configuration and design information.

BMP Drawing 2 Drawings of the BMP in plan, profile and layout view.

2

– National Stormwater BMP Database requirement for all Structural BMPs
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 165 April 25, 2002

Form C
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 166 April 25, 2002

Non-Structural BMP Information

The purpose of the non-structural BMP form is to provide general BMP information inherent to

all non-structural BMP types. A non-structural BMP can generally be described as a

preventative action to protect receiving water quality that does not require construction. 

Nonstructural BMPs rely predominantly on behavioral changes in order to be effective. Major

categories of non-structural BMPs include education, recycling, maintenance practices and

source controls, as described below.

• Educational BMPs: Include efforts to inform city employees, the public, and businesses

about the importance of using practices that protect stormwater from improper use, storage,

and disposal of pollutants, toxics, household products, etc. The ultimate goal of educational

BMPs is to cause behavioral changes. 

• Recycling BMPs: Include measures such as collecting and recycling automotive products,

household toxics, leaves, landscaping wastes, etc.

• Maintenance practices: Include measures such as catch basin cleaning, parking lot sweeping, 

road and street pavement repair, road salting and sanding, roadside ditch cleaning and

restoration, street sweeping, etc.

• Source controls: Include preventing rainfall from contacting pollutant-laden surfaces and

preventing pollutant-laden runoff from leaving locations such as automobile maintenance,

salvage and service stations; commercial, restaurant and retail sites; construction sites;

farming and agricultural sites; industrial sites, etc. 

The Non-structural BMP form data reports narrative/descriptive information on the type and

extent of the BMP being practiced, as well as cost data. The non-structural BMP form and the

form fields are described in Table 3.14: and Form D, respectively.

Table 3.14: Non-structural BMP form data elements description

Data Element Description

Non-structural BMP Type3 Categories of non-structural BMPs, such as education, recycling, maintenance 

practices and source controls.

BMP Name for the subject 

non-structural BMP3

BMP Name for the subject non-structural BMP (e.g., Erosion and Sediment 

Control Pamphlets).

Date Test Began3 Date (month, day and 4-digit year) that the BMP test was begun (e.g., 

01/01/1998).

Educational BMP3

“measurements” 

Measure of eductational BMP effectiveness/progress. Examples include: the 

number of brochures distributed per resident and employee in watershed per 

year, number of radio ads, percent of stormwater inlets in watershed stenciled, 

etc. 

(Table continued on the following page)
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Data Element Description

Recycling BMP 

“measurements” 3

Measure of recycling BMP effectiveness/progress. Could include gallons of 

used oil collected per resident in the watershed; pounds of household toxics 

collected per resident in the watershed; tons of landscaping waste per 

resident collected, etc.

Maintenance BMP 

“measurements” 3

Measure of maintenance BMP effectiveness/progress. Could include percent 

of stormwater catch basins cleaned once each year, twice each year, etc.; 

tons of materials removed per average inlet each year; lane miles of street 

swept each year and tons of material removed per lane mile each year; etc.

Source Control 

“measurements” 3

Measure of source control BMP effectiveness/progress. Could include 

percent of industrial storage area in watershed that is covered; etc. 

Cost Information

Initial Costs Initial costs, including the time and measures necessary to design and 

implement a program. 

Annual Costs Year-to-year costs once the initial program has been developed.

3

– National Stormwater BMP Database requirement for all Non-Structural BMPs
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 168 April 25, 2002

Form D
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 169 April 25, 2002

Detention Basin Design Data

The primary purpose of the detention basin design data form is to provide structural BMP

information specific to detention basins. Detention basins are designed to collect stormwater

runoff and completely empty sometime after the end of the runoff event. Detention basins used

for water quality purposes differ from flood control basins only by their outlet structures. 

Detention basin design characteristics are extremely important for comparing their performance

under various hydrological and environmental conditions. The detention basin form and the

form data elements are presented respectively in Form E and Table 3.15.

Table 3.15: Detention basin design form data elements list

Data Element Description

Water Quality Detention 

Volume4

The volume of storm runoff that is captured and slowly drained over a period 

of time (e.g., 12 to 48 hours). 

Water Quality Detention 

Surface Area When Full4

The area of the water surface in the detention basin at full water quality 

detention volume. 

Water Quality Detention 

Basin Length4

Length of the water quality detention basin, measured as the distance 

between inflow and outflow. If there is more that one inflow point, use the 

average distance between the inflow points and the outflow weighted by the 

tributary impervious area.

Detention Basin Bottom 

Area4

Area of the bottom of the entire detention basin, not including the side slopes 

but including the bottom stage area. 

Brim-full Volume Emptying 

Time4

Emptying time (in hours) of the water quality detention volume. 

Half Brim-full Volume 

Emptying Time4

Emptying time (in hours) of the lower half of the water quality detention 

volume. 

Bottom Stage Volume, If 

Any4

The volume of the lower “bottom stage” portion (if applicable) of the detention 

basin. 

Bottom Stage Surface 

Area, If Any4

The surface area of the lower “bottom stage” portion (if applicable) of the 

detention basin. 

Is There a Micro Pool?4“Yes” or “No” indication of micropool.

Forebay Volume4Volume of the forebay portion of the detention basin when filled to the point of 

overflow into the rest of the basin.

Forebay Surface Area4Surface area of water in the forebay at the level of overflow to the bottom 

stage.

Describe Vegetation Cover 

Within Basin4

Describe the types of vegetation on the basin sides and floor. 

Flood Control Volume, If 

Any4

The flood control detention volume in excess of the water quality detention 

basin volume (if any).

List Design Flood Return

Periods4

List the flood return period (in years) for which the flood control volume is 

designed (e.g., 25-year). 

Depth to Seasonal High 

Water Table, If Known

The minimum depth from the basin bottom to the water table during the 

monitoring season.

Detention Basin Construction Cost Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which cost estimates were made.

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring.

(Table continued on the following page)
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 170 April 25, 2002

Data Element Description

Structural Control Devices The estimated cost of establishing all structural control devices, such as inlet 

and outlet structures, trash racks and energy dissipaters, including cost of 

materials and construction.

Vegetation and 

Landscaping Costs

The estimated cost of establishing vegetation for the BMP, including acquiring 

landscape materials, establishing vegetation, and establishing the irrigation 

infrastructure, if any.

Engineering and Overhead 

Costs

The estimated engineering and associated overhead costs, including site, 

structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land or the cost of acquiring the land.

Rehabilitative Costs:

Average Annual Sediment 

Removal Costs

Estimated average annual cost to remove sediment accumulated in the 

detention basin.

Average Annual

Revegetation Costs 

Estimated average annual cost to revegetate the sides and floor of the 

detention basin.

4

– National Stormwater BMP Database requirement for all Non-Structural BMPs
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 171 April 25, 2002

Form E
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 172 April 25, 2002

Retention Pond Design Data

The retention pond design data form reports BMP specific information for retention ponds. 

Retention ponds are also commonly known as “wet ponds” because they have a permanent pool

of water, unlike detention basins, which dry out between storms. The permanent pool of water is 

replaced in part, or in total, by stormwater during a storm event. The design is such that any

available surcharge capture volume is released over time. Retention of stormwater in the

permanent pool over time can provide biochemical treatment. A dry weather base flow, pond

liner and/or high groundwater table are required to maintain the permanent pool. The retention

pond form and the form data elements descriptions are shown in Form F and Table 3.16:

Table 3.16: Retention pond design form data elements list

Data Element Description

Volume of permanent 

pool4

Volume of the permanent pool of water. 

Permanent Pool Surface 

Area4

Area of the water surface in the permanent pool. 

Permanent Pool Length4Length of the permanent pool of water, measured along the axis of the inflow 

and outflow. If more that one inflow point, use the average distance between 

the inflow points and the outflow weighted by the tributary impervious area.

Littoral Zone Surface 

Area4

Surface area of the littoral zone. The littoral zone refers to the area above the 

level of the permanent pool that is periodically and temporarily covered by 

captured storm runoff. 

Littoral Zone Plant Species 

List 

List plant species (by Latin name, if known), percent of cover and densities in 

the littoral zone. 

Water Quality Surcharge 

Detention Volume When 

Full4

Water quality detention volume above permanent pool, when full.

Water Quality Surcharge 

Surface Area When Full4

The surface area of water quality detention volume above the permanent pool, 

if applicable. 

Water Quality Surcharge 

Basin Length4

Length of the water quality detention volume, measured along the axis 

between the inflow and outflow. If more that one inflow point, use the average 

distance between the inflow points and the outflow weighted by the tributary 

impervious area. 

Brim-full Emptying Time 

For Surcharge4

Time (in hours) required for the retention pond water quality surcharge 

detention volume to be released to the permanent pool level. 

Half Brim-full Emptying 

Time For Surcharge4

Time (in hours) required for the lower half of the retention pond water quality 

surcharge detention volume to be released to the permanent pool. 

Forebay Volume4Volume of the forebay portion of the retention basin when it is filled to the 

point of overflow into the lower part of the basin.

Forebay Surface Area

4

Surface area of water in the forebay when it is filled to the point of overflow 

into the lower part of the basin. 

Describe Vegetation Cover 

Within Basin4

Describe the types of vegetation (provide Latin names, if known) on the basin 

sides and floor.

Flood Control Volume, If 

Any4

The flood control detention volume in excess of the retention basin volume (if 

any).

List Design Flood Return 

Periods (in years)4

List the flood return period (in years) for which the flood control volume is 

designed (e.g., 25-year). 

(Table continued on the following page)
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 173 April 25, 2002

Data Element Description

Retention Pond Construction Cost Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which cost estimates were made.

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring.

Structural Materials Costs The estimated cost of materials used in constructing the retention pond, 

excluding vegetation costs.

Basin Construction Costs The estimated cost for construction of the retention pond, including site survey 

and construction activities.

Structural Control Devices 

Costs 

The estimated cost of establishing all retention pond control devices, such as 

inlet and outlet structures, spillways, and culverts. Includes the cost of 

materials and construction.

Vegetation and 

Landscaping Costs

The estimated cost of establishing vegetation for the BMP, including acquiring 

landscape materials, etc.

Engineering and Overhead 

Costs

The estimated engineering and associated overhead costs, including site, 

structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land dedicated to this BMP or the cost of acquiring 

this land.

Rehabilitative Costs:

Average Annual Sediment 

Removal Costs

Estimated average annual cost to remove sediment accumulated in the 

retention pond.

