United States Region III
Environmental Protection Chesapeake Bay
Agency Program Office
Region III
Water Protection
Division
EPA 903-R-17-002
CBP/TRS 320-17
November 2017
In coordination with the Office of Water/Office of Science and Technology, Washington, D.C., and the
states of Delaware, Maryland, New York, Pennsylvania, Virginia, and West Virginia and the District of
Columbia
Ambient Water Quality
llSsEZ 7 - -
Criteria for Dissolved
Oxygen, Water Clarity
and Chlorophyll a for
the Chesapeake Bay
and Its Tidal Tributaries
2017 Technical Addendum
November 2017
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Ambient Water Quality Criteria for
Dissolved Oxygen, Water Clarity and
Chlorophyll a for the Chesapeake Bay and
Its Tidal Tributaries: 2017 Technical
Addendum
November 2017
U.S. Environmental Protection Agency
Region III
Chesapeake Bay Program Office
Annapolis, Maryland
and
Region III
Water Protection Division
Philadelphia, Pennsylvania
in coordination with
Office of Water
Office of Science and Technology Washington, D.C.
and
the states of
Delaware, Maryland, New York
Pennsylvania, Virginia, and
West Virginia and the District of Columbia
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V
Contents
Acknowledgements viii
Principle and Contributing Authors viii
Criteria Assessment Protocol Workgroup viii
Umbrella Criteria Assessment Team ix
Water Quality Goal Implementation Team ix
Scientific and Technical Advisory Committee x
Chesapeake Bay Program Partners x
I. Introduction l
Literature Cited 3
II. Assessing Short-Duration Dissolved Oxygen Criteria Attainment 5
Background 5
Segment Level Assessment 6
Direct Assessment with Enhanced Monitoring 7
Assessing Conditional Attainment Across Dissolved Oxygen Criteria 7
Demonstrating Conditional Dissolved Oxygen Attainment 8
Historical Evidence Demonstrating Conditional Attainment 8
Recent Evidence Demonstrating Conditional Attainment 10
Example of Conditional Attainment Assessment 13
Application of Conditional Criteria Attainment Assessment 16
Framing the Assessment of Open Water Short Duration Dissolved Oxygen
Criteria 17
Rationale for Sub-segmenting Open-Water Designated Use Segments into
Zones 17
Three Zones within the Open-Water Designated Use 188
Criteria Assessment Procedures Tailored Towards the Three Zones 200
Continuous Monitoring-based Assessment 211
Discrete Monitoring-based Assessment 24
Recommended Methods for Assessing Short-Duration Dissolved Oxygen
Criteria Attainment 24
Literature Cited 26
III. Accounting for Missing Volumes in the Chesapeake Bay Program
Segmentation to Support Clean Water Act 303(d) Listing
Assessments 30
Background 30
WBRTF Segment Volume 32
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ANATF MD and PAXTF Segment Volumes 32
Literature Cited 32
IV. Development of a Multi-metric Chesapeake Bay Water Quality
Indicator for Tracking Progress toward Chesapeake Bay Water
Quality Standards Achievement 34
Background 34
Criteria Attainment Assessment Methodologies 36
Four Levels of Water Quality Attainment Assessment 37
Criterion Assessment Level 38
Designated Use Assessment Level 38
Chesapeake Bay Segment Assessment Level 39
Chesapeake Bay-wide Assessment Level 39
Structure of the Multi-Metric Water Quality Standards Indicator 39
Rules for Computing the Indicator 42
Literature Cited 44
V. Aligning the Chesapeake Bay Program's Underwater Bay Grasses
Restoration Goal with the Jurisdictions' Chesapeake Bay Water
Quality Standards 46
Background 46
History of Developing the Underwater Bay Grasses Restoration Goal 48
Restoration Goal and Water Quality Standards Underwater Bay Grasses
Restoration Acreages Comparison 49
Water Quality Standards-based Underwater Bay Grasses Restoration Acreage
51
Chesapeake Bay Program 192,000 Acre Water Quality Standards-based
Underwater Bay Grasses Acreage Goal 63
Considerations for Future Underwater Bay Grasses Restoration Acreage Goals
63
Literature Cited 64
VI. Interim Rules for Water Quality Clean Water Act Section 303(d)
Listing Status Using the Chesapeake Benthic Index of Biotic Integrity
to Support Aquatic Life Use Assessments 66
Background 67
Review of Index Recalibration Results 68
Water Quality Status Classifications 68
Interim Rules for Defining Chesapeake Bay Aquatic Life Use Water Quality
Status 69
Literature Cited 72
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Acronyms 73
Appendices
A. Conditional Probability Analysis Support 74
B. Rationale for Sub-segmenting Open-Water Designated Use Segments into Zones 87
C: Chesapeake Bay Water Quality Data Supporting Development and Testing of Short-
Duration Dissolved Oxygen Criteria Assessments 100
D. Western Branch Patuxent River Tidal Freshwater Segment Metadata 103
E. Centroid Coordinates for Grid Cells Used to Define the Chesapeake Bay Western Branch
Tidal 109
F. Accounting for the Segment*Designated Use*Criteria Combinations used to Compute the
Multi-metric Water Quality Standards Indicator Ill
G. Chesapeake Benthic Index of Biotic Integrity Recalibration Report 116
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Acknowledgements
This eighth addendum document since the April 2003 publication of Ambient Water
Quality Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the
Chesapeake Bay and Its Tidal Tributaries was developed and documented through a
collaborative effort of the members of the Chesapeake Bay Program Science, Technical
Assessment and Reporting Team's Umbrella Criteria Assessment Team, Criteria
Assessment Protocol Workgroup, and Tidal Monitoring and Analysis Workgroup and
the Water Quality Goal Implementation Team.
Principle and Contributing Authors
This document resulted from the collaborative expertise and talent of Chesapeake Bay
Program partnership (the Partnership) state agency, federal agency, interstate river
basin commissions, contract statistician and academic institutional partners. Unless
noted, authors' affiliations are listed under the specific workgroup, team or committee
acknowledgement. The principal authors (listed first) and contributing authors (listed
in alphabetical order) follow by chapter:
Chapter 1. Peter Tango
Chapter 2. Peter Tango, Richard Batiuk U.S. Environmental Protection Agency
Chesapeake Bay Program Office, Walter Boynton, Claire Buchanan, Matt Hall, Will
Hunley, Elgin Perry, Tish Robertson, and Mark Trice.
Chapter 3. Howard Weinberg and Peter Tango
Chapter 4. Liza Hernandez, University of Maryland Center for Environmental
Studies, and Peter Tango
Chapter 5. Howard Weinberg, Rebecca Golden, Maryland Department of Natural
Resources, and Peter Tango
Chapter 6. Peter Tango
Criteria Assessment Protocol Workgroup
Peter Tango, Chair, United States Geological Survey/Chesapeake Bay Program Office;
Melissa Merritt, Staff, Chesapeake Research Consortium/Chesapeake Bay Program
Office; John Backus, Maryland Department of the Environment; Thomas Barron,
Pennsylvania Department of Environmental Protection; Clifton Bell, Brown and
Caldwell; Mark Bennett, United States Geological Survey; Lucretia Brown, District of
Columbia Department of the Energy and the Environment; Claire Buchanan, Interstate
Commission on the Potomac River Basin; Bill Dennison, University of Maryland
Center for Environmental Science; Sherm Garrison, Maryland Department of Natural
Resources; William Hunley, Hampton Roads Sanitation District; Arianna Johns,
Virginia Department of Environmental Quality; Cindy Johnson, Virginia Department
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of Environmental Quality; Renee Karrh, Maryland Division of Natural Resources; John
Kennedy, Virginia Department of Environmental Quality; Rodney Kime, Pennsylvania
Department of Environmental Protection; Michael Lane, Old Dominion University;
Roberto Llanso, Versar Inc; Bruce Michael, Maryland Department of Natural
Resources; Hassan Mirsajadi, Delaware Department of Natural Resources and
Environmental Control; Ken Moore, Virginia Institute of Marine Science; Tom
Parham, Maryland Department of Natural Resources; David Parrish, Virginia Institute
of Marine Science; Elgin Perry, Statistical Consultant; Scott Phillips, United States
Geological Survey; Tish Robertson, Virginia Department of Environmental Quality;
John Schneider, Delaware Department of Natural Resources and Environmental
Control; Donald Smith, Virginia Department of Environmental Quality; Cleo Stevens,
Virginia Department of Environmental Quality; Matthew Stover, Maryland
Department of the Environment; Richard Tian, University of Maryland Center for
Environmental Science; Mark Trice, Maryland Department of Natural Resources;
Howard Weinberg, University of Maryland Center for Environmental Science; David
Wolanski, Delaware Department of Natural Resources and Environmental Control;
John Wolf, United States Geological Survey; Joseph Wood, Chesapeake Bay
Foundation; and Qian Zhang, University of Maryland Center for Environmental
Sciences.
Umbrella Criteria Assessment Team
Peter Tango, Coordinator, United States Geological Survey/ Chesapeake Bay Program
Office; Walter Boynton, University of Maryland Center for Environmental Sciences
Chesapeake Biological Laboratory; Claire Buchanan, Interstate Commission on the
Potomac River Basin; Matt Hall, Maryland Department of Natural Resources; Jeni
Keisman United States Geological Survey/Chesapeake Bay Program Office; Mike
Lane, Old Dominion University; Elgin Perry, Statistical Consultant; and Tish
Robertson, Virginia Department of Environmental Quality.