Average Annual 

Revegetation Costs 

Estimated average annual cost to revegetate and/or reseed the retention 

pond.

4

– National Stormwater BMP Database requirement for all Retention Ponds
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 174 April 25, 2002

Form F
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 175 April 25, 2002

Percolation Trench and Dry Well Design Data

The percolation trench and dry well form contains essential design information for percolation

trenches and dry wells. Percolation or infiltration trenches can be generally described as

trenches or excavations filled with porous media designed to encourage rapid percolation of

runoff to the groundwater. A dry well is a drilled well, often drilled through impervious layers to 

reach lower pervious layers. The percolation trench and dry well form and data elements are

presented in Table 3.17: and Form G.

Table 3.17: Percolation trench and dry well design form data elements list

Data Element Description

Percolation Trench/Well Surface 

Area4

The top surface area of the percolation trench or well.

Percolation Trench/Well Length4The length of the percolation trench, or the diameter of the well. 

Percolation Trench/Well Depth4The depth of the trench or the well that is exposed to permeable soils. 

Depth to Seasonal High 

Groundwater Below Bottom of 

Trench/Well4

The minimum depth to the seasonal high groundwater table below the 

trench or well. 

Depth to Impermeable Layer 

Below Bottom of Trench/Well4

The depth to the first impermeable layer below the trench or well. 

Depth and Type of Each Soil 

Layer Adjacent To and Below 

Trench/Well4

The order of stratification (from the surface downward) and the depth of 

each layer of soils at the BMP site. 

Type and Gradation of Granular 

Materials Used in Trench/Well4

Describe the type and depth of granular material used in the trench or 

well. 

Was Geotextile Used Above 

Granular Trench Fill? 4

“Yes” or “no” indication of geotextile use above granular fill.

Was Geotextile Used On the 

Sides of Granular Fill? 4

“Yes” or “no” indication of geotextile use on sides of granular fill.

Was Geotextile Used On the 

Bottom of Granular Fill? 4

“Yes” or “no” indication of geotextile use below granular fill.

Give porosity (in percent) of the 

granular fill material4

The volumetric portion of the granular material that is not occupied by 

solid matter (expressed as a percent).

Total Storage Pore Volume in 

Trench4

The volume of the available pore space in the granular materials. 

Describe Type of Geotextile 

Used4

Describe the types and locations of the geotextile fabrics used in the 

trench or well, if any. Include the effective pore opening of the fabrics. 

Hydraulic Conductivity of 

Adjacent Soils4

The hydraulic conductivity of the soils adjacent to the trench or well 

infiltration surfaces.

Groundwater Flow Gradient4The flow gradient of groundwater below the infiltration basin (expressed 

as unit length per unit length, e.g., feet/feet).

Purpose of Trench or Well Describe the purpose of the percolation trench or well (e.g., water quality 

treatment, reduction of surface runoff, groundwater recharge, etc.).

Percolation Trench and Dry Well Construction Costs Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which cost estimates were made.

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring.

Well Drilling The estimated cost of establishing the well, if this is a dry well.

(Table continued on the following page)
Urban Stormwater BMP Performance Monitoring

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 176 April 25, 2002

Data Element Description

Trench Construction Costs The estimated cost of establishing the trenches, if this is a percolation 

trench.

Structural Control Devices Costs The estimated cost of establishing all percolation trench or dry well 

control devices, such as inlet and outlet structures and culverts. Include 

the cost of materials and construction.

Structural Materials Costs The estimated cost of materials used in the percolation trench, such as 

granular fill and geotextiles.

Engineering and Overhead 

Costs 

The estimated engineering and associated overhead costs, including 

site, structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land dedicated to this BMP or the cost of 

acquiring this land.

Rehabilitative Costs:

Average Annual Sediment 

Removal Costs 

Estimated average annual cost to remove sediment accumulated in the 

retention pond.

4

– National Stormwater BMP Database requirement for all Percolation Trenches and Dry Wells
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 177 April 25, 2002

Form G
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 178 April 25, 2002

Media Filter Design Data

The media filter design data form contains design information related to the performance of

media filters. A Media Filter is a facility that uses some form of granular or membrane filter,

with or without a pre-settling basin, to remove a fraction of the constituents found in stormwater. 

The most typical filter is sand, but other materials, including peat mixed with sand, compost with 

sand, geotextiles, and absorption pads and beds are commonly used. The media filter form and

data elements are presented in Table 3.18 and Form H.

Table 3.18: Media filter design form data elements list

Data Element Description

Permanent Pool Volume 

Upstream of Filter Media, If 

Any4

Volume of the permanent pool (if any) if the pool is part of the filter basin 

installation and not a separate pretreatment retention pond or a detention 

basin. 

Permanent Pool Surface 

Area of Sedimentation 

Basin Preceding Filter, If 

Any4

Area of the water surface in the permanent pool (if any). 

Permanent Pool Length of 

Sedimentation Basin 

Preceding Filter, If Any4

Length of the permanent pool (if any) measured as the distance from pool 

inflow to outflow. If more than one inflow point, use the average length. 

Surcharge Detention 

Volume, Including Volume 

Above Filter Bed4

The design water quality capture volume, including the volume above the 

filter. 

Surcharge Detention 

Volume Surface Area4

The surface area of the design water quality captured runoff including the area 

above the filter. 

Surcharge Detention 

Volume Length

The length of the design captured runoff volume, including the portion above 

the filter, measured as the distance along the flow path. If more than one 

inflow point, use the average length.

Surcharge Detention 

Volume's Design Drain 

Time, If Controlled and 

Known 4

The design time for complete drawdown (in hours) of the water quality capture 

volume if the drain time is controlled by a flow regulating device such as an 

orifice. Leave blank if the drain rate is only a fraction of the filter’s flowthrough rate. 

Surcharge Detention 

Volume Design Depth4

The design depth of water quality capture volume that can be stored above 

the filter before overflow or runoff bypass occurs. 

Media Filter Surface Area4Surface area of the media filter (e.g., the sand bed or geotextile filter) as a 

whole orthogonal to the flow. 

Angle of Sloping or Vertical 

Filter4

Inclination of filter in degrees above the horizontal plane.

Number of Media Layers in 

Filter4

The number of layers of different filter materials in this BMP. 

Describe Depth and Type 

of Each Filter Media Layer4

Describe the type of media used in the filter (Example: ASTM C-33 Sand with 

d50=0.7 mm, 50% ASTM C-33 Sand with d50=0.6 mm and 50% Peat).

Media Filter Construction Cost Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which the above estimates were made.

(Table continued on the following page)
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 179 April 25, 2002

Data Element Description

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring.

Basin Construction Costs The estimated cost for construction of the media filter, including site survey 

and construction activities.

Filter Construction Costs The estimated cost of establishing the filter system itself, including filter 

material and the underdrain system. Include costs of materials and 

construction.

Structural Control Devices 

Costs 

The estimated cost of establishing all BMP control devices, such as inlet 

devices, trash racks, energy dissipaters, and outlet structures. Include costs 

of materials and construction.

Engineering and Overhead 

Costs 

The estimated engineering and associated overhead costs, including site, 

structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land dedicated to this BMP or the cost of acquiring 

this land.

Rehabilitative/ 

Maintenance Costs:

Average Annual Sediment 

Removal and Media 

Replacement Costs 

Estimated average annual cost to remove sediment accumulated in the media 

filter and replace the filter material.

4

– National Stormwater BMP Database requirement for all Media Filters
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 180 April 25, 2002

Form H
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 181 April 25, 2002

Grass Filter Strip Design Data

The grass filter strip form provides design information specific to grass filter strips. Grass filter

strips, sometimes called buffer strips, are vegetated areas designed to accept sheet flow provided 

by flow spreaders which accept flow from an upstream drainage area. Vegetation may take the

form of grasses, meadows, forests, etc. The primary mechanisms for pollutant removal are

filtration, infiltration, and settling. The grass filter strip form and data elements are shown in

Table 3.19 and Form I.

Table 3.19: Grass filter strip form data elements list

Data Element Description

Grass Strip Length4Length of the grass strip in the direction of the flow path. 

Grass Strip Slope4The slope of the strip along the flow path expressed as unit length per unit 

length (e.g., feet/feet). 

Flow Depth during 2-Year 

Storm4

The design depth of flow over the strip during the 2-year storm peak flow. 

2-Year Peak Flow 

Velocity4

The design flow velocity over the strip during the 2-year peak flow. 

Describe Grass Species 

and Densities4

List of grass species and their densities.

Is Strip Irrigated?4“Yes” or “no” indication of irrigation.

Estimated Manning's n 

During 2-Year Flow 

The estimated Manning’s roughness factor, n, during the 2-year flow event. 

Depth to Groundwater or 

Impermeable Layer 

Depth to the seasonal high groundwater table and/or the impermeable layer, 

whichever is shallower.

Measured Saturated 

Infiltration Rate, if Known 

Rate of infiltration into the filter strip under saturated soil conditions.

NRCS Hydrologic Soil 

Group 

The Natural Resource Conservation Service Hydrologic Soil Group (e.g., A, B, 

C, or D) comprising the infiltrating surface.

Grass Filter Strip Construction Cost Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which the above estimates were made.

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring.

Structural Control Devices 

Costs 

The estimated cost of establishing all BMP control devices, such as slotted 

curbing or other flow spreading devices, and outflow collection and 

conveyance systems. Include costs of materials and construction.

Vegetation and 

Landscaping Costs 

The estimated cost of establishing vegetation for the BMP, including acquiring 

landscape materials, establishing vegetation, and establishing the irrigation 

infrastructure, if any.

Engineering and Overhead 

Costs 

The estimated engineering and associated overhead costs, including site, 

structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land dedicated to this BMP or the cost of acquiring 

this land.

Rehabilitative Costs:

Average Annual Sediment 

Removal Costs 

Estimated average annual cost to remove sediment accumulated on the grass 

filter strip.

Average Annual 

Revegetation Costs 

Estimated average annual cost to revegetate and/or reseed the grass filter 

strip.

4

– National Stormwater BMP Database requirement for all Grass Filter Strips
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 182 April 25, 2002

Form I

 
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 183 April 25, 2002

Wetland Channel and Swale Design Data

The purpose of the wetland channel and swale design form is to consistently collect and report

wetland channel and swale information. A wetland channel is a channel designed to flow very

slowly, probably less than two feet per second at the two-year flood peak flow rate. It has, or is

designed to develop, dense wetland vegetation on its bottom. A swale is a shallow grass-lined 

channel designed for shallow flow near the source of storm runoff. The wetland channel and

swale form and data elements are provided in Table 3.20 and Form J. 

Table 3.20: Wetland channel and swale form data elements list

Data Element Description

Average Longitudinal 

Inflow Spacing

The average longitudinal spacing between all separate stormwater inflow 

points. 

Length of Channel/Swale4The length of the wetland channel or swale, from the stormwater inflow to 

outflow point. 

Longitudinal Slope of 

Channel/Swale4

The average longitudinal slope (in unit length per unit drop, e.g., feet per feet 

or meter per meter) of the wetland channel or swale, as measured between 

grade control structures. 

Bottom Width of 

Channel/Swale4

The average width of the nearly flat bottom of the channel or swale between 

its side slopes. 

Side Slope of 

Channel/Swale4

The average (in vertical unit length per horizontal unit length) of the channel or 

swale’s side slopes. 

2-Yr Flow Design Depth in 

Channel/Swale4

The average depth of water in the channel or swale during the two-year flood 

peak flow. 

2-Yr Peak Design Flow 

Velocity4

The flow velocity in the channel or swale during the two-year flood peak flow. 

2-Yr Manning's n The Manning’s roughness factor, n, for the 2-year peak flow.

Type of Plant Species in 

Wetland Zone or Swale4

List the plant species, percent of cover and densities. 

Maximum Design Flow 

Capacity Return Period of 

Swale 

The flood return period that the channel has been designed to convey within 

its banks in addition to the water quality design event. (Example: 2-year and 

10-year flood).

Depth to High 

Groundwater or 

Impermeable Layer

The minimum depth to the water table during the high water table season, or 

to the first impermeable layer.

Groundwater Hydraulic 

Conductivity

The hydraulic conductivity of the groundwater below the channel or swale.

Wetland Channel and Swale Construction Cost Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which cost estimates were made.

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring.

Structural Control Devices 

Costs 

The estimated cost of establishing all wetland channel or swale control 

devices, such as inlet and outlet devices, trash racks, etc. Include the cost of 

materials and construction.

(Table continued on the following page)
Urban Stormwater BMP Performance Monitoring

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 184 April 25, 2002

Data Element Description

Vegetation and 

Landscaping Costs 

The estimated cost of establishing vegetation for the BMP, including acquiring 

landscape materials, establishing vegetation, and establishing the irrigation 

infrastructure, if any.

Engineering and Overhead 

Costs 

The estimated engineering and associated overhead costs, including site, 

structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land dedicated to this BMP or the cost of acquiring 

this land.

Rehabilitative Costs:

Average Annual Sediment 

Removal Costs 

Estimated average annual cost to remove sediment accumulated in the 

swale/wetland channel.

Average Annual 

Revegetation Costs 

Estimated average annual cost to revegetate the sides and floor of the 

swale/wetland channel.

4

– National Stormwater BMP Database requirement for all Wetland Channels/Swales
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 185 April 25, 2002

Form J

 
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 186 April 25, 2002

Porous Pavement Design Data

The porous pavement form provides design information particular to porous pavement BMPs. 

There are two forms of porous pavement: modular block, which is made porous through its

structure, and poured-in-place concrete or asphalt which is porous due to the mix of the

materials. Modular block porous pavement consists of perforated concrete slab units underlain

with gravel. The surface perforations are filled with coarse sand or sandy turf. It is used in low

traffic areas to accommodate vehicles while facilitating stormwater runoff at the source. It

should be placed in a concrete grid that restricts horizontal movement of infiltrated water through 

the underlying gravels. Poured-in-place porous concrete or asphalt is generally placed over a

substantial layer of granular base. The pavement is similar to conventional materials, except for 

the elimination of sand and fines from the mix. If infiltration to groundwater is not desired, a

liner may be used below the porous media along with a perforated pipe and a flow regulator to

slowly drain the water stored in the media over a 6 to 12 hour period. The porous pavement

design form and data elements are given in Table 3.21 and Form K.

Table 3.21: Porous pavement form data elements

Data Element Description

Porous Pavement Surface 

Area4

Surface area of the porous pavement. 

Depth to Seasonal High 

Groundwater4

The minimum depth to the seasonal water table below the porous pavement. 

Depth to Impermeable 

Layer4

The depth to the first impermeable layer below the BMP, if known. 

NRCS Hydrologic Soil 

Group

The Natural Resource Conservation Service Hydrologic Soil Group (e.g., A, B, 

C, or D) comprising the infiltrating surface.

Infiltration Rate4 Rate of infiltration for site soils under saturated conditions. 

Type of Granular or Other 

Materials Used in or Below 

Pavement4

Describe the type and depth of each granular material layer under the porous 

pavement, if any. Include each layer of geotextile fabric used as though it was 

a granular layer. 

Porosity of Granular 

Materials, as a Percent4

Porosity measures the volumetric portion of the filter material that is not 

occupied by solids. If the layer is geotextile fabric, give the effective pore size. 

Is Grass Growing in 

Modular Pores?

“Yes” or “No” indication of grass growing in modular pores.

If Yes, is Grass Healthy? “Yes” or “No” indication of grass health, if applicable.

Describe Depth of Each 

Soil Layer Below 

Pavement, If Known 

The order of stratification (from the surface downward) and the depth of each 

layer of soils below the porous pavement, to a depth of at least ten feet (3.05 

meters). 

Total Storage Volume 

Above Pavement, If Any4

The volume of water stored in depressions or as a result of attenuation (if any) 

above the porous pavement surface.

Estimated Drain Time (hrs) 

of Storage Volume Above 

Pavement, If Any4

The emptying time of the storage volume above the pavement.

Total Storage Volume 

Under Pavement, If Any4

The net available volume of the pore spaces in the granular materials under 

the porous pavement, if any.

Estimated Drain Time of 

Storage Volume Under 

Pavement, If Any4

The total emptying time (in hours) for the storage detention volume under the 

pavement.

(Table continued on the following page)
Urban Stormwater BMP Performance Monitoring

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 187 April 25, 2002

Data Element Description

Groundwater Hydraulic 

Conductivity 

The hydraulic conductivity of the groundwater underlying the BMP.

Groundwater Flow 

Gradient 

The flow gradient (in unit length per unit length, e.g. feet/feet) of groundwater 

below the infiltration basin.

Does Porous Pavement

Have Underdrains?4

“Yes” or “No” indication of underdrains for the porous pavement. 

Describe Purpose of 

Porous Pavement

Describe the purpose(s) of the porous pavement (examples: water quality 

treatment, reduction in peak surface runoff rate and volume, groundwater 

recharge, etc.)

Porous Pavement Construction Cost Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which cost estimates were made.

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring.

Structural and Piping 

Costs 

The estimated cost of establishing the structural and piping features of the 

BMP, including modular blocks, retaining concrete, sub-base material, and 

inlay material. Include costs of materials and construction.

Granular Fill Costs The estimated cost of establishing the granular fill for the BMP, including sand 

or gravel inlay materials, filter fabric, and perforated underdrain (if any). 

Include costs of materials and construction.

Paving Costs If poured-in-place porous concrete or asphalt paving was used, this is the 

estimated cost of establishing the paving. Include costs of materials and 

construction.

Curb and Gutter Costs The estimated cost of establishing curbs and gutters for the BMP. Include 

costs of materials and construction.

Engineering and Overhead 

Costs

The estimated engineering and associated overhead costs, including site, 

structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land dedicated to this BMP or the cost of acquiring 

this land.

Rehabilitative/ 

Maintenance Costs:

Average Annual 

Vegetation Replacement 

and Granular Media 

Replacement and 

Maintenance Costs 

Estimated average annual cost to revegetate void spaces in modular block 

pavement. If poured-in-place porous pavement, report estimated average 

annual cost to wash, vacuum, pressure wash, patch, gutter clean, etc. at a 

frequency that ensures the continued function of the BMP.

4

– National Stormwater BMP Database requirement for all Porous Pavement
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 188 April 25, 2002

Form K
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 189 April 25, 2002

Infiltration Basin Design Data

The infiltration basin form reports important design information for infiltration basins. An

infiltration basin is a basin that can capture a given stormwater runoff volume and infiltrate it

into the ground, transferring this volume from surface flow to groundwater flow. The infiltration 

basin form and data elements are listed in Table 3.22 and Form L.

Table 3.22: Infiltration basin form data elements list

Data Element Description

Capture Volume of Basin4The design runoff capture volume of the basin. 

Surface Area of Capture 

Volume, When Full4

The area of the water surface in the infiltration basin, when full. 

Infiltrating Surface Area4The plan area of the surface used to infiltrate the water quality volume. 

Basin Length Length of the infiltration basin, measured as the distance between inflow and 

outflow.

Depth to Seasonal High 

Groundwater Below 

Infiltrating Surface4

Depth to the seasonal high groundwater table. 

Depth to Impermeable 

Layer Below Infiltrating 

Surface4

Depth to the impermeable layer, if any. 

NRCS Hydrologic Soil 

Group

The Natural Resource Conservation Service Hydrologic Soil Group (e.g., A, B, 

C, or D) comprising the infiltrating surface.

Depth and Type of Each 

Layer of Soil 

The order of stratification (from the surface downward) and the depth of each 

layer of soils at the infiltration basin site, to a depth of at least ten feet (3.05 

meters). 

Field Measured Infiltration 

Rate

The saturated soil infiltration rate, based on soil surveys, infiltrometer 

measurements or observed draw down of a new basin.

List Plant Species on 

Infiltrating Surface4

 List the plant species (by Latin names, if known) and densities of cover on the 

bottom of the infiltration basin. 

Describe Granular Material 

on Infiltrating Surface, If 

Any4

 Describe the granular material and its depth and porosity (if any). 

Hydraulic Conductivity of 

Underlying Soils 

The hydraulic conductivity of the soils underlying the infiltration surface. 

Groundwater Flow 

Gradient 

The flow gradient (in unit length per unit length, e.g. feet/feet) of groundwater 

below the infiltration basin.

Flood Control Volume 

Above Water Quality 

Detention Volume

The volume of the flood control detention volume above the infiltration basin 

volume.

List All Design Flood 

Control Return Periods 

List the flood return period (in years) for which the flood control volume is 

designed (e.g., 25-year). 

Describe Purpose of Basin Describe the purpose of the infiltration basin (e.g., surface water quality only, 

groundwater recharge, etc.).

Infiltration Basin Construction Cost Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which cost estimates were made.

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring.

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Data Element Description

Structural Materials Costs The estimated cost of materials used in constructing the infiltration basin, 

excluding vegetative cover.