Water Quality Goal Implementation Team
James Davis Martin, Chair, Virginia Department of Environmental Quality; Teresa
Koon, Vice Chair, West Virginia Department of Environmental Protection; Lucinda
Power, Coordinator, U.S. Environmental Protection Agency; David Wood, Staff,
Chesapeake Research Consortium/Chesapeake Bay Program Office; Lindsey Gordon,
Staff, Chesapeake Research Consortium/Chesapeake Bay Program Office; Bill
Angstadt, Delaware Maryland Agribusiness Association; Lee Currey, Maryland
Department of the Environment; Dinorah Dalmasy, Maryland Department of the
Environment; Sarah Diebel, United States Department of Defense; Jim George,
Maryland Department of the Environment; Ann Jennings, Chesapeake Bay
Commission; Veronica Kasi, Pennsylvania Department of Environmental Protection;
Bill Keeling, Virginia Department of Environmental Quality; Sara Latessa, New York
State Department of Environmental Conservation; Jackie Lendrum, New York State
Department of Environmental Conservation; Beth McGee, Chesapeake Bay
Foundation; Hassan Mirsajadi, Delaware Department of Natural Resources and
Environmental Control; George Onyullo, District of Columbia Department of Energy
and the Environment; Ted Tesler, Pennsylvania Department of Environmental
Protection; Marel King, Chesapeake Bay Commission; John Schneider, Delaware
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Department of Natural Resources and Environmental Control; Mary Searing, District
of Columbia Department of Energy and the Environment; Jennifer Sincock U.S.
Environmental Protection Agency; Tanya Spano, Metropolitan Washington Council of
Governments; Chris Thompson, Lancaster County Conservation District; Suzanne
Trevena, U.S. Environmental Protection Agency; Jenn Volk, University of Delaware;
and Kristen Wolf, Pennsylvania Department of Environmental Protection.
Scientific and Technical Advisory Committee
The support and expert advice of all the members of the Chesapeake Bay Program's
Scientific and Technical Advisory Committee, under the leadership of Dr. Lisa
Wainger, University of Maryland Center for Environmental Sciences, and the
Executive Secretarial support of Dr. Bill Ball, Natalie Gardner, and Rachel Dixon,
Chesapeake Research Consortium, are hereby acknowledged. The Scientific and
Technical Advisory Committee convened a panel of independent scientific experts to
provide expert advice and direction on a set of criteria assessment issues and
procedures. The members of the Panel were: Dr. Mary Christman, University of
Florida; Dr. Marjy Friedrichs, Virginia Institute of Marine Science; Dr. Ken Moore,
Virginia Institute of Marine Science; Dr. Malcolm Scully, Woods Hole, Oceanographic
Institute; Dr. Jian Shen, Virginia Institute of Marine Science; and Dr. Steve Weisberg,
Southern California Coastal Water Research Project. The contributions of the
independent scientific peer reviewers—selected and convened by the Chesapeake Bay
Program's Scientific and Technical Advisory Committee based on their recognized
national expertise and drawn from institutions and agencies across the country—are
hereby acknowledged.
Chesapeake Bay Program Partners
Without the efforts of the hundreds of colleagues involved in all aspects of field
collection, laboratory analysis, management, and interpretation of Chesapeake Bay
Monitoring Program data over the past three decades, these enhanced and new criteria
assessment procedures could not have been developed.
The individual and collective contributions from members of U.S. EPA Region 3
Office and U.S. EPA Headquarters Office of Water are acknowledged: Mark Barath,
Christopher Day, Erica Fleisig, Kelly Gable, Jim Keating, Evelyn MacKnight, and Bill
Richardson. The individual and collective contributions from members of the
Chesapeake Bay Program Office are also acknowledged: Howard Weinberg,
University of Maryland Center for Environmental Science/Chesapeake Bay Program
Office, and John Wolf, United States Geological Survey Chesapeake Bay Program
Office.
Supporting analyses and syntheses were contributed by the following partners: Dr. Iris
Anderson, Virginia Institute of Marine Science; Dr. Eva Bailey, University of
Maryland Center for Environmental Sciences Chesapeake Biological Laboratory; Dr.
Donna Bilkovic, Virginia Institute of Marine Science; Dr. Walter Boynton, University
of Maryland Center for Environmental Sciences Chesapeake Biological Laboratory;
Dr. Mark Brush, Virginia Institute of Marine Science; Dr. Claire Buchanan, Interstate
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Commission on the Potomac River Basin; Dr. Amy Drohan, University of Maryland
Center for Environmental Sciences Chesapeake Biological Laboratory; Matt Hall,
Maryland Department of Natural Resources; David Jasinski, Chesapeake
Environmental Communications; Dr. Howard Kator, Virginia Institute of Marine
Science; Mike Lane, Old Dominion University; Marcia Olson; Elgin Perry, Statistics
Consultant; Dr. Tish Robertson, Virginia Department of Environmental Quality; David
Rudders, Chesapeake Research Consortium; and Dr. Lisa Wainger, University of
Maryland Center for Environmental Sciences Chesapeake Biological Laboratory.
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chapter I
Introduction
In April 2003, the U.S. Environmental Protection Agency (EPA) published, on behalf
of its seven jurisdictional partners, the Ambient Water Quality Criteria for Dissolved
Oxygen, Water Clarity and Chlorophyll a for the Chesapeake Bay and Its Tidal
Tributaries which was the foundation document defining Chesapeake Bay water
quality criteria and recommended implementation procedures for monitoring and
assessment (U.S. EPA 2003a). In October 2003, EPA published, on behalf of its seven
jurisdictional partners, the Technical Support Document for Identification of
Chesapeake Bay Designated Uses and Attainability which defined the five tidal water
designated uses to be protected through the published Chesapeake Bay water quality
criteria (U.S. EPA 2003b):
• Migratory fish spawning and nursery habitat;
• Open-water fish and shellfish habitat;
• Deep-water seasonal fish and shellfish habitat
• Deep-channel seasonal refuge habitat; and
• Shallow-water bay grass habitat.
A total of seven addendum documents have been published by EPA since April 2003.
Four addenda were published documenting detailed refinements to the criteria
attainment and assessment procedures (U.S. EPA 2004a, 2007a, 2008, 2010)
previously published in the original April 2003 Chesapeake Bay water quality criteria
document (U.S. EPA 2003a). One addendum published Chesapeake Bay numerical
chlorophyll a criteria (U.S. EPA 2007b). Three addenda addressed detailed issues
involving further delineation of tidal water designated uses (U.S. EPA 2004b, 2005,
2010) building from the original October 2003 tidal water designated uses document
(U.S. EPA 2003b). Finally, one addendum documented the 92-segment Chesapeake
Bay segmentation scheme (U.S. EPA 2008) after refinements to the Chesapeake Bay
Program analytical segmentation schemes were documented (U.S. EPA 2005) building
from the original U.S. EPA 2004 document (U.S. EPA 2004b). This 2017 addendum
is the eight addendum document developed through the Partnership and published by
EPA.
The detailed procedures for assessing attainment of the Chesapeake Bay water quality
criteria continued to be advanced through the collective and collaborative EPA, States
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and District of Columbia partnership efforts. These partners continue to develop and
apply procedures that incorporate the most advanced state-of-the-science magnitude,
duration, return frequency, space and time considerations of, as available, biologically-
based reference conditions and cumulative frequency distributions. As a rule, the best
test of any new method or procedure is putting it to application with full partner
involvement, stakeholder input, and independent scientific review. Through the work
of its Criteria Assessment Protocol Workgroup1, the Chesapeake Bay Program (CBP)
partnership has an established, long-standing forum for resolving issues, factoring in
new scientific findings, and ensuring consistent bay-wide criteria assessment procedure
development and management implementation. The Criteria Assessment Protocol
Workgroup draws upon the talents and input from state, federal, river basin
commission, and academic, as well as regional and local government and municipal
authority partners. This sixth Chesapeake Bay water quality criteria addendum
provides previously undocumented features of the present procedures as well as
refinements and clarifications to the previously published Chesapeake Bay water
quality criteria assessment procedures (U.S. EPA 2004a, 2007a, 2007b, 2008, 2010).
Chapter 2 documents recommendations for assessment of short duration Chesapeake
Bay dissolved oxygen criteria based on a conditional attainment approach or a
combination of sub-segmenting open-water designated use segments in up to three
possible zones and applying the different criteria assessment procedures protective of
each zone and the applicable criterion.
Chapter 3 documents the water column volumes in three Chesapeake Bay segments—
Western Branch Patuxent River Tidal Fresh, Maryland portion of Anacostia Tidal
Fresh, and Patuxent River Tidal Fresh—where the water column volumes had not been
estimated and, therefore, were limiting reporting in Maryland's Clean Water Act 303(d)
listing assessments.
Chapter 4 documents the Partnership development of a multi-metric Chesapeake Bay
water quality indicator using the water quality criteria attainment assessment results for
dissolved oxygen, water clarity/underwater bay grasses and chlorophyll a, to support
public reporting of progress toward achievement of the jurisdictions' Chesapeake Bay
water quality criteria.
Chapter 5 documents an update to the Chesapeake Bay underwater bay grasses
restoration goal and alignment of the goal with the four jurisdictions' Chesapeake Bay
water quality standards' underwater bay grasses restoration acres.
Chapter 6 documents refinements to how the Chesapeake Bay benthic index of biotic
integrity assessment of the aquatic life use should be applied in undertaking water
quality 303(d) listing status supporting aquatic life use assessments.
1 http://www.chesapeakebav.net/groups/group/criteria assessment protocol workgroup
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Appendices to these chapters provide more detailed documentation on development of
the recommended new and refined criteria assessment procedures.