Basin Construction Costs The estimated cost for construction of the infiltration basin, including site 

survey and construction activities.

Structural Control Devices 

Costs 

The estimated cost of establishing all BMP control devices, such as inlet 

devices, trash racks, energy dissipators, and outlet structures. Include costs 

of materials and construction.

Vegetation and 

Landscaping Costs 

The estimated cost of establishing vegetation for the infiltration basin, 

including acquiring landscape materials, establishing vegetation, and 

establishing the irrigation infrastructure, if any.

Engineering and Overhead 

Costs 

The estimated engineering and associated overhead costs, including site, 

structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land dedicated to this BMP or the cost of acquiring 

this land.

Rehabilitative/ 

Maintenance Costs:

Average Annual Sediment 

Removal Costs 

Estimated average annual cost to remove sediment accumulated in the 

infiltration basin.

Average Annual 

Revegetation Costs 

Estimated average annual cost to revegetate the infiltration basin.

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Hydrodynamic Device Design Data

The hydrodynamic device form provides important design criteria specific to hydrodynamic

devices. The hydrodynamic device BMP category includes BMPs such as oil-water separators,

sand interceptors, swirl-type concentrators, sedimentation vaults, and other prefabricated and

package-type treatment devices. The hydrodynamic device form and data elements are provided 

in Table 3.23 and Form M.

Table 3.23: Hydrodynamic device form data elements

Data Element Description

Volume of Permanent 

Pool4

Volume of the permanent pool (dead pool) of water. 

Permanent Pool Surface 

Area4

Area of the water surface in the permanent pool (dead pool). 

Permanent Pool Length4Length of the permanent pool of water, measured as the distance between 

inlet and outlet. If more than one inlet location, use the average distance 

between the inlet location and the outlet location. 

Water Quality Surcharge 

Detention Volume When 

Full4

The surcharge detention volume above the permanent pool volume (device 

active storage volume). 

Inlet Chamber Volume, If 

Any4

Volume of the inlet chamber portion of the hydrodynamic device when it is 

filled to the point of overflow into the lower (next) part of the device.

Brim-full Emptying Time 

For Surcharge4

Time (in hours) required for the hydrodynamic device water quality surcharge 

detention volume to be released from the outlet discharge. 

Half Brim-full Emptying 

Time For Surcharge4

Time (in hours) required for the lower half of the hydrodynamic device water 

quality surcharge detention volume to be discharged from the outlet. 

Comments. This field can be used for comments and other miscellaneous information 

such as model type and related manufacturer's specifications for design. 

Hydrodynamic Device Construction Cost Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which cost estimates were made.

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring, and backfilling. 

Structural Materials Costs The estimated cost of materials such as gravel, pavement and vegetation 

necessary for the installation of the hydrodynamic device. These costs should 

include installation costs but exclude the cost of the device itself. 

Device Construction Costs The estimated cost for supply, construction, and installation of the 

hydrodynamic device, including site survey and construction activities. 

Structural Control Devices 

Costs

The estimated cost of establishing all hydrodynamic device control devices, 

such as inlet and outlet structures (manholes), spillways, pipelines and 

culverts. Include the cost of materials and construction.

Engineering and Overhead 

Costs

The estimated engineering and associated overhead costs, including site, 

structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land dedicated to this BMP or the cost of acquiring 

this land.

Rehabilitative Costs:

Average Annual Sediment 

Removal Costs

Estimated average annual cost to remove oils, sediments, and trash 

accumulated in the hydrodynamic device.

4

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Wetland Basin Design Data

The wetlands basin form provides important design information specific to wetland basins. A

wetland basin is a BMP similar to a retention pond (with a permanent pool of water) with more 

than 50% of its surface covered by emergent wetland vegetation, or similar to a detention basin

(no significant permanent pool of water) with most of its bottom covered with wetland

vegetation. The wetland basin data form and data elements list are shown in Table 3.24 and

Form N.

Table 3.24: Wetland basin form data elements list

Data Element Description

Volume of permanent 

pool4

Volume of the permanent pool of water, if any. 

Permanent Pool Surface 

Area4

Area of the water surface in the permanent pool, if any.

Permanent Pool Length4Length of the permanent pool of water, measured at the water surface along 

the axis of the inflow and outflow. If more that one inflow point, use the 

average distance between the inflow points and the outflow weighted by the 

tributary impervious area.

Water Quality Surcharge 

Detention Volume When 

Full4

The water quality surcharge detention volume above the permanent volume 

(when full).

Water Quality Surcharge 

Surface Area When Full4

The surface area of any supplementary water quality detention volume above 

the permanent pool, if applicable. 

Water Quality Surcharge 

Basin Length 4

Length of the water quality detention volume, measured at the water surface 

along the axis of the inflow and outflow. If more that one inflow point, use the 

average distance between the inflow points and the outflow weighted by the 

tributary impervious area.

Brim-full Emptying Time 

For Surcharge 4

Time (in hours) required for the wetland basins water quality surcharge 

detention volume to be released to the permanent pool. 

Half Brim-full Emptying 

Time For Surcharge 4

Time (in hours) required for the lower half of the water quality surcharge 

detention volume to be released to the permanent pool. 

Forebay Volume 4Volume of the forebay portion of the wetland basin when it is filled to the point 

of overflow into the rest of the basin. 

Forebay Surface Area 4Surface area of water in the forebay when it is filled to the point of overflow 

into the rest of the basin. 

Describe Vegetation Cover 

Within Basin 4

Describe the types of vegetation on the basin sides and floor. 

Flood Control Volume, If 

Any 4

The volume of the flood control detention volume above the wetland basin 

volume.

Design Flood Return 

Periods 4

List the flood return period (in years) for which the flood control volume is 

designed (e.g., 25-year). 

Wetland Surface Area 4Surface area of the wetland basin, including all pond areas and meadow 

wetland areas. Use permanent pool surface area if no other wetland area 

exists adjacent to the pool. 

(Table continued on the following page)
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Data Element Description

Percent of Wetland Pond 

with 12 inches (0.3 m) 

Depth 4

Percent of the wetland basin’s surface area typically having 12 inches (0.3 m) 

or less water depth. 

Percent of Wetland Pond 

with 12 - 24” (0.3 – 0.6 m) 

Depth 4

Percent of the wetland basin’s surface area typically having 12 to 24 inches 

(0.3 - 0.6 m) water depth. 

Percent of Wetland Pond 

with 24 - 48” (0.6 – 1.3 m) 

Depth 4

Percent of the wetland basin’s surface area typically having 24 to 48 inches 

(0.6 - 1.3 m) water depth. 

Percent of Wetland Pond 

with > 48” (> 1.3 m) Depth

Percent of the wetland basin’s surface area typically having greater than 48 

inches (> 1.3 m) water depth. 

Percent of wetland basin's 

area that is meadow 

wetland 4

Percent of the wetland basin that is meadow area, that is, area without 

standing water. 

List All Known Plant 

Species in the Wetland 4

Type and percent cover of the wetland basin by each wetland species, and 

densities. 

Wetland Basin Construction Cost Estimates

Year of Cost Estimate Four-digit year (e.g., 1998) for which the above estimates were made.

Construction Costs:

Excavation Costs The estimated cost of all excavation-related activities, including stripping, 

drilling and blasting, trenching and shoring.

Structural Materials Costs The estimated cost of materials used in the wetland basin, such as imported 

topsoil or fill.

Basin Construction Costs The estimated cost of establishing the wetland basin itself, not including 

vegetation costs.

Structural Control Devices 

Costs 

The estimated cost of establishing all wetland basin control devices, such as 

inlet and outlet devices, trash racks, etc. Include the cost of materials and 

construction.

Vegetation and 

Landscaping Costs 

The estimated cost of establishing vegetation for the BMP, including acquiring 

landscape materials, establishing vegetation, and establishing the irrigation 

infrastructure, if any.

Engineering and Overhead 

Costs 

The estimated engineering and associated overhead costs, including site, 

structural, and landscape design and engineering expenses.

Land Costs or Values The estimated value of the land dedicated to this BMP or the cost of acquiring 

this land.

Rehabilitative Costs:

Average Annual Sediment 

Removal Costs 

Estimated average annual cost to remove sediment accumulated in the 

wetland basin.

Average Annual 

Revegetation Costs 

Estimated average annual cost to revegetate the sides and floor of the 

wetland basin.

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Monitoring Station Information

Monitoring station information is requested for both structural and non-structural BMPs in a test 

site. The monitoring station information form contains information on monitoring station 

locations, instrumentation, and monitoring costs. More than one instrument may be present in a 

monitoring station. For example, a monitoring station may contain a flow gauge and a water

quality sampler. A single form should be filled out for each individual monitoring station at the 

site. The monitoring station form and data elements list are provided in Table 3.25 and Form O.

Table 3.25: Monitoring station form data elements

Data Element Description

Monitoring Station Information

Monitoring Station Name1 User-defined name for subject monitoring station.

Identify Upstream BMP1BMP upstream of the monitoring point (if any).

Identify Relationship to 

Upstream BMP1

Identify Relationship to Upstream BMP. These may include inflow, outflow, 

bypass, intermediate or not applicable.

Identify Downstream BMP1BMP downstream of the monitoring point (if any).

Identify Relationship to 

Downstream BMP1

Identify Relationship to Downstream BMP. These may include inflow, 

outflow, bypass, intermediate or not applicable.

Site Monitoring Instrumentation

Select monitoring station 

where instrument is located1

A monitoring station that contains the instrument must be selected or defined 

before entering data on specific instruments.

What date was the 

instrument installed? 

Provide the date (month, day and 4-digit year) the instrument was installed 

(e.g., 6/1/1998). 

What type of instrument is in 

place? 

The instrument type at the monitoring station. These may include a Bubble 

Gauge, Digital Recorder, Graphic Recorder, Land Line Telemetered, Radio 

Telemetered, Satellite Relayed, ADHAS, Crest Stage Indicator, Tide Gauge, 

Deflection Meter, Stilling Well, CR Type Recorder, Weighing Rain Gauge, 

Tipping Bucket Rain Gauge, Acoustic Velocity Meter, or Electromagnetic 

Flow Meter, Pressure Transducer, Unknown or Other.

What type of monitoring is 

conducted? 