This document represents the sixth addendum to the original 2003 Chesapeake Bay
water quality criteria document. As such readers should regard the sections in this
document as new or replacement chapters and appendices to the original published
Chesapeake Bay water quality criteria report (U.S. 2003a). The criteria assessment
procedures published in this addendum also replace and otherwise supersede similar
criteria assessment procedures published in the 2004, 2007, 2008 and 2010 addenda
(U.S. EPA 2004a, 2007a, 2007b, 2008, 2010). Publication of future addenda by EPA
on behalf of the Chesapeake Bay Program watershed jurisdictional partners is likely as
continued scientific research and management applications reveal new insights and
knowledge that should be incorporated into revisions of state water quality standards
regulations in upcoming triennial reviews.
LITERATURE CITED
U.S. EPA (U.S. Environmental Protection Agency). 2003a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries (Regional Criteria Guidance). April 2003. EPA 903-R-
03-002. Region III Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2003b. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability.
October 2003. EPA 903-R03-004. Region III Chesapeake Bay Program Office,
Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2004a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2004 Addendum. October 2004. EPA 903-R-04-005.
Region III Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2004b. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability -
2004 Addendum. October 2004. EPA 903-R-04-006. Region III Chesapeake Bay
Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2005. Chesapeake Bay Program
Analytical Segmentation Scheme: Revisions, Decisions and Rationales 1983-2003.
2005 Addendum. December 2005. EPA 903-R-05-004. Region III Chesapeake Bay
Program Office, Annapolis, MD.
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U.S. EPA (U.S. Environmental Protection Agency). 2007a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2007 Addendum. July 2007. EPA 903-R-07-003.
Region III Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2007b. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries Chlorophyll a Addendum. October 2007. EPA 903-R-
07-005. Region III Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2008. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2008 Technical Support for Criteria Assessment
Protocols Addendum. September 2008. EPA 903-R-08-001. Region III Chesapeake
Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2010. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2010 Technical Support for Criteria Assessment
Protocols Addendum. May 2010. EPA 903-R-10-002. Region III Chesapeake Bay
Program Office, Annapolis, MD.
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chapter II
Assessing Short-Duration Dissolved
Oxygen Criteria Attainment
BACKGROUND
U.S. EPA has published and Delaware, Maryland, Virginia, and the District of
Columbia (referred to here as the Chesapeake Bay jurisdictions) have adopted into their
respective state's water quality standards regulations, the dissolved oxygen criteria
protective of the published migratory spawning and nursery, open-water, deep-water
and deep-channel designated uses (Table II-l) (U.S. EPA 2010a). These dissolved
oxygen criteria include 30-day, 7-day and 1-day means along with instantaneous
minima as needed to protect the variety of Chesapeake Bay living resource species and
their life stages within each designated use (U.S. EPA 2003a). "Short-duration" as
defined here will refer to a dissolved oxygen criterion with a temporal period of less
than the 30-day mean used to support assessments of the four Chesapeake Bay
jurisdictions' Chesapeake Bay water quality standards.
Enhanced monitoring remains a viable option for filling dissolved oxygen criteria
assessment gaps. Alternatively, estimating probable attainment of a dissolved oxygen
water quality standard at a temporal scale that is not directly monitored has also been
recommended to assess short-duration criteria (p. 179, U.S. EPA 2003a). Such a
conditional attainment approach would address assessment needs where gaps exist for
measuring and reporting on the states' Chesapeake Bay water quality standards
attainment. Practical considerations of the conditional attainment method in the context
of the Chesapeake Bay long term water quality monitoring program sampling design
can limit its use in fulfilling all criteria assessment gaps. Sub-segmenting by habitat
and providing methods and decision-making rules offers further options to provide
sufficient monitoring to assess all applicable temporal scales of the Chesapeake Bay
dissolved oxygen criteria. This chapter provides documentation for recommended
monitoring and assessment procedures to ensure the four Chesapeake Bay jurisdictions
can fully assess all their short-duration Chesapeake Bay dissolved oxygen criteria for
protection of all designated uses adopted into their state's water quality standards
regulations.
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Table 11-1. Chesapeake Bay dissolved oxygen water quality criteria.
Designated
Use
Criteria
Concentration/Duration
Protection Provided
Temporal
Application
Migratory
fish
spawning
and nursery
use
7-day mean > 6 mg/L (tidal
habitats with 0-0.5 salinity)
Survival/growth of larval/juvenile tidal-
fresh resident fish; protective of
threatened/endangered species
February 1-May 31
Instantaneous minimum > 5
mg/L
Survival and growth of larval/juvenile
migratory fish; protective of
threatened/endangered species
Open-water fish and shellfish designated use criteria apply
June 1-January 31
Shallow -
water bay
grass use
Open-water fish and shellfish designated criteria apply
Year-round
Open-water
fish and
shellfish
use1
30-day mean> 5.5 mg/L (tidal
habitats with <0.5 salinity)
Growth of tidal-fresh juvenile and adult
fish; protective of threatened/endangered
species
Year-round
30-day mean > 5 mg/L
(tidal habitats with >0.5
salinity)
Growth of larval, juvenile and adult fish
and shellfish; protective of
threatened/endangered species
7-day mean > 4 mg/L
Survival of open-water fish larvae
Instantaneous minimum >3.2
mg/L
Survival of threatened/endangered
sturgeon species1
Deep-water
seasonal
fish and
shellfish use
30-day mean > 3 mg/L
Survival and recruitment of bay anchovy
eggs and larvae
June 1-September 30
1 -day mean >2.3 mg/L
Survival of open-water juvenile and adult
fish
Instantaneous minimum >1.7
mg/L
Survival of bay anchovy eggs and larvae
Open-water fish and shellfish designated-use criteria apply
October 1 -May 31
Deep
channel
seasonal
refuge use
Instantaneous minimum >_1
mg/L
Survival of bottom-dwelling worms and
clams
June 1-September 30
Open-water fish and shellfish designated use criteria apply
October 1 -May 31
1. When water column temperatures are greater than 29 °C, an open water dissolved oxygen
criterion for the instantaneous minimum of 4.3 mg/L is applied to protect habitat for survival
of shortnose sturgeon.
Source: U.S. EPA 2003a
SEGMENT LEVEL ASSESSMENT
The Chesapeake Bay Program partners have used various forms of a basic
segmentation scheme to organize collection, analysis and presentation of
environmental data for more than three decades. The Chesapeake Bay Program
Segmentation Scheme Revisions, Decisions and Rationales: 1983-2003 (U.S. EPA
2004b) provides documentation on the development and evolution of the spatial
segmentation scheme of the Chesapeake Bay and its tidal tributaries. For the purpose
of water quality attainment assessment, the four tidal water Chesapeake Bay Program
partner jurisdications have coordinated with U.S. EPA to create subsegement
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assessment units. The following guidance first describes criteria attainment
assessment options at the full segment scale, then support for options to address the
segment scale assessment through sub-segment assessments.
DIRECT ASSESSMENT WITH ENHANCED MONITORING
The four Chesapeake Bay jurisdictions always have the option of collecting water
column profiles of dissolved oxygen concentration at high enough frequencies to
support direct assessments of each dissolved oxygen criterion's temporal period—7-
day mean, 1-day mean, and instantaneous minimum—at spatial resolutions
characteristic of the segment of focus. The high frequency data can be collected using
any one or an assortment of methods—e.g., depth transect of water quality sensors,
greater manual measurement density in space and or time with water quality sensors,
water quality profilers, Underwater Autonomous Vehicles, etc. The jurisdiction would
evaluate the high resolution data against the suite of water quality criteria using the
published CFD-based Chesapeake Bay water quality criteria attainment assessment
methods (U.S. EPA 2003a, 2004a, 2007, 2008, 2010a) (see Table II-6).
ASSESSING CONDITIONAL ATTAINMENT ACROSS
DISSOLVED OXYGEN CRITERIA
Conditional attainment refers to using the mathematical relationship between results of
computing one statistic from a set of dissolved oxygen concentration measurements
collected to support water quality standards attainment assessments at a specific
temporal scale (e.g., 30-day mean) to evaluate dissolved oxygen criteria attainment at
another temporal scale (e.g., 7-day mean, 1-day mean, instantaneous minimum). The
Chesapeake Bay long term, fixed station tidal water quality monitoring program
directly supports 30-day mean dissolved oxygen assessments, however, the monitoring
program has thus far been considered insufficient on its own to assess short-duration
dissolved oxygen criteria (U.S. EPA 2003a, CBP STAC 2012).
For example, the open-water designated use has a set of summer season dissolved
oxygen criteria that includes a 30-day mean, 7-day mean and instantaneous minimum
that must be met simultaneously for a Chesapeake Bay segment to be considered in
attainment under the Clean Water Act 303(d) impairment assessments. However, the
Chesapeake Bay long term water quality monitoring program measures habitat
conditions biweekly which thus far only supports dissolved oxygen standards
assessment for the 30-day mean portion of the three applicable criteria (see Table II-
1).
The concept of conditional attainment as an assessment approach uses the idea of an
umbrella-like dissolved oxygen criterion effect to support multiple criteria assessments
simultaneously. This concept is borrowed from conservation biology's use of umbrella
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species, first used by Wilcox (1984) and with additional applications over recent
decades (Launer and Murphy 1994, Roberge and Per Angelstam 2004). Some scientists
have found that accounting for an umbrella effect provides a simpler way to manage
ecological communities, for example, considering multi-species protections based on
the presence of one umbrella species in a habitat (e.g., Dunk et al. 2006). In this case,
meeting a stated dissolved oxygen threshold from one scale of measurement is meant
to provide levels of habitat protection for one or more other, shorter duration, dissolved
oxygen habitat protection criteria.
The value of applying a conditional attainment assessment method for addressing water
quality standards attainment of Chesapeake Bay dissolved oxygen criteria within a
designated use is: 1) multiple duration criteria are addressed; 2) attainment of criteria
of different durations must be met simultaneously; and 3) not all scales of criteria are
being directly measured through the present Chesapeake Bay long term water quality
monitoring program.
Demonstrating Conditional Dissolved Oxygen Attainment
Through the recent efforts of the Chesapeake Bay Program Scientific, Technical
Assessment and Reporting Team's Criteria Assessment Protocol Workgroup, the
Chesapeake Bay Program partnership explored the relationship between 30-day mean
dissolved oxygen measurements and 7-day mean, 1-day mean and instantaneous
minimum measurements in the same 30-day period. The Partnership's analysts used
Chesapeake Bay-specific, geographically diverse, high temporal density water quality
data sets that covered tidal fresh to polyhaline salinities and mainstem Chesapeake Bay
as well as tidal tributary and embayment habitats (Appendix A, B, C). Further similar
analyses have been conducted using the Chesapeake Bay Program's Water Quality
Sediment Transport Model (U.S. EPA 2010b). By evaluating water quality
relationships for mutual and simultaneous habitat protection across different temporal
application scales of the Chesapeake Bay dissolved oxygen criteria, the scientific and
management communities have developed a foundation of understanding regarding
habitat protections between measured criteria (e.g., 30-day mean) averaging periods
and unassessed, shorter duration temporal scales of dissolved oxygen criteria
attainment (e.g., 7-day mean, 1 day mean and instantaneous minimum).
Historical Evidence Demonstrating Conditional Attainment
Previously, Jordan et al. (1992) developed regression equations to derive the seasonal
mean concentrations that could be presumed protective of target, shorter-duration
assessment dissolved oxygen thresholds in a given Chesapeake Bay segment. They
concluded that knowing the seasonal mean dissolved oxygen concentration for a given
region in the Bay permitted "a good estimate of what proportion of actual dissolved
oxygen observations are likely to meet, or fail to meet, each of the target dissolved
oxygen concentrations". Further, in 2004, CBP analysts explored mutual protection
among the new 2003 Chesapeake Bay dissolved oxygen criteria with different
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9
durations (U.S. EPA 2003a). Olson et al. (cited in U.S. EPA 2004a) primarily used 147
buoy-based, high temporal frequency dissolved oxygen data sets collected
betweenl987-1995 (where dates were noted) from the EPA's Environmental
Monitoring and Assessment Program. The data sets are geographically diverse in their
collections, represent tidal fresh to polyhaline habitats, and have measurements from
the mainstem Chesapeake Bay as well as tidal tributaries and embayments (Table V-2
in U.S. EPA 2004a). They documented that: 1) the open-water 30-day mean dissolved
oxygen criterion attainment was generally protective of the open-water 7-day mean
dissolved oxygen criterion and instantaneous minimum in those segments where both
criteria applied; and 2) the deep-water 30-day mean dissolved oxygen criterion
attainment was generally protective of the 1-day mean and instantaneous minimum
dissolved oxygen criteria.
Similarly, mutual protection between one measured dissolved oxygen criterion and a
second dissolved oxygen criterion of a different duration was tested in the course of
developing the 2010 Chesapeake Bay Total Maximum Daily Loads (TMDL). Analysts
at the Chesapeake Bay Program Office conducted an assessment of how well dissolved
oxygen criteria that are already measured with the current Chesapeake Bay Program
partnership's long term water quality monitoring program mutually protected the
attainment of unmeasured, short-duration dissolved oxygen criteria (U.S. EPA 2010b,
2010c).
Using hourly output from a calibration run of the Partnership's Chesapeake Bay Water
Quality Sediment Transport Model, the Chesapeake Bay Program Office analysts
produced a summer season test of the "umbrella criterion". Note that for the purposes
of developing the 2010 Chesapeake Bay TMDL, the summer season (June 1 -
September 30) was assumed to be the limiting season in all designated uses being
assessed for dissolved oxygen impairments (i.e., open-water, deep-water and deep-
channel). Chesapeake Bay Program Office analysts determined that evaluation of
attainment of the open-water and deep-water 30-day mean dissolved oxygen criteria
was sufficient to determine attainment of the remaining open-water and deep-water
designated uses dissolved oxygen criteria (U.S. EPA 2010b, 2010c).
Furthermore, in segments containing a summer deep-channel designated use (8 of the
92 tidal water segments in Chesapeake Bay), non-attainment rates of the summer
instantaneous minimum dissolved oxygen criterion protective of the deep-channel
designated use were higher than for any other open-water and deep-water designated
use criteria for the same segment. Thus, the three dissolved oxygen criteria currently
being assessed using the Chesapeake Bay long term water quality monitoring program
data—open-water 30-day mean, deep-water 30-day mean and deep-channel
instantaneous minimum—appear to be "umbrella criteria". That is, these criteria are
the most restrictive of all available criteria mutually protective of the full range of
criteria by designated use (U.S. EPA 2010b, 2010c). These findings provided additional
support for using an approach of estimating conditional attainment to address water
quality standards attainment decisions for unmeasured criteria. However, further
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10
evidence of the suitability of the approach was requested by Chesapeake Bay Program
partners before adopting this criteria attainment procedure into the Bay jurisdictions'
water quality standards regulations.
Recent Evidence Demonstrating Conditional Attainment
Perry (cited in CBP STAC 2012) conducted a study on conditional dissolved oxygen
water quality standards attainment across different scales of dissolved oxygen criteria
when measuring one scale, the 30-day mean. Perry notes that in order for the summer
open-water 30-day mean dissolved oxygen criterion to serve as a conditional criteria
attainment measure for the 7-day mean dissolved oxygen criterion, there was the need
to show that if the 30-day mean dissolved oxygen criterion was satisfied, there was a
small probability that the 7-day mean dissolved oxygen criterion was going to be
violated. Using 'less than 10 percent' as an acceptable risk of wrongly concluding that
the 7-day mean dissolved oxygen criterion is satisfied when it is in fact violated, then
this condition of mutual attainment is satisfied when the standard deviation for the
distribution of the differences between the weekly mean from the monthly mean is
0.7805 or smaller. At this level of variability in the weekly deviations from the monthly
mean, excursions of the weekly mean below the 7-day mean dissolved oxygen criterion
of 4.0 mg/L while the monthly mean is at the 30-day mean dissolved oxygen criterion
of 5.0 mg/L would be about 10 percent (Figure II-l). This scenario would be strong
evidence that the 30-day mean criterion is mutually protective of habitat with the 7-day
mean dissolved oxygen criterion of 4.0 mg/L.
CD
CO
CD
CD
o °
o
a- ,*¦
CD
Csl
CD
O
CD
Figure 11-1. Illustration of the 30-day mean criterion serving to simultaneously protect the 7-day mean
criterion when the standard deviation of the differences between the monthly mean and weekly mean is
0.7805 or less.
Using tidal Potomac River continuous monitoring data for monitoring stations located
across all salinity zones and the summer seasons from 2004-2009, the standard
deviation of the differences between the weekly mean from the monthly mean exceeds
this ideal 0.7805 value and was estimated to be 1.005 or very close to 1.0. At this level
10%
3
4
5
6
7
DO
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11
of variability, the risk of violating the 7-day criterion when the 30-day criterion is
satisfied exactly is about 16 percent (Figure II-2, blue dashed line). However,
increasing the monthly mean dissolved oxygen concentration to 5.285 mg/L again
brings the risk of violations of the 7-day mean dissolved oxygen criterion to an
acceptable level of 10 percent (Figure II-2, blue solid line). Perry also completed a
complementary study of conditional attainment using depth specific data from offshore
continuous monitoring sites in the Chesapeake Bay that had a range of dissolved
oxygen means (Appendix A). The violations rates were computed and produced
comparable results to Perry's previously cited analysis (i.e., CBP STAC 2012).
Because it is unlikely that under the natural conditions of the Chesapeake Bay and its
tidal tributaries and embayments, the monthly mean will hover in this narrow window
of dissolved oxygen concentrations (5.0 to 5.285 mg/L) for an extended time then it
seems reasonable to consider that the 7-day criterion is satisfied if the 30-day mean
dissolved oxygen criterion is satisfied. This evidence is one key supporting fact for the
CBP Scientific, Technical Assessment and Reporting Team's Umbrella Criteria
Assessment Team conclusion that the 30-day mean dissolved oxygen criterion is
mutually protective for the 7-day mean dissolved oxygen criterion. It is important to
recognize that this conclusion depends on both the true monthly mean and the true
weekly mean are being estimated with great precision. The high level of precision is
obtained here by using a near continuous record of dissolved oxygen concentrations
(i.e., data collected at 15 minute intervals through the Chesapeake Bay Program's
Shallow-water Water Quality Monitoring Program).
o
in
cc
c\
LT
CO
o
to
o
c
^r
o
CsJ
o
o
o
2
3
4
5
6
7
8
DO
Figure 11-2. Illustration of the change in the distributions from an ideal (black line) to account for natural
dissolved oxygen dynamics in the Bay (dashed blue line) and subsequent shift in the monthly mean
required to meet 10% risk tolerance for the 7-day mean criterion when the weekly mean deviation is 1.005
(solid blue line).
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12
By contrast, the Chesapeake Bay Program long term fixed station water quality
monitoring program collects dissolved oxygen profiles through the water column one
to two times a month which serves as the basis for assessing attainment of the 30-day
mean dissolved oxygen water quality standard. When the 30-day mean dissolved
oxygen concentration is estimated by a sample size of two observations then the
variability of the deviations between the 30-day mean dissolved oxygen estimate and
the 7-day dissolved oxygen means increases by 60 to 90 percent (Figure II-3). At this
higher level of variability, satisfying the 30-day criterion exactly results in a 28 percent
risk of violating the 7-day criterion (Figure II-3, red dashed line). Estimates of the 30-
day mean have to exceed a threshold of 6.22 to insure that the risk of violating the 7-
day mean criterion is 10 percent or less (Figure II-3, red solid line).
o
CnJ
CM
CD
CO
O
CD
O
TJ
r^-
o
CM
O
O
d
1 i i i i i r
2 3 4 5 6 7 8
DO
Figure 11-3. Illustration of the shift—from red dashed line to red solid line—in the monthly mean required
to meet 10% risk tolerance for the 7-day criterion when the weekly mean deviation of 1.74 accounting for
the uncertainty in estimating the mean due to small sample sizes (n=2).