The type of data collected by the instrument based on U.S. Geological 

Survey (USGS) code. Data types may include: Tide, Water Flow/Stage 

Continuous, Water Flow/Stage Intermittent, Water Quality Continuous, Water 

Quality Grab, Precipitation Continuous, Precipitation Intermittent, Evaporation 

Continuous, Evaporation Intermittent, Wind Velocity Continuous, Wind 

Velocity Intermittent, Tide Stage Continuous, Tide Stage Intermittent, Water 

Quality Probe Continuous, Water Quality Probe Intermittent, Unknown, or 

Other.

What type of control structure 

is in place, if any? 

Type of control structure in place at the monitoring station (i.e. 90-degree Vnotched weir, etc.).

Additional Comments May be necessary to explain special features associated with the instrument 

or other information deemed important to the user.

Site Monitoring Costs

Number of years in which 

monitoring was conducted

The number of years over which the monitoring station was in operation

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Data Element Description

Comments May be needed to clarify unusual monitoring costs or other details as 

deemed appropriate by the user.

Fixed Monitoring Station 

Costs

Those costs associated with fixed monitoring instrumentation installed for 

long-term use. For example, a shed may be constructed to house the 

instrumentation. Year of cost basis, equipment, maintenance, sampling and 

laboratory costs are requested for fixed monitoring stations.

Temporary Monitoring

Station Costs

Costs associated with temporary monitoring instruments not intended for 

long-term use. Year of cost basis, equipment, sampling and laboratory costs 

are requested for temporary monitoring stations.

Year of Cost Basis Year that the monitoring activities were conducted or equipment purchased. 

Equipment Costs Costs of sampling and flow gauging equipment (rental or purchase) and 

installation in U.S. currency.

Maintenance Costs Annual maintenance costs for equipment in U.S. currency.

Sampling Costs Annual costs of sampling in U.S. currency.

Laboratory Costs Annual costs of sample analysis by a laboratory. 

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Precipitation Data

The precipitation form contains important precipitation data, which can be used for evaluating

the performance of BMPs under various conditions. Precipitation information requested includes 

data such as time and date that the event began and ended, total depth and one-hour peak

precipitation rate. The precipitation data form and data elements list are provided in Table 3.26

and Form P.

Table 3.26: Precipitation Form Data Elements

Data Element Description

Event ID User provided name or identifier for the precipitation event.

Select Monitoring Station 

for Event1

Monitoring station name where the precipitation event was monitored. 

Start Date Calendar date (month, day and 4-digit year) that storm started (e.g., 

01/01/1998). 

Start Time Time that the storm started, e.g., 21:00. If only storm duration is available, 

record 00:00 for start time and enter the storm duration for end time. 

End Date Calendar date (month, day and 4-digit year) that storm ended (e.g., 

01/01/1998). Use six hours as the separation criteria to define a new storm. 

End Time Time that the storm ended, e.g., 13:21. If only storm duration is available, 

record 00:00 for start time and enter the storm duration for end time. 

Total Storm Precipitation Amount of precipitation that occurred during the storm. For example, a total of 

4 inches of rain fell during a 12-hour storm. 

Peak One Hour 

Precipitation Rate

The most intense one-hour of rainfall for the storm. For storms with less than 

one-hour duration, divide the storm rainfall depth by one hour.

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Form P
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Flow Data

The flow data form provides on-site stormwater runoff information. Accurate flow data coupled 

with water quality information can be used to estimate removal efficiencies for BMPs, providing 

a relative measure of a BMP’s ability to remove certain pollutants. The flow data form contains 

information on the date and time of the beginning and end of the flow event and total flow

volumes and peak flow rates for runoff and baseflow. Each flow event should have a related

precipitation event recorded on the precipitation form. The flow form and data elements list are

provided in Table 3.27 and Form Q. 

Table 3.27: Flow form data elements

Data Element Description

Monitoring Station1 Provide monitoring station where flow event was monitored. 

Select the type of flow1The type of flow: base flow or storm runoff.

If storm runoff, select the 

related precipitation event, 

if available1

The start-date of the precipitation event associated with the current flow event.

Flow Start Date1 Date (month, day and 4-digit year) that the measurement began being taken 

(e.g., 01/01/1998).

Flow Start Time Time at beginning of measurement event, e.g., 23:30. If only flow duration is 

provided, enter 00:00 for start time and enter the flow duration for end time. 

Flow End Date Date (month, day and 4-digit year) that the measurement event ended (e.g., 

01/01/1998). The end of runoff event can be defined as that point in time 

when the recession limb of the hydrograph is <2% of the peak or is within 10% 

of the pre-storm base flow, whichever is greater. 

Flow End Time Time at the end of the measurement event, e.g., 01:30. The end of runoff 

event can be defined as that point in time when the recession limb of the 

hydrograph is <2% of the peak or is within 10% of the pre-storm base flow, 

whichever is greater. 

Total Storm Flow Volume 

into or from BMP1

Total Runoff Volume minus the Bypass Volume.

Peak Storm Flow Rate into 

or from BMP

Greatest rate of storm flow into or from the BMP.

Total Bypass Volume, if 

any1

Total Runoff Volume minus the Runoff Volume Influent to the BMP.

Peak Bypass Flow Rate, if 

any

Peak rate of flow measured for flows bypassing the BMP. 

Dry Weather Base Flow 

Rate1

Flow rate during dry-weather conditions. Base flow is collected during nonwet weather conditions. 

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Water Quality Data

The water quality sampling event form provides the general information for a water quality

sampling event such as date, time, location, and QA/QC measures used for a study. Provided

water quality information must have associated flow and precipitation information recorded on

the precipitation and flow forms. The water quality data form and data elements list are provided 

in Table 3.28 and Form R.

Table 3.28: Water quality form data elements

Data Element Description

Sample ID User provided name or identifier for the water quality sample.

Select Monitoring Station 

Where Data Collected1

Monitoring station name where the data was collected.

Related Flow Event1Flow event associated with the water quality sampling event.

Date Water Quality 

Sample Collected1

Date that the water quality sample began being collected.

Time Water Quality 

Sample Collected

Time that the water quality sample began being collected. 

What medium does the 

instrument monitor? 1

Groundwater, Surface Runoff/Flow, Soil, Dry Atmospheric Fallout, Wet 

Atmospheric Fallout, Pond/Lake Water, Accumulated Bottom Sediment, 

Biological, or Other.

What type of samples are 

collected?1

The type of samples that the instrument collects, including: Flow Weighted 

Composite EMCs (Event Mean Concentrations), Time Weighted Composite 

EMCs, Unweighted (mixed) Composite EMCs, or Grab Sample.

Provide the Number of 

Samples, If Composite 

The number of samples collected or mixed (if composite).

Describe Quality 

Assurance/Quality Control 

Measures in Place for the 

Sampling Event

Describe the types of Quality Assurance/Quality Control (QA/QC) measures in 

place for both laboratories and field activities.

Provide Additional 

Comments, If Needed

Discuss special circumstances associated with the sampling event. 

Water Quality Parameter 

(STORET)1

The STORET name for the U.S. Environmental Protection Agency’s STORET 

water quality database for streams and other waterbodies throughout the 

United States. 

Value1Value of the measured constituent should be provided. If the value is below 

detection limits, provide the reported detection limit with a “U” qualifier in the 

qualifier field and place a minus sign in front of the value. 

Unit1 Unit of the measured constituent should be provided.

Qualifier1 Numerical STORET qualifier associated with a data point.

Analysis Method Analysis Method should be provided for the constituent. For example EPA

8270 or Standard Method 513. 

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Form R
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3.4.3.3 On-line Information

Forms and field descriptions can be printed from the world-wide-web at

www.bmpdatabase.org. Each set of forms is subcategorized into its subsequent BMP

type. Each folder contains all of the necessary forms and information needed for

monitoring and reporting for a particular BMP type. BMP categories include:

• Non-Structural BMPs.

• Detention Basins.

• Retention Ponds.

• Percolation Trenches and Dry 

Wells.

• Media Filters.

• Grass Filter Strips.

• Wetland Channels and Swales.

• Porous Pavement.

• Infiltration Basins.

• Hydrodynamic Devices.

• Wetland Basins. 
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References

American Society for Testing and Materials. 1995. Standard Guide for Selection of Weirs 

and Flumes for Open-Channel Flow Measurement of Water (D5640). American 

Society for Testing and Materials, West Conshohocken, PA.

American Society for Testing and Materials. 1997. Standard Guide For Monitoring

Sediment in Watersheds. ASTM D 6145-97.

American Society for Testing and Materials. 2000. Standard Test Method for

Determining Sediment Concentration in Water Samples. ASTM Designation D

3977-97, 395- 400.

ASCE. 1999. National Stormwater Best Management Practices Database, Verision 1. 

American Society of Civil Engineers, Urban Water Resource Research Council,

June.

ASCE. 2000. Data Evaluation Report, Task 3.4. National Stormwater Best Management

Practices Database Project. June.

Burton, A.G. and R. Pitt. 2001. Stomwater Effects Handbook: A Toolbox for Watershed

Managers, Scientists, and Engineers. Lewis Publishers, Boca Raton, FL.

Caltrans. 1997. Guidance Manual: Stormwater Monitoring Protocols. Prepared by Larry

Walker and Associates and Woodward-Clyde Consultants. August 15.

Caltrans. 2000. California Department of Transportation District 7 Litter Management

Pilot Study, Final Report, Caltrans Document No. CT-SW-RT-00-013, June 26.

Cave, K. A., and L.A. Roesner. 1994. Overview of Stormwater Monitoring Needs.

Proceedings of the Engineering Foundation Conference on Stormwater Monitoring. 

August 7-12, Crested Butte, CO.

Chow, V.T. 1954. The lognormal distribution and its engineering applications. Proc., 

American Society of Civil Engineers. 110, 607-628.

Chow, V.T. 1959. Open-Channel Hydraulics. McGraw-Hill, New York, NY.

Coffey, S.W., and M.D. Smolen. 1990. The Nonpoint Source Manager's Guide to Water

Quality Monitoring - Draft. Developed under EPA Grant Number T-9010662. 

U.S. Environmental Protection Agency, Water Management Division, Region 7,

Kansas City, MO.

Cochran, W.G. 1963. Sampling Techniques. Second Edition. John Wiley and Sons, Inc.

New York, New York.
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 209 April 25, 2002

Driscoll, E., G. Palhegyi, E. Strecker, and P. Shelley. 1989. Analysis of Storm Event

Characteristics for Selected Rainfall Gauges Throughout the United States. Draft 

Rep. Prepared for U.S. Environmental Protection Agency, Woodward-Clyde 

Consultants, Oakland, CA.