The direct application of the conditional probability analysis approach used above was
not suitable for understanding protection of the 30-day mean for an instantaneous
minimum criterion. Perry (cited in CBP STAC 2012) used parametric simulation of
dissolved oxygen dynamics to generate time series that have properties similar to
observed Chesapeake Bay dissolved oxygen concentration time series. Autoregressive
(AR) modeling is a parametric simulation tool that has been used to describe certain
time-varying processes in nature. Perry (cited in CBP STAC 2012) used a specific case
of autoregressive models, an AR(2) model, for simulating Chesapeake Bay dissolved
oxygen dynamics. The data used for this exercise are the open-water buoy data from
the U.S. EPA Environmental Mapping and Assessment Program as compiled by Olson
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13
(cited in U.S. EPA 2004a). Details of the autoregressive modeling approach are
provided in Appendix A.
Results of the autoregressive analysis demonstrate protection levels for meeting a 30-
day mean dissolved oxygen concentration and mutually protecting the summer open-
water instantaneous minimum criterion are presented in Table II-2. Whereas we
previously saw achievable thresholds in protection of the 7-day mean dissolved oxygen
criterion using 30-day means derived from high and low frequency monitoring data in
Chesapeake Bay, applying the conditional criteria attainment approach for protecting
the instantaneous minimum by the 30-day mean with less than a 10 percent risk of non-
attainment could not be achieved with a 30-day mean even as high as 7.01 mg/L. An
alternative level of acceptable risk greater than 10 percent would need to be considered
acceptable for declaring attainment in order for the conditional attainment procedures
to apply to the instantaneous minimum criterion (e.g., approximately 25% if meeting a
30-day mean threshold of 6.3 based on Table II-2).
The selection of an appropriate level of acceptable risk is a decision to be made by
individual jurisdictions with consultation with EPA. If the selection of an appropriate
level of acceptable risk yields a dissolved oxygen concentration which can't be
routinely achieved, then direct measurement or other assessment methods are
recommended for evaluating attainment of the instantaneous minimum dissolved
oxygen criteria.
Table 11-2. Parametric simulation results for a gradient of dissolved oxygen mean data and their ability
to mutually protect the summer, open-water instantaneous minimum dissolved oxygen criteria.
Summer Season, Open-water 30-day Mean Dissolved Oxygen (mg/L)
Rate of instantaneous
criterion >10 percent
5.0058
5.6732
6.3407
7.0082
47.6%
32.5%
25.3%
18.5%
Source: CBP STAC 2012
Example of Conditional Attainment Assessment
An example of the relevance of this range of 30-day mean dissolved oxygen
concentrations documented in Table II-2 was developed. Table II-3 below illustrates
the application of the conditional attainment assessment for the 2011-2013 Chesapeake
Bay open-water summer season designated use dissolved oxygen assessment. First, 40
of 92 Chesapeake Bay segments attained the summer open-water designated use for
dissolved oxygen under the 30-day mean criterion of 5.0 mg/L. This is based on the
standard CFD attainment assessment (U.S. EPA 2003a, 2010a).
Next, for the sake of illustration, we want to apply the conditional attainment approach
and show segments that simultaneously meet the 30-day mean dissolved oxygen
criterion and the 7-day mean dissolved oxygen mean criterion without having the
temporal density of measurements to support direct water quality standards attainment
assessment of the 7-day mean dissolved oxygen criterion. Such segments would be
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14
considered as passing both criteria under the rules of conditional attainment. For
demonstration purposes in this example, we assume the required dissolved oxygen
concentration threshold to achieve simultaneous protection is 6.1 mg/L.2
Table 11-3. Conditional attainment assessment approach applied using two threshold values to show
mutual protection for the 30-day and 7-day mean open-water dissolved oxygen criteria.
Segments attaining the 30-day
mean dissolved oxygen criterion.
Segments that further pass
attainment of the 7-day
mean dissolved oxygen
criterion using a 6.1 mg/L
30-day mean dissolved
oxygen threshold1.
Segments that
also pass the 7-
day mean
dissolved oxygen
criterion using a
6.5 mg/L 30-day
mean dissolved
oxygen
threshold.
CB1TF, CB3MH, CB4MH, CB5MH,
CB8PH, CHSMH, EASMH, JMSMH,
JMSPH, JMSTFU, MPNTF, PIAMH,
PMKTF, POCMH, MPCMH, VPCMH,
POTMH, POTMH MD, POTOH VA,
POTTF, POTTF DC, POTTF MD,
TAMMH, APPTF, BIGMH, BOHOH,
C&DOH, CHKOH, ELKOH, FSBMH,
MANMH, CB5MH MD, MIDOH,
NANMH, NORTF, PISTF, SASOH,
SEVMH, SOUMH, CB5MH VA
POCMH, POCMH MD,
POCMH VAPOCOH VA,
APPTF, BIGMH, FSBMH,
MANMH
None
l.The subset of segments that further pass attainment of the 30-day mean dissolved oxygen criterion
using 6.1 mg/L dissolved oxygen threshold for assessing mutual protection of the 7-day mean
dissolved oxygen criterion (less 10 percent risk of nonattaimnent) based on 2 samples each month,
June-September 2011-2013.
The results of the dissolved oxygen assessment are re-run through the same CFD
attainment assessment. However, the protocol requires using the 6.1 mg/L threshold in
place of the 5.0 mg/L threshold for assessing simultaneous protection of the 7-day
dissolved oxygen mean based on the 30-day dissolved oxygen mean. The assessment
of passing or failing are now interpreted as evidence for meeting the 7-day dissolved
oxygen mean and the 30-day dissolved oxygen mean while accounting for uncertainty
due to the CBP water quality monitoring program's sampling design.
In this illustration, 8 of the 40 segments that met the 30-day mean 5.0 mg/L summer
mean open-water dissolved oxygen criterion also meet an example dissolved oxygen
threshold of 6.1 mg/L, providing protection of the open-water designated use under the
7-day dissolved oxygen mean criterion considering the uncertainty of measuring the
30-day dissolved oxygen mean from two days each month (Table II-3). These 8
2. This value would have a 10 percent risk of nonattaimnent if the standard deviation is 1.61. The
proposed threshold value of 6.22 mg/L was shown in Figure II-3 has a similar standard deviation of
1.74. See Appendix A for the associated reference table.
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15
segments, which met the 6.1 mg/L threshold supported by a 10 percent level of
acceptable risk decision-rule, can be effectively stated as also in attainment for the 7-
day mean dissolved oxygen mean criterion.
It is noteworthy that 11 more of the Chesapeake Bay segments were less than 1 percent
from demonstrating mutual protection of the 30-day and 7-day mean criteria when
applying the 6.1 mg/L threshold and requiring no more than a 10 percent level of risk
to be considered protective for the 7-day dissolved oxygen mean criterion: CB1TF,
CB3MH, CB5MH, PIAMH, POTTFDC, GUNOH, CB5MH MD, NORTF, SASOH,
SOUMH, and CB5MH VA (Table II-3). Due to the uncertainty of estimating the 30-
day mean from 2 samples per month under the natural variability exhibited by dissolved
oxygen in Chesapeake Bay, these 11 segments would be prime targets for enhanced
monitoring to demonstrate that the 7-day mean dissolved oxygen criterion is being
protected by the 30-day mean water quality criterion for dissolved oxygen.
Protecting other short duration criteria may require using more stringent dissolved
oxygen thresholds. Under more stringent mutual protection decision rules, e.g. if a 30-
day mean must now meet a threshold of 6.5 mg/L, then in this illustration no segments
demonstrate sufficient water quality to show the 30-day mean can mutually protect any
short-duration dissolved oxygen criteria that requires a 30-day mean at or above 6.5
mg/L (Table II-3). Three Eastern Shore Maryland segments are, however, less than 1
percent from meeting the 6.5 mg/L threshold (NORTF, FSBMH, and BIGMH). This
finding provides an important perspective when considering the instantaneous
minimum dissolved oxygen criteria that needs a 30-day mean dissolved oxygen
assessment well above 7.01 mg/L in order to be in attainment.
Therefore, conditional attainment assessment provides a viable method of assessment.
However, the robustness of the technique to discriminate mutual criteria attainment or
impairment for measured and unmeasured criteria at different time scales is sensitive
to the uncertainty in sampling effort underlying the estimate of a 30-day mean. Under
the existing sampling effort of the Partnership's long term Chesapeake Bay water
quality monitoring program, this uncertainty generates decision thresholds that appear
to be unattainable measures of dissolved oxygen concentrations (Table II-2). Yet, this
does not mean the instantaneous minimum criterion is unattainable. Rather, this issue
highlights the practical limits of applying this method of attainment in the context of
accounting for the uncertainty of small sample size on estimating the 30-day mean and
trying to make an effective decision about habitat protection at another time scale.
Further, alternative sampling densities and alternative acceptable risk levels of non-
attainment need to be considered to address assessment of the instantaneous minimum
criterion.
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16
Application of Conditional Criteria Attainment Assessment
Application of conditional dissolved oxygen criteria attainment assessment is
supported by the above documented relationships between assessed and unassessed
dissolved oxygen criteria. However, there are key findings that must be considered
when applying conditional dissolved oxygen attainment assessments.