Driscoll, E.D., P.E. Shelly, and E.W. Strecker. 1990. Pollutant Loadings and Impacts from 

Stormwater Runoff, Volume III: Analytical Investigation and Research Report. 

Federal Highway Administration Final Report FHWA-RD-88-008, 160 p.

EPA. 1983. Results of the Nationwide Urban Runoff Program, volume I – Final Report. 

U.S. Environmental Protection Agency, Water Planning Division, Washington

D.C.

EPA. 1989. Analysis of Storm Event Characteristics for Selected Gages throughout the

United States. Environmental Protection Agency. Washington D.C.

EPA. 1993a. Guidance Specifying Management Measures for Sources of Nonpoint

Pollution in Coastal Waters. EPA-840-B-93- 001c. U.S. Environmental 

Protection Agency, Office of Water, Washington D.C.

EPA. 1993b. Investigation of Inappropriate Entries into Storm Drainage Systems: A 

User’s Guide. EPA-600-R-92-238. U.S. Environmental Protection Agency, 

Office of Research and Development, Washington D.C.

EPA, 1993c. Memo. Office of Water Policy and Technology. Guidance on Interpretation

and Implementation of Aquatic Life Metals Criteria, Washington, D.C.

EPA. 1994a. Laboratory Data Validation: Functional Guidelines for Evaluating

Inorganics Analyses. U.S. Environmental Protection Agency, Data Review

Workgroup, Washington, D.C.

EPA. 1994b. Laboratory Data Validation: Functional Guidelines for Evaluating

Organics Analyses. U.S. Environmental Protection Agency, Data Review

Workgroup, Washington, D.C.

EPA. 1994c. Guidance for the Data Quality Objectives Process. EPA-QA/G-4. U.S. 

Environmental Protection Agency.

EPA. 1997. Monitoring Guidance for Determining the Effectiveness of Nonpoint Source

Controls. EPA 841-B-96-004. U.S. Environmental Protection Agency, Office of

Water, Washington, D.C. September.

FHWA. 2000. Stormwater Best Management Practices in an Ultra-Urban Setting: 

Selection and Monitoring. FHWA-EP-00-002. U.S. Department of 

Transportation. Federal Highway Administration. Washington, D.C., May.
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 210 April 25, 2002

FHWA. 2000. Guidance Manual for Monitoring Highway Runoff Water Quality. 

Federal Highway Administration, U.S. Department of Transportation. Federal 

Highway Administration. Washington, D.C.

Fischer, H. B., List, J. E., KOH, R. C. Y., Imberger, J., and N.H. Brooks. 1979. Mixing in 

Inland and Coastal Waters. Academic Press Inc., San Diego, CA.

Gilbert, R.O. 1987. Statistical Methods for Environmental Pollution Monitoring. John

Wiley and Sons, Inc. New York, New York.

Grant, D.M. and B.D. Dawson. 1997. ISCO Open Channel Flow Measurement Handbook. 

ISCO Environmental Division. Lincoln, NE.

Gray, J.R., G.D. Glysson, and L.M. Turcios. 2000. Comparability and reliability of total

suspended solids and suspended-sediment concentration data. U.S. Geological

Survey Water-Resources Investigations Report 00-4191. U.S. Geological Survey.

Green, D., T. Grizzard, and C. Randall. 1994. Monitoring of Wetlands, Wet Ponds, and

Grassed Swales. In Proceedings of the Engineering Foundation Conference on

Storm Water Monitoring. August 7-12, Crested Butte, CO.

Gupta, R.S. 1989. Hydrology and Hydraulic Systems. Prentice Hall. NJ. 

Gwinn, W.R., and D.A. Parsons. 1976. Discharge Equations for HS, H and HL Flumes.

Journal of the Hydraulics Division American Society of Civil Engineers, Vol. 102,

No. HY1 pp. 73-89.

Harremoes, P. 1988. Stochastic models for estimations of extreme pollution from urban

runoff. Water Resource Bulletin, 22, 1017-1026.

Harrison, D. 1994. Policy and Institutional Issues of NPDES Monitoring: Local Municipal 

Perspectives of Stormwater Monitoring. Proceedings of the Engineering Foundation 

Conference on Storm Water Monitoring. August 7-12, Crested Butte, CO.

James, W. 2001. http://131.104.80.10/webfiles/james/KeyModels.html.

Loftis, J.C., L.H. MacDonald, S. Streett, H.K. Iyer, and K. Bunte. 2001. Detecting 

Cumulative Watershed Effects: The Power of Pairing. In Review Journal of

Hydrology. 

Martin, E.H., and J.L. Smoot. 1986. Constituent-load changes in urban storm water

runoff routed through a detention pond-wetland system in central Florida. Water 

Resources Investigation Report 85-4310. U.S. Geological Survey.
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 211 April 25, 2002

Martin, G.R., J.L. Smoot, and K.D. White. 1992. A Comparison of Surface-Grab and

Cross Sectionally Integrated Stream-Water-Quality Sampling Methods. Water

Environment Research. November/December 1992.

Minton, G.R. 1998. Stormwater Treatment Northwest, Vol. 4, No. 3, August.

National Urban Runoff Program. 1983. Final Report. U.S. Environmental Protection

Agency Water Planning Division, Washington, D.C.

Oswald, G.E., and R. Mattison. 1994. Protocols for Monitoring the Effectiveness of

Structural Stormwater Treatment Devices. In Proceedings of the Engineering

Foundation Conference on Storm Water Monitoring. August 7-12, Crested Butte, 

CO.

Pitt, R. 1979. Demonstration of Nonpoint Pollution Abatement Through Improved Street 

Cleaning Practices, EPA-600/2-79-161, U.S. Environmental Protection Agency,

Cincinnati, Ohio.

Pitt, R. 2001. Personal Correspondence. Peer review meeting, August.

Pitt, R. and K. Parmer. 1995. Quality Assurance Project Plan (QAPP) for EPA

Sponsored Study on Control of Stormwater Toxicants. Department of Civil and

Environmental Engineering, University of Alabama at Birmingham. 

Ponce, V.M. 1989. Engineering Hydrology Principles and Practices. Prentice Hall,

Englewood Cliffs, NJ.

Ruthven, D.M. 1971. "The Dispersion of a Decaying Effluent Discharged Continuously

into a Uniformly Flowing Stream," Water Research, 5(6) 343-352.

Quigley, M.M, and E.W. Strecker. 2000. Protocols and methods for evaluating the

performance of stormwater source controls. NATO Advanced Research Workshop 

on Source Control Measures for Stormwater Runoff, St. Marienthal, Ostritz,

Germany.

Saunders, T.G. 1983. Design of Networks for Monitoring Water Quality. Water 

Resources Publications. December.

Schueler, T.R. 1987. Controlling Urban Runoff: A Practical Manual for Planning and

Designing Urban BMPs. Washington Metropolitan Water Resources Planning

Board, Washington, D.C.

Schueler, T. 1996. Irreducible Pollutant Concentrations Discharged from Urban BMPs.

Watershed Protection Techniques, 1(3): 100-111. Watershed Protection

Techniques 2(2): 361-363.
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 212 April 25, 2002

Schueler. 2000. National Pollutant Removal Performance Database: for Stormwater

Treatment Practices, Second Edition. Center for Watershed Protection. June.

Spitzer, DW (ed.) 1996. Flow Measurement Practical Guides for Measurement and

Control. Instrument Society of America. NC.

Strecker, E.W., J.M. Kersnar, E.D. Driscoll, and R.R. Horner. 1992. The use of wetlands 

for controlling storm water pollution. The Terrene Institiute, Washington, D.C.

Strecker, E.W. 1994. Constituents and Methods for Assessing BMPs. In Proceedings of

the Engineering Foundation Conference on Storm Water Monitoring. August 7-

12, Crested Butte, CO.

Strecker, E.W., M.M. Quigley, B.R. Urbonas, J.E. Jones, and J.K. Clary. 2001. 

Determining Urban Storm Water BMP Effectiveness. Journal of Water

Resources Planning and Management, 127 (3), 144-149.

Stenstrom, M.K. and E.W. Strecker. 1993. Assessment of Storm Drain Sources of

Contaminants to Santa Monica Bay. Volume II. UCLA School of Engineering and 

Applied Science. UCLA ENG 93-63.

Stevens Water Resources Data Book. 1998. Leupold & Stevens, Inc. Beaverton, OR.

Taylor, J.R. 1997. An Introduction to Error Analysis. University Science Books,

Sausalito, CA.

Urbonas, B.R. 1994. Parameters to Report with BMP Monitoring Data. In Proceedings 

of the Engineering Foundation Conference on Storm Water Monitoring. August

7-12, Crested Butte, CO.

Urbonas, B., and Stahre, P., 1993. Stormwater: Best management practices and

detention for water quality, drainage, and CSO management, Prentice Hall,

Englewood Cliffs, NJ.

USGS. 1980. National Handbook of Recommended Methods for Water-Data Acquisition. 

U.S. Geological Survey. Reston, VA.

USGS. 1985. Development and Testing of Highway Storm-Sewer Flow Measurement 

and Recording System. Water-Resources Investigations Report 85- 4111. U.S.

Geological Survey. Reston, VA.

USGS. 2001. A Synopsis of Technical Issues for Monitoring Sediment in Highway

and Urban Runoff. Open-File Report 00-497. U.S. Geological Survey, 

Northborough, MA.
Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

 213 April 25, 2002

Van Buren M.A., W.E. Watt, and J. Marsalek. 1997. Applications of the Log-normal and 

Normal Distributions to Stormwater Quality Parameters. Wat. Res., Vol. 31, No 1, 

pp. 95-104.

Waschbusch, R., and D. Owens. 1998. Comparison of Flow Estimation Methodologies in

Storm Sewers. United States Geological Survey, January 16.

Watt, W.E., K.W. Lathem, C.R. Neill, T.L. Richards, and J. Rouselle, (Eds). 1989. 

Hydrology of Floods in Canada: A Guide to Planning and Design. National

Research Council Canada, Ottawa, Ontario.

WCC. 1993. Data from storm monitored between May 1991 and January 1993. Final 

Data Rep. Woodward-Clyde Consultants. Prepared for Bureau of Environmental 

Services, City of Portland, Oregon; Portland, OR.