Temporal sampling density must be accounted for in order to use conditional dissolved
oxygen attainment assessments. Perry's (cited within CBP STAC 2012) conditional
probability assessment of summer season dissolved oxygen criteria showed that
attaining a 30-day mean dissolved oxygen concentration of 5.3 mg/L can
simultaneously protect open-water habitat by ensuring the 7-day mean dissolved
oxygen concentrations will remain above 4 mg/L while allowing for less than 10
percent non-attainment. This result depends on high temporal density dissolved oxygen
data (collected every 15 minutes throughout a summer season). By contrast, Perry's
(cited within CBP STAC 2012) parametric simulation evaluated the same relationship
between 30-day mean and 7-day mean dissolved oxygen when using the Chesapeake
Bay long term water quality monitoring program sampling design of 2-samples per
month. Due to the uncertainty introduced by variability in dissolved oxygen
concentrations coincident with evaluating the means with a low sample density, a 30-
day mean dissolved oxygen must now be at least 6.1 mg/L in order to allow for a less
than 10 percent non-attainment. Therefore, the temporal scale of assessment is an
essential element of effectively applying the conditional dissolved oxygen attainment
assessment methodology.
For a 30-day mean dissolved oxygen criteria attainment assessment using near
continuous high frequency (e.g., every 15 minutes) time series monitoring data for
assessing the habitat protection of the summer season open water 7-day dissolved
oxygen mean criterion, the 30-day mean dissolved oxygen must be equal to or greater
than 5.3 mg/L, allowing for no more than 10 percent non-attainment. By contrast, when
using the Chesapeake Bay long-term water quality monitoring program sampling
design of 2-samples per month, a 30-day mean dissolved oxygen must now achieve a
threshold of at least 6.22 mg/L in order to allow for a less than 10 percent non-
attainment to protect the habitat with the 7-day mean dissolved oxygen criterion (Figure
II-3). However, for deep-water designated use habitat which has different criteria
thresholds than the open-water designated use habitat, Olson et al. (cited in U.S. EPA
2004a) determined a direct assessment of the 30-day mean attainment effectively
evaluates protection for the 1-day mean and instantaneous minimum dissolved oxygen
criteria.
The risk of non-attainment for a short duration criterion relative to a 30-day mean
dissolved oxygen concentration varies according to the criterion being protected.
Conditional attainment assessment provides a method to assess any short-duration
criteria, however, the required 30-day mean dissolved oxygen concentration to achieve
mutual habitat protection over a short duration criterion may be impractically high if
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17
temporal sampling density of the existing Chesapeake Bay long term water quality
monitoring program is used and a low level of acceptable risk of nonattainment is
selected. There are two options available to account for this finding: 1) sample more
frequently to better account for dissolved oxygen variability; or 2) define a different
level of acceptable risk of nonattainment.
This criteria assessment approach is based on the existing Chesapeake Bay Program
partnership's long-term Chesapeake Bay and Tidal Tributaries Water Quality
Monitoring Program sampling strategy. Jurisdictions would define and apply an
acceptable risk (e.g., 10 percent) for decisions supporting attainment associated with
meeting one or more shorter duration dissolved oxygen criteria in a designated use
when using the single 30-day mean threshold dissolved oxygen concentration and
criterion assessment under existing, published criteria assessment procedures (U.S.
EPA 2003a, 2004a, 2007, 2008, 2010a). The conditional criterion attainment approach
can be used by jurisdictions to assess their open-water 7-day mean dissolved oxygen
criterion. In deep-water designated use segments, assessment of the 30-day mean
dissolved oxygen criterion directly serves to protect the 1-day mean and the
instantaneous minimum dissolved oxygen criteria (see Recommended Methods for
Assessing Short Duration Dissolved Oxygen Criteria Attainment, this chapter).
Additional monitoring and research can be used to develop segment- and designated
use-specific relationships to be applied in a conditional attainment assessment approach
to assessing Chesapeake Bay dissolved oxygen water quality standards.
FRAMING THE ASSESSMENT OF OPEN-WATER SHORT DURATION
DISSOLVED OXYGEN CRITERIA
Assessing the full array of open-water short duration dissolved oxygen criteria builds
on the recognition that even within an individual open-water designated use segment,
there are different habitat zones which have different dissolved oxygen dynamics and
characteristics—e.g., diurnal cycles in dissolved oxygen concentrations in shallow
water habitats vs. relatively constant dissolved oxygen concentrations over extended
periods of times in open, more well-mixed habitats. By matching up assessment
procedures with the characteristic dissolved oxygen dynamics and the life stages often
present in these zones, the different sub-segments of an overall open-water designated
use segment may be assessed using different assessment procedures while at the same
time still ensuring full protection of the open-water designated use.
Rationale for Sub-segmenting Open-Water Designated Use Segments
into Zones
The Chesapeake Bay Program partners have used various forms of a basic segmentation
scheme to organize collection, analysis and presentation of environmental data for
more than three decades. The Chesapeake Bay Program Segmentation Scheme
Revisions, Decisions and Rationales: 1983-2003 (U.S. EPA 2004b) provides
documentation on the development and evolution of the spatial segmentation scheme
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18
of the Chesapeake Bay and its tidal tributaries. Segmentation has been used to
compartmentalize the estuary into subunits based on selected criteria for setting
boundaries and grouping regions having similar natural characteristics, so that
differences in water quality and biological communities among similar segments can
be identified and the source of their impacts elucidated (U.S. EPA 2004b).
Segmentation also serves management purposes as a way to group regions to define a
range of water quality and resource objectives, target specific actions, and then monitor
the response.
As documented in detail in Appendix B, there is a strong scientific rationale for further
sub-segmenting the existing Chesapeake Bay segments from a water quality criteria
assessment perspective. Sub-segments have been previously created for state-specific
Chesapeake Bay water quality standards applications (U.S. EPA 2004c, 2007a). The
U.S. EPA (2003b) 305(b) guidance similarly highlights the Washington State
Department of Ecology's 3-zone approach to water quality assessment in estuarine
habitats. In this EPA national guidance, estuarine habitats are divided to define
monitoring site representativeness by open-water, sheltered bays and highly sheltered
bays. Virginia Department of Environmental Quality already cites the U.S. EPA
(2003b) 305(b) guidance to support the same sub-segmentation for these three habitats
for their existing non-Chesapeake Bay Program tidal and estuarine monitoring station
location considerations (VADEQ 2014).
This 3-zone approach is further supported by Caffrey (2004) and Boynton et al. (2014)
findings that nearshore monitoring sites with greater exposure to mainstem tidal bay
and mainstem tidal tributary habitats show better water quality conditions than
nearshore sites with more restricted exposures. Boynton et al. (2014) also pointed to
"tributaries of tributaries" having greater violation rates on average than monitoring
stations located in the nearshore zone of the mainstem of a tributary. Both the tributary
of tributary sites and the nearshore zones of tidal tributaries had greater violation rates
than monitoring sites exposed to the open waters of the mainstem Chesapeake Bay
(Boynton et al. 2014).
Acknowledging that there is a scientific basis showing habitat differences exist in open-
water habitats (Appendix A) (Boynton et al. 2014), and EPA and state policies and
procedures are already in place that support sub-segmentation of habitats to account for
habitat differences (U.S. EPA 2003b, U.S. EPA 2004c, U.S. EPA 2007, VADEQ
2014), a jurisdiction may specifically delineate sub-segments within an individual
Chesapeake Bay segment's open-water designated use for purposes of dissolved
oxygen criteria attainment assessment.
Three Zones within the Open-Water Designated Use
The existing published Chesapeake Bay designated uses call for two zones—open,
well-mixed waters and shallow-water waters (U.S. EPA 2003a, 2003c). Boynton et al.
2014 provide a solid rationale for adding a third zone—tributaries of tributaries.
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19
Applying the concept of three zones to Chesapeake Bay open-water habitats yields the
following physically delineated three zones illustrated in Figure II-4 and described
below along with the underlying rationale for each zone.
Zone 1
Open, well-mixed Chesapeake Bay mainstem and tidal tributary waters: open, well-
mixed tidal waters above the pycnocline located within the mainstem Chesapeake Bay,
its tidal tributaries, and embayments.
Rationale: These well-mixed tidal waterbodies are represented by the 92 Chesapeake
Bay segments delineated and refined over the past 30+ years of the Chesapeake Bay
Program partnership (U.S. EPA 2004b, 2005a).
Zone 2
Shallow-water waters: waters generally equal to or less than 2 meters in depth1.
Rationale: Shallow-waters are well recognized and documented as a distinct
designated use habitat supporting underwater bay grasses and having unique water
quality conditions compared with other tidal habitats (Dennison et al. 1993, Kemp et
al. 2004, U.S. EPA 2003a, 2003c).
Zone 3
Tributaries of tributaries off of the mainstem Chesapeake Bay and its tidal tributaries
and embayments: waters with weak hydrodynamic links to open waters of the mainstem
bay and mainstem of tidal tributaries. These waters are considered poorly mixed.
Rationale: Boynton et al. (2014) provided in-depth analyses which provided for clear
delineation of tidal water bodies which were well removed and isolated from more
open, well-mixed tidal waters and, therefore, displayed different water quality
conditions.
The actual scale and specific delineations of these three zones will be determined on a
case-by-case basis through consultation between the individual Chesapeake Bay
jurisdictions and EPA, consistent with past published Chesapeake Bay criteria
guidance (U.S. EPA 2007a).
1. On May 15, 2014, the CBP Scientific and Technical Assessment and Reporting Team's Criteria
Assessment Protocol Work Group reached a consensus decision that, while the shallow-water bay
grass designated use may have a 2 meter contour boundary, for the purpose of dissolved oxygen
attaimnent assessments, there is not a single depth contour that would be applied baywide at this
time to define shallow water. Final decisions on sub-segment boundaries would be determined on
a segment-specific basis, as necessary, based on consultations between each of the four the
Chesapeake Bay jurisdictions and EPA.
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20
Zam2
Shallow Water
/ Zone 3
Tributaries of
Tributaries
Zone I
Offshore Open
WaSerEg.
Mairtstem Bay
Figure 11-4. Applying the concept of three zones to Chesapeake Bay open-water habitats.
CRITERIA ASSESSMENT PROCEDURES TAILORED TOWARDS THE
THREE ZONES
Given the option for creating the delineation of the three zones based on their unique
dissolved oxygen dynamics and mixing characteristics, distinct sets of criteria
assessment procedures can be aligned with each zone (Table II-4). When these criteria
assessment procedures are applied to each respective zone, the result is the ability to
assess all applicable open-water dissolved oxygen criteria throughout each open-water
designated use segment. By meeting the instantaneous minimum dissolved oxygen
criterion in the sub-segment zones 2 and 3, the defacto decision is that the entire open-
water designated use segment meets the instantaneous minimum criterion and is,
therefore, in attainment with this criterion.
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21
Table 11-4. Applicable criteria assessment procedures for each of the three zones within the open-water
designated use.
Zone
Zone Description
Applicable Criteria Assessment
Procedures
1
Open, well-mixed
mainstem
Bay and tidal tributary
waters
• CFD-based assessment of the 30-day mean
• CFD-based assessment of the 7-day mean
with enhanced temporal frequency of
monitoring
• Conditional attainment assessment of the 7-
day mean
• Continuous monitoring-based assessment
of the instantaneous minimum
2
Shallow-water waters
• Continuous monitoring-based assessment
of the instantaneous minimum
3
Tributaries of tributaries
off of the mainstem
Chesapeake Bay and its
tidal tributaries
• Discrete sampling-based assessment of the
instantaneous minimum
Continuous Monitoring-Based Assessment
Continuous monitoring data sensors are in use evaluating shallow-water habitat
conditions throughout the summer season in Chesapeake Bay (U.S. EPA 2010b).
Continuous monitoring data are not currently used in dissolved oxygen criteria
attainment assessments as standard practice (U.S. EPA 2010a). The technological and
statistical challenge of mixing nearshore high frequency data with low frequency
offshore data over multiple depths for an open-water dissolved oxygen criteria
attainment assessment has been overcome. However, the results remain subject to the
uncertainty imposed by the lowest common denominator in the monitoring data, the
estimate of a monthly mean at the long term water quality monitoring stations using no
more than 2 samples per month. The opportunity to sub-segment out and separately
assess attainment in the nearshore habitats where the continuous monitoring sensors
are routinely monitoring presents the ability to now assess attainment of the open-water
instantaneous minimum dissolved oxygen criterion directly with high frequency
dissolved oxygen data.
Published state-specific methods for assessing attainment of dissolved oxygen criteria
using continuous monitoring data are highly varied:
Virginia - "10%-10% rule": a water body is impaired if exceedances were
observed more than 10% of the time within more than 10% of the 24-hour periods
monitored (VADEQ 2016).
Wisconsin - "10% rule": a water body is impaired if exceedances were more than
10% of the time (WDNR 2015).
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22
Louisiana - "25% rule": a water body is impaired if violations were observed more
than 25% of the time (LDEQ 2016).
Washington - "3 daily minimum values rule": a water body is impaired if at least
3 daily minimum values are below the instantaneous minimum (WDE 2012).
New Jersey - "2 daily minimum values rule": a water body is impaired if at least
2 daily minimum values are below the instantaneous minimum (NJDEP 2015).
Though these five states' methods differ, almost all rest on the assumption that monitors
will be deployed primarily for short durations (30 days or less). Further, EPA
recommends making determinations of impairment for conventional pollutants "when
more than 10% of measurements exceed the water quality criterion" (U. S. EPA 2005b).
Though not stated explicitly, this recommendation assumes assessments are based on
low-frequency discrete monitoring datasets, not continuous monitoring.
Based on the above published state methods and EPA guidance, the CBP Scientific,
Technical Assessment and Reporting Team's Criteria Assessment Protocol Workgroup
worked with U.S. EPA Region III Office staff to develop options for assessing
attainment of season-long, high frequency data (e.g., every 15 minutes) for criterion
assessment that protects the designated use. The Criteria Assessment Protocol
Workgroup then considered three options for instantaneous minimum criterion
assessment that account for concerns of living resource protection over an entire season
at a conservative level.
Rule 1. No more than 10 percent of days during a single season with an exceedance—
9 total of 12 days can have a single exceedance. This translates into about 30 minutes
x 12 or 5 hours total per season, and given 2880 hours in a summer season, about 0.17
percent of the summer season.
Rule 2. No more than 1 day with 10 percent time (>2.5 hours) exceedance during a
single season. This translates into 3 or more hours or about 0.1 percent of the summer
season.
Rule 2-Alternate. No more than two consecutive days with 10 percent time (>2.5 hours)
exceedance during a single season. This translates into 6 or more hours or about 0.2
percent of the summer season.
In a test of applying all three rules to assess impairment in multiple segments, all three
rules performed similarly well (Table II-5). Therefore, based on the assumption that
the instantaneous minimum criterion is interpreted as a discrete 1 hour average
condition (i.e., for Chesapeake Bay jurisdictions, the computations start at midnight
and there are 24 discrete hourly calculations for each day. This approach is contrasted
with the option that may be applied elsewhere (e.g. recommendations for assessment
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23
in Delaware, tidal Murderkill River, Hydroqual 2014) of using a rolling 1-hour average
that would be calculated every 15 minutes to produce 96 hourly results for the
instantaneous minimum criterion assessment each day) not to be exceeded (U.S. EPA
2008), rule 1 is the least consistent with this assumption by allowing 12 days to
experience criterion exceedance. Rules 2 and 2-Alternate more closely approach the
interpretation for protecting against an instantaneous minimum violation for a season.
Given it is the best option for addressing the need for separating out a random event
from a more persistent event, Rule 2-Alternate is recommended for use by the
jurisdictions in assessing attainment of instantaneous minimum criteria using
continuous monitoring data.
In utilizing the wealth of continuous monitoring data they have collected through the
Partnership's Chesapeake Bay Shallow-water Monitoring Program, the jurisdictions
can use this approach to directly assess attainment of their open-water instantaneous
minimum criterion within their sub-segmented shallow-water habitats. Attainment
would be based on the rule allowing no more than two consecutive days with a 10
percent time (greater than 2.5 hours) exceedance during a single season (see Table II-
6) using data from at least 2 stations in the zone.
Table 11-5. Testing of the three potential rules for assessing instantaneous minimum criterion assessment
using continuous monitoring dissolved oxygen data.
Segment
Year
Rule 1
Rule 2
Rule 2 (Alt)*
JMSMH
2006
Pass
Fail
Pass
2007
Pass
Pass
Pass
2008
Pass
Fail
Fail
2006-2008
Pass
Fail
Fail
JMSMH
2012
Pass
Pass
Pass
2013
Pass
Pass
Pass
2014
Pass
Pass
Pass
2012-2014
Pass
Pass
Pass
JMSPH
2006
Pass
Fail
Pass
2007
Pass
Pass
Pass
2008
Pass
Pass
Pass
2006-2008
Pass
Fail
Pass
LAFMH
2012
Fail
Fail
Fail
2013
Pass
Pass
Pass
2014
Pass
Pass
Pass
2012-2014
Fail
Fail
Fail
LAFMH
2012
Fail
Fail
Fail
2013
Fail
Fail
Fail
2012-2013
Fail
Fail
Fail
Source: Tish Robertson, Virginia Department of Environmental Quality and Will Hunley, Hampton Roads
Sanitation District, Virginia.
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24
Discrete Monitoring-based Assessment
Building from the programmatic experience of Virginia Department of Environmental
Quality, for those 'tributary of a tributary' habitats that fall under the zone 3 definition
(see Table II-4) (VADEQ 2014), the recommended procedure for use in assessing
instantaneous criteria attainment is using a discrete monitoring approach to collect data
from the waterbody. Specifically, the discrete monitoring approach is based on using
sensors at one or more locations in the delineated sub-segment with a minimum of 10
samples per year collected over 3 years. At least 50 percent of the samples must be
collected before 9 AM to address diel variability in dissolved oxygen concentrations.
Dissolved oxygen criteria attainment is based on 10 percent allowable exceedance of
the applicable instantaneous minimum criterion.
For those waterbodies for which sub-segmenting them for their own criteria assessment
makes sense due to their isolated nature (see Zone 3 in Table II-4), taking a discrete
sampling approach which relies on additional sampling beyond that accomplished by
the existing Chesapeake Bay Program Partnership's long term water quality monitoring
program is the best choice. The specifications of the discrete sampling need to be robust
enough to provide confidence in the attainment assessment of that sub-segment yet not
resource intensive enough to prevent its routine application.
RECOMMENDED METHODS FOR ASSESSING SHORT-DURATION
DISSOLVED OXYGEN CRITERIA ATTAINMENT
The methods described above and summarized in Table II-6, when adopted directly or
by reference into the four Chesapeake Bay jurisdictions' water quality standards
regulations, should be used to assess short duration dissolved oxygen criteria across all
designated uses. In combination with the criteria assessment methods previously
approved by the Partnership and published by EPA (U.S. EPA 2003a, 2004a, 2007,
2008, 2010a), these combined sets of dissolved oxygen criteria assessment methods
provide the four Chesapeake Bay jurisdictions with the ability to make water quality
standards attainment and impaired waters listing and delisting decisions for all 92
Chesapeake Bay segments and for all five designated uses based on assessments of all
applicable criteria protecting those designated uses.
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25
Table 11-6. Recommended methods for assessing attainment of the short duration Chesapeake Bay
dissolved oxygen criteria.