WCC. 1995. Stormwater Quality Monitoring Guidance Manual. Woodward-Clyde 

Consultants. Prepared for Washington State Department of Ecology Water Quality 

Program. November.
Urban Stormwater BMP Performance Monitoring

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 214 April 25, 2002

INDEX

A

Accuracy, 52, 61, 62, 64, 65, 82, 92, 93, 

94, 100, 106, 110, 120, 126, 129, 135, 

136, 141, 144, 1

Achievable efficiency, 32, 34, 35, 37

Agriculture, 155, 159

Analysis, 

of variance, 26, 41, 70, 72, 74, 145

sample, 119, 125

standards violations, 11

Analytical, 12, 13, 45, 46, 48, 76, 77, 79, 

80, 81, 82, 121, 123, 125, 128, 129, 

137, 142, 143, 144, 145, 146, 209

ASCE, 33, 48, 77, 137, 139, 147, 208, 1

Assumptions, 23, 24, 26, 29, 31

Atmospheric deposition, 63

B

Bias, 81, 109, 112, 126, 140

BMP

effectiveness, 12, 40, 45, 52, 68, 96, 

156, 166, 167

efficiency, 2, 4, 8, 12, 14, 15, 16, 17, 

18, 21, 32, 33, 34, 40, 61, 71

monitoring, 2, 4, 5, 6, 8, 18, 21, 37, 

43, 46, 47, 48, 49, 52, 53, 55, 58, 

61, 63, 70, 72, 77, 80, 83, 102, 111, 

115, 122, 123, 124, 127, 132, 147, 

156

non-structural, 149, 166

structural, 149, 161, 164, 166, 167, 

170, 207

systems, 44

types, 13, 33, 164, 166

C

Calibration, 107, 118, 141

Central tendency, 41

Chi-square, 41

Clean Water Act, 4, 11

Climate, 16, 65, 148

Coefficient of variation, 22, 70, 71, 75, 

76, 145

Completeness, 129, 137

Compliance, 6, 49, 51

Concentrations, 17, 18, 205, 211

Construction, 7, 100, 155, 159, 166, 170, 

173, 176, 179, 181, 183, 187, 190, 

192, 195

Cost, 6, 100, 167, 169, 173, 175, 178, 

181, 183, 187, 189, 192, 195, 199

CZARA, 4, 5

D

Data, 

water quality, 22, 58, 69, 130, 149, 

205

Data Logger, 83, 84, 85, 88

Data management, 45, 48

Data Quality Objectives, 129, 209

Design flow, 181

Detention Basin, 150, 169, 207

Dry weather flow, 18

E

Effectiveness, 6, 10, 209, 211, 212

Efficiency, 13, 15, 18, 20, 21, 24, 25, 28, 

29, 30, 32, 33, 34, 35, 37, 38, 39

Efficiency Ratio (ER), 20, 21, 24, 31, 

32, 33, 34, 35, 38, 39, 41

Effluent, 18, 20, 33, 34, 35, 36, 40, 211

EPA, 4, 5, 7, 11, 12, 22, 31, 48, 49, 50, 

65, 66, 68, 70, 71, 74, 79, 81, 82, 113, 

117, 128, 134, 135, 136, 137, 139,

144, 145, 147, 156, 159, 205, 208, 

209, 211, 1

Erosion, 164, 166

Error, 28, 29, 126, 130, 212, 2, 5, 7

Evaluation, 2, 17, 37, 41, 51, 52, 67, 78, 

122, 144, 145

Event mean concentration, 16, 17, 18, 

21, 22, 23, 24, 36, 70, 72

F

FHWA, 77, 118, 119, 120, 209, 210

Field blanks, 133, 135

Field duplicate samples, 135
Urban Stormwater BMP Performance Monitoring

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 215 April 25, 2002

Field operations, 134

Filter, 150, 151, 178, 179, 181, 207

Flow Measurement, 90, 96, 99, 102, 208, 

210, 212

Flow meter, 141

G

Geology, 64

Grass filter strip,181

Great Lakes, 64

H

Habitat, 6

Human Health, 50

Hydrodynamic device, 192

Hypothesis testing, 72, 145, 147

I

Implementation, 6, 139, 209

Infiltration Basin, 150, 151, 189, 190, 

207

Inflow, 183

In-situ, 119, 121, 123

Irreducible concentration, 33

K

Kolmogorov-Smirnov, 41

L

Lakes, 64

Load, 10, 11, 18, 31

M

Management, 2, 3, 10, 15, 16, 18, 48, 65, 

66, 137, 138, 146, 147, 208, 209, 212

Mean concentration, 21

Methods

Effluent Probability, 18, 20, 34, 40

Reference Watershed, 43

tracer dilution, 95

Model

Non-Linear, 20, 40

Models, 20, 40, 87

Monitoring, 4, 5, 8, 9, 10, 11, 12, 14, 24, 

43, 45, 46, 47, 49, 51, 53, 55, 56, 57, 

59, 60, 61, 62, 68, 76, 83, 92, 102, 

109, 114, 124, 139, 141, 146, 147, 

148, 149, 157, 198, 199, 201, 203, 

205, 208, 209, 210, 211, 212, 213

Monitoring station, 59, 60, 61, 62, 146,

198, 201, 205

N

National Stormwater BMP Database, 2, 

147, 148, 149, 150, 155, 156, 157, 

161, 164, 167, 170, 173, 176, 179, 

181, 184, 187, 190, 192, 195, 199, 

201, 203, 205

Nonpoint, 4, 114, 208, 209, 211

NURP, 12, 13, 77

O

Overland flow sampler, 119

P

Percent removal, 39

Pesticides, 17, 79

Ponds, 150, 173, 207, 210

Porous Pavement, 150, 152, 186, 187, 

207

Q

Quality assurance and quality control, 

129, 130, 131, 134, 135, 136, 137, 

143, 144, 205

Quality assurance project plan, 211

R

Range, 99, 128, 157

Regression, 20, 21, 25, 27, 32

Regression of loads (ROL), 20, 21

Retention Pond, 150, 152, 172, 173, 207

S

Safety, 6, 131

Sample, 111, 113, 125, 132, 135, 136, 

139, 146, 149, 205
Urban Stormwater BMP Performance Monitoring

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 216 April 25, 2002

composite, 112

grab, 111

Sampling, 13, 17, 58, 63, 77, 82, 96, 

114, 115, 124, 125, 132, 149, 199, 

205, 208, 211

automatic, 90, 102

manual, 90, 102, 124, 125

methods, 13, 77

sediment, 63

Sampling Methods, 132, 211

Sensor

ultrasonic depth, 102, 104

Sensors

electromagnetic, 107, 110

Soils, 189

Stage-flow relationships, 98

Statistic

mean, 11, 17, 18, 20, 21, 29, 157, 205

variability, 70

Storm event, 114

Stormwater quality, 7, 8, 51, 69, 145

Stream, 65, 211

Summation of loads, 21

Surface Water, 49

T

Test, 45, 147, 148, 149, 156, 157, 166, 

208

Toxicity, 6, 16

Training, 134, 139

TSS, 16, 17, 24, 25, 27, 28, 29, 32, 33, 

34, 35, 38, 43, 64, 79, 80, 82

V

Variability, 70

VOC, 112, 115, 117

W

Water Quality, 11, 36, 41, 49, 50, 51, 64, 

138, 141, 152, 154, 172, 205

Wetland, ix, 150, 153, 154, 183, 184, 

194, 195, 207

Wetland Basin, 150, 154, 194, 195, 207
A-1

Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

APPENDIX A

ERROR ANALYSIS

Estimating flow in a pipe or open channel is generally accomplished by measuring two or 

more variables and relating them with an equation to calculate the flow. The continuity

equation relates flow to area and velocity:

Q = A× v (A.1)

where, 

A: Area

v : Velocity

For a rectangular channel, the cross-sectional area can be calculated as the water depth

multiplied by the width of the channel. 

A = H × w (A.2)

where, 

H: Depth

W: Width

Velocity can be directly measured with a mechanical current meter or Doppler

technology. Estimating flow in the rectangular channel requires three measured variables; 

each will have an error associated with it:

Q = H × w× v (A.3)

For depth and width measurements, the accuracy will usually be expressed as absolute

error governed by the tolerance of the measuring device (i.e. measured depth + X cm).

For velocity, the error in measurement will most likely be a relative error expressed as a

percent of the measured value (i.e. measured velocity + X %). The total error in the

calculated flow measurement will include all of the errors associated with the individual

measurements as illustrated in the following example: 

Equipment tolerances provided by manufacturers generally are based on laboratory data

under ideal conditions (e.g. steady state, laminar flow), which may not be representative

of installed conditions. A recent USGS study compared several flow monitoring devices 

designed specifically for stormwater application, and found the error in the observed

measurements ranged from 12 to 28 percent.

The actual error is most likely somewhat less than the maximum error and mathematical

formulas have been described by Taylor (1997), which describe how error propagates

when variables (with associated errors) are combined. 

If variables xi (for I=1 to n) are measurements with small but known uncertainties δxi and 

are used to calculate some quantity q, then δxi cause uncertainty in q as follows. 
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

If q is a function of one variable, q(x1), then

1

1

x

dx

dq dq = d (A.4)

If q is the sum and/or difference of xis then

( )

2

1

1

2













= ∑=

n

i

i

dq dx (for independent random errors) (A.5)

Estimates of δq from Equation A.2 are always less than or equal to:

= ∑ idq dx

where xi are measured with small uncertainties δxi. 

If q is the product and quotient of xis then 

2

1

1

2

































= ∑=

n

i i

i

x

x

q

d

d (for independent random errors) (A.6)

Estimates of δq from Equation A.6 are always less than or equal to:

= ∑

i

i

x

x

q

d

d (A.7)

This approach can be directly applied to the analysis of error propagation. Examples for 

applying this method to flow measurement follow.

Relative Error in Flow Versus Relative Error in Head 

Errors in flow measurements are most often caused by field conditions that are

inconsistent with the conditions under which rating curves for flow devices were

calibrated. However, even under ideal conditions, errors in flow measurement can be

significant. This section discusses calculations for estimating the theoretical error

associated with flow measurement equipment under ideal circumstances. It can be seen

that errors, particularly in low flow measurements, can be quite large. 
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

Equations relating the head (H) measured in a primary device to discharge (Q) (i.e., 

Rating Equations) fall into four general forms:

1) d Q = aH

2) d Q = a(H + c)

3) d Q = a(bH + c)

4) n Q = a + b H + b H + b H +L+ bnH

3

3

2

1 2

The first rating equation is a straight forward application of error propagation for a power 

function. This equation is













=

H

H

Q Q d

d

d (A.8)

Flow and head can only be positive values and the power for Rating Equation 1 is always 

positive (i.e., flow increases proportionally to head, not decreases), thus the absolute

value sign is omitted in the above equation. The relative error in flow equals the relative 

error in head multiplied by the exponent d.