Designated
Use
Assessment Scale
Assessment Method
Criteria
Supporting
Documentation
All
Designated
Uses
Segment
Direct Assessment with
Enhanced Monitoring
Collecting data beyond the existing
fixed station monitoring network
using vertical water quality
profilers, autonomous underwater
vehicles, citizen science, etc.
All
U.S. EPA 2003a,
U.S. EPA 2004a,
this document
Conditional Attainment with
Monitoring Data
Meet the longest duration mean
dissolved oxygen threshold
associated with a defined level of
acceptable risk of nonattainment
of the short duration dissolved
oxygen criterion/criteria
Open-water
Designated
Use
Full segment
assessed with
shoreline to
shoreline
Application
Segment
Conditional Attainment with
Bimonthly Monitoring Data
Meet the 30-day mean dissolved
oxygen threshold associated with
a defined level of acceptable risk
of nonattainment of the 7-day
mean dissolved oxygen criterion
7-day mean
U.S. EPA 2003a,
U.S. EPA 2004a,
CBP STAC 2012,
this document
Meet the 30-day mean dissolved
oxygen threshold associated with
a defined level of acceptable risk
of nonattainment for the
instantaneous minimum criterion
Instantaneous
minimum
Sub-segment
approach
application
Zone 1:
Open, well-
mixed waters
Zone 2 and Zone 3
Attainment Decision Rule
If sub-segments Zone 2 and Zone
3 pass, then the Zone 1 sub-
segment is deemed passing and
the entire segment is considered in
attainment for the instantaneous
minimum criterion
Instantaneous
minimum
This document
Conditional Attainment
Meet the 30-day mean dissolved
oxygen threshold associated with
a a defined level of acceptable
risk of nonattainment of the 7-day
mean dissolved oxygen criterion
7-day mean,
Instantaneous
minimum
U.S. EPA 2003a,
U.S. EPA 2004a,
CBP STAC 2012,
this document
Zone 2:
Shallow-water
waters
Continuous Monitoring
15 minute interval data collected
over the entire summer season
with no more than two consecutive
days with 10% time exceedance
Instantaneous
minimum
This document
Zone 3:
Isolated
Waters
Discrete Sampling
10 sample events per year
collected over 3 years assessed
based on 10% allowable
exceedance
Instantaneous
minimum
This document
Deep-water
Designated
Use
Segment
Conditional Attainment with
Bimonthly Data.
Meeting the deep water 30-day
mean criterion ensures attainment
of the short duration criteria
1-day mean,
Instantaneous
minimum
U.S. EPA 2004a
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26
LITERATURE CITED
Boynton, W.R., J.M. Testa, C.L.S. Hodgkins, J.L. Humphrey, and M.A.C. Ceballos.
2014. Maryland Chesapeake Bay Water Quality Monitoring Program. Ecosystem
Processes Component. Level one Report No. 31. Interpretive Report. August 2014.
Tech. Report Series No. TS-665-14 of the University of Maryland Center for
Environmental Science. UMCES-CBL 2014-051.
Caffrey, J.M. 2004. Factors controlling net metabolism in U.S. estuaries. Estuaries
27(1):90-101.
CBP STAC (Chesapeake Bay Program Scientific and Technical Advisory Committee).
2012. Evaluating the Validity of the Umbrella Criterion Concept for Chesapeake Bay
Tidal Water Quality Assessment. Findings of the Umbrella Criterion Action Team,
Tidal Monitoring and Analysis Workgroup. August 2012, STAC Publication. 12-02.
Dennison, W. C., R.J. Orth, K.A. Moore, J.C. Stevenson, V. Carter, S. Roller, P.W.
Bergstrom, and R.A. Batiuk. 1993. Assessing water quality with submersed aquatic
vegetation. Bioscience. 143:86-94.
Dunk, J.R., W.J. Zielinski and H.H. Welsh. 2006. Evaluating reserves for species
richness and representation in northern California. Diversity and Distributions 12,
434-442.
Hydroqual. 2014. Tidal Murderkill River site-specific dissolved oxygen criteria. Report
to the Delaware Department of Natural Resources and Environmental Control. 73pp.
Jordan, J., C. Stenger, M. Olson, R. Batiuk, andK. Mountford. 1992. Chesapeake Bay
dissolved oxygen goal for restoration of living resource habitats. CBP/TRS 88/93.
Chesapeake Bay Program, Annapolis, MD.
Kemp, W.M., R.A. Batiuk, R. Bartleson, P. Bergstrom, V. Carter, C.L. Gallegos, W.
Hunley, L. Karrh, E. Koch, J.M. Landwehr, K.A. Moore, L. Murray, M. Naylor, N.B.
Rybicki, J.C. Stevenson, and D.J. Wilcox. 2004. Habitat requirements for submerged
aquatic vegetation in Chesapeake Bay: Water quality, light regime and physical-
chemical factors. Estuaries 27(3):363-377.
Launer, A. and D. Murphy. 1994. Umbrella species and the conservation of habitat
fragments: a case of a threatened butterfly and a vanishing grassland ecosystem.
Biological Conservation, 69 (2): 145-153.
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27
LDEQ (Louisiana Department of Environmental Quality). 2015. Louisiana's 2016
Integrated Report and Section 303(d) List Methods and Rationale. Baton Rouge,
LA. February 2016.
NJDEP (New Jersey Department of Environmental Protection). 2015. Draft 2016
New Jersey Integrated Water Quality Assessment Methods. Trenton, NJ. December
2015.
Roberge, J. and P. Angelstam. 2004. Usefulness of the umbrella species concept as a
conservation tool. Conservation Biology, 18 (1): 76-85
U.S. EPA (U.S. Environmental Protection Agency). 2003a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries. EPA 903-R-03-002. U.S. Environmental Protection
Agency, Region 3, Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2003b. Guidance for 2004 Listing
and Reporting Requirements Pursuant to Sections 303(d) and 305(b) of the Clean
Water Act, July 21, 2003. U.S. Environmental Protection Agency Office of Water,
Office of Wetlands, Oceans and Watersheds, Assessment and Watershed Protection
Division, Watershed Branch, Washington D.C.
U.S. EPA (U.S. Environmental Protection Agency). 2003c. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability.
October 2003. EPA 903-R03-004. Region III Chesapeake Bay Program Office,
Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2004a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries. 2004 Addendum. EPA 903-R-03-002. U.S.
Environmental Protection Agency, Region III, Chesapeake Bay Program Office,
Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2004b. Chesapeake Bay Program
Analytical Segmentation Scheme: Revisions, Decisions and Rationales 1983-2003.
EPA 903-R-04-008. CBP/TRS 268/04. U.S. Environmental Protection Agency, Region
III, Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2004c. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability -
2004 Addendum. EPA 903-R-04-006. U.S. Environmental Protection Agency, Region
III, Chesapeake Bay Program Office, Annapolis, MD.
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28
U.S. EPA (U.S. Environmental Protection Agency). 2005a. Chesapeake Bay Program
Analytical Segmentation Scheme: Revisions, Decisions and Rationales 1983-2003.
2005 Addendum. December 2005. Region III Chesapeake Bay Program Office,
Annapolis, MD. EPA 903-R-05-004.
U.S. EPA (U.S. Environmental Protection Agency). 2005b. Guidance for 2006
Assessment, Listing and Reporting Requirements Pursuant to Sections 303(d), 305(b)
and 314 of the Clean Water Act. U.S. Environmental Protection Agency, Office of
Water, Office of Watershed, Oceans, and Wetlands, Assessment and Watershed
Protection Division, Washington, DC.
U.S. EPA (U.S. Environmental Protection Agency). 2007. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries—2007 Addendum. EPA 903-R-07-003. CBP/TRS 285-
07. U.S. Environmental Protection Agency, Region III, Chesapeake Bay Program
Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2008. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2008 Technical Support for Criteria Assessment
Protocols Addendum. September 2008. EPA 903-R-08-001. Region III Chesapeake
Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2010a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2010 Technical Support for Criteria Assessment
Protocols Addendum. May 2010. EPA 903-R-10-002. Region III Chesapeake Bay
Program Office, Annapolis, MD.
U. S. Environmental Protection Agency. 2010b. Chesapeake Bay Total Maximum Daily
Load for Nitrogen, Phosphorus and Sediment. U. S. Environmental Protection Agency,
Region 3 Chesapeake Bay Program Office, Annapolis, MD.
U. S. Environmental Protection Agency. 2010c. Chesapeake Bay Total Maximum Daily
Load for Nitrogen, Phosphorus and Sediment - Technical Appendices. U.S.
Environmental Protection Agency, Region 3 Chesapeake Bay Program Office,
Annapolis, MD.
VADEQ (Virginia Department of Environmental Quality). 2014. Water Quality
Assessment Guidance Manual for 2014 305(b) 303(d) Integrated Water Quality
Report. April 2014, Richmond, VA.
VADEQ (Virginia Department of Environmental Quality). 2016. Water Quality
Assessment Manual for 2016 303(d)/305(b) Integrated Water Quality
Report. Guidance Memo No. 16-2005. June 2016. Richmond, VA.
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29
WDE (Washington Department of Ecology). 2012. Water Quality Program Policy:
Assessment of Water Quality for the Clean Water Act Section 303(d) and 305(b)
Integrated Report. July 2012. Olympia, WA.
Wilcox, B. 1984. In situ conservation of genetic resources: determinants of minimum
area requirements. In: National Parks, Conservation and Development, Proceedings of
the World Congress on National Parks. J. A. McNeely and K.R. Miller, Smithsonian
Institution Press, pp. 18-30.
WDNR (Wisconsin Department of Natural Resources). 2015. Wisconsin 2016
Consolidated Assessment and Listing Methodology (WisCALM) for CWA Section