Rating Equations 2, 3, and 4 require an equation relating the error in flow to the

derivative of the flow equation and the error in the measured head, which is:

H

dH

dQ dQ = d (A.9)

Before applying this equation, the derivatives of Rating Equations 2, 3, and 4 are taken 

with respect to H. 

For Rating Equation 2: 

1

( )

−

= +

d

ad H c

dH

dQ (A.10)

For Rating Equation 3:

1

( )

−

= +

d

abd bH c

dH

dQ (A.11)

For Rating Equation 4:

2 1

3

1

1 2

2 3

−

= + + + +

n

b b H b H nbnH

dH

dQ L (A.12)
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

Prior to applying the equation to the derivatives of Rating Equations 2, 3, and 4 the

equation is modified by dividing each side of the Equation by the flow (Q). This yields 

an equation for the relative error in the flow on the left hand side.

Q

H

dH

dQ

Q

dQ d

= (A.13)

Substituting flow Rating Equation 2 for Q and the derivative of Rating Equation 2 for 

dQ/dH into the right hand side of the above equation, yields:

( )

d

d

a H c

H

ad H c

Q

Q

+

= +

d −1 d

( ) (A.14)

which reduces to:

H

H

H

c

d

Q

dQ d













+

=

1

(A.15)

Equation A.11 relates the relative error in the flow to the relative error in the head.

A similar analysis for Rating Equation 3 yields:

H

H

bH

c

d

Q

dQ d













+

=

1

(A.16)

Determining an equation for the relative error for Rating Equation 4 is more

cumbersome, but is calculated the same way:

n

n

n

n

a b H b H b H b H

H

b b H b H nb H

Q

Q

+ + + + +

= + + + +

−

L

L 3

3

2

1 2

2 1

3

1

1 2

2 3

d d

 (A.17)

Rearranging yields:

H

H

a b H b H b H b H

b b H b H nb H

Q

Q

n

n

n

d n d

+ + + + +

+ + + +

=

L

L

3

3

2

1 2

3

3

2

1 2 2 3

(A.18)

Equation A.4, A.11, A.12, and A.14 relate the relative error in flow to the relative error in 

head for four common equations describing flow through a primary device. While the

equations can be unwieldy, it is a relatively simple exercise to enter them into a

spreadsheet program to estimate the error in flow based on estimated error in head and

other variables. Most primary devices have a relatively simple flow equation that is
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

sufficiently accurate throughout most of the flow range for the device, which allows for

the use of an error equation related to one of the Rating Equations. 

The equations relating the relative error in the estimate of flow to the relative error in the 

measurement of head can also be expressed in terms of absolute errors by multiplying 

each side of the equations by Q. For example the flow Equation 3 becomes:

a(bH c) abd bH c H

H

H

bH

c

d

Q

Q

Q

d d

d

d d 1

( )

1

−

× + = +













+

× = (A.19)

An Example of Error Analysis for a BMP

The following example illustrates how estimates of error propagation can be applied to

flow measurements. This example assumes a stormwater BMP has two separate sources 

of inflow and one outflow. The flow measurement devices and errors are listed in Table

1.

Table A.1: Example of inputs for estimation of errors in flow measurement devices

Station Variable Equipment Measured Value or 

formula

Accuracy

Inlet 1 Width Tape Measure 3 meters + 0.025 meters

Depth Pressure Transducer 1.2 meters + 0.007 meters

Velocity Doppler 0.071 meters/sec + 4 %

Inlet 2 Depth Bubbler 0.12 meters + 0.001 meters

0.457 m (1.5’) 

Palmer-Bowlus 

Flume

Q (L/s) = 

1076.4(H + 0.005715)1.8977

+ 3 %

Outlet Depth Pressure Transducer 0.70 meters + 0.007 meters

45o V notch weir Q (L/s) = 571.4H2.5 + 6 %

For Inlet 1, the flow calculation is:

Q m m m s inlet (3) (1.2) (0.071)

−1 = × ×

Q m s inlet

3

1 = 0.2556 −

The error associated with this measurement can be calculated using the equation for error 

of products and quotients (i.e., Equation A.6):

Assuming that the errors are independent and randomly distributed, the relative error in q 

equals: 
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

0.0413

2 2 2

 =











 +











 +











=

v

v

H

H

w

w

q

dq d d d

( )

2

2 2

0.04

1.2

0.007

3

.025  +











 +











=

q

dq

q m s m s

3 3

d = 0.2556 / × 0.0413 = 0.011

So that:

Q m s inlet

3

1 = 0.2556 ± 0.011 −

For the Palmer-Bowlus Flume installed in Inlet 2, the equation that describes flow (L/s) 

as function of water depth is: 

1.8977

2 = 1076.4× ( + 0.005715) Qinlet− H

Therefore:

1.8977

2 = 1076.4× (0.12 + 0.005715) Qinlet−

Q L s m s inlet

3

2 = 21.032 / = 0.0210 −

The error associated with flow measurement above is proportional to the precision of the 

transducer used to measure the water depth (i.e., + 0.007 meters) and the error intrinsic

to the primary device (a relative error of 3%). Rating Equation 1 is used for this case;

Equation A.8 can be used to determine the magnitude of relative error in the flow

measurement as:

H

H

H

c

d

Q

dQ d













+

=

1

0.11

0.12

0.007

0.12

0.005715 1

1.8977

=













+

=

m

m

m

Q

dQ

Q m s m s

3 3

d = 0.021 / × 0.11 = 0.00231

Relative error for the flume itself also has to be included. Since the error is a function of 

one variable, it can be calculated using Equation A.4:

x m s m s

dx

dq

q

3 3

d = d = 0.03× 0.021 = 0.00063
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

The total error is therefore the sum of errors associated with the measuring device 

(Equation A.5).

q m s inlet total

2 2 3

d −2( ) = 0.0023 + 0.00063 = 0.0024

Q m s inlet

3

2 = 0.0210 ± 0.0024 −

For the Outlet weir, the flow can be calculated using the following equation:

2.5 Q = 571.4× H

Q L s m s

2.5 3

= 571.4× 0.70 = 234.25 / = 0.234

This is also a power function (Rating Equation 1) and the error can be calculated 

similarly to the equation for the flume:

Q 0.234 m /s 0.059 m /s

0.70

0.007 2.5

3 3

d = =

The error associated with the weir itself is a single variable as was the flume:

q 0.06 0.234m /s 0.014 m /s

3 3

d = × =

The total error is the sum of the errors associated with the measuring device and is 

calculated as follows:

q m s Outlet total

2 2 3

d ( ) = 0.059 + 0.014 = 0.061

Q m s outlet

3

= 0.234 ± 0.061

Results of this error analysis are provided below in Table A.2.

Table A.2: Summary of examples demonstrating the propagation of errors in flow 

measurement

Flow (m3/sec) Total Error (m3/sec) Total Relative Error

(m3/sec)

Inlet-1 0.255 + 0.011 4%

Inlet-2 0.021 + 0.0024 11%

Outlet 0.234 + 0.061 26%
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

APPENDIX B

NUMBER OF SAMPLES REQUIRED FOR VARIOUS POWERS, CONFIDENCE 

INTERVALS, AND PERCENT DIFFERENCES

The figures in this Appendix are from: R. Pitt and K. Parmer. Quality Assurance Project 

Plan (QAPP) for EPA Sponsored Study on Control of Stormwater Toxicants. Department 

of Civil and Environmental Engineering, University of Alabama at Birmingham. 1995.
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002
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Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002
C-1

Urban Stormwater BMP Performance Monitoring

 A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

APPENDIX C

DERIVATION OF THE NUMBER OF SAMPLES REQUIRED TO MEASURE A 

STATISTICAL DIFFERENCE IN POPULATION MEANS

Define: COV = σ / C

% removal = ( )

in

in out

C

C −C

Setting the lower boundary of the influent confidence interval to the upper boundary of the 

effluent confidence interval gives:

n

C

n

C

out

out

in

in

s s

a a 2

2

− Ζ = + Ζ

The COV is substituted for the σ in the above equation. While the σ of a BMP effluent is almost 

certainly less than the σ of the BMP influent, the assumption that COVin = COVout is a more

reasonable one. In most instances the COV of the BMP effluent would be less than the influent. 

Ample data are available for estimating the COV for influent flows to stormwater BMPs, such as 

the ASCE database; this is not the case for effluent flows. It is also assumed that n is the same

for the influent and effluent (nin = nout). These assumptions simplify the equation. 

Substituting σin = COV × Cin and σout = COV × Cout , where COVin = COVout yield:

n

COV C

C

n

COV C

C

out

out

in

in

×

= + Ζ

×

− Ζ

2 2

a a

rearranging:















 +

− = × Ζ

n

C C

C C COV in out

in out

2

a

Substituting for C C C (%removal)

out = in − in gives:















 × − ×

× = × Ζ

n

C removal C

C removal COV in in

in

2 %

%

2

a

Dividing both sides by Cin and solving for n yields:

( )

2

2

%

2 %















Ζ × × −

=

removal

COV removal

n

a

The above approach considers the number of samples required for a power of 50%. For an 

arbitrary power the equation becomes:
C-2

Urban Stormwater BMP Performance Monitoring

 A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

( )

2

2 2

%

2 %

























× × −











Ζ + Ζ

=

removal

COV removal

n

a b

where, 

Zβ/2: false negative rate (1-β is the power. If used, a value of β of 0.2 is common, but it 

is frequently ignored, corresponding to a β of 0.5.)
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 Urban Stormwater BMP Performance Monitoring

A Guidance Manual for Meeting the National Stormwater BMP Database Requirements

April 25, 2002

APPENDIX D

RELATIONSHIPS OF LOG-NORMAL DISTRIBUTIONS

Table D.1

T = EXP (U) S = M * CV

M = EXP (U + 0.5 * W2) W = SQRT (LN (1 + CV2)

M = T * SQRT (1 + CV2) U = LN (M/EXP (O.5 * W2))

CV = SQRT (EXP (W2) - 1) U = LN (M/SQRT (1 + CV2)

Parameter designations are defined as:

Arithmetic Logarithmic

MEAN M U

STD DEVIATION S W

COEF OF VARIATION CV

MEDIAN T

LN(x) designates the base e logarithm of the value x 

SQRT(x) designates the square root of the value x 

EXP(x) designates e to the power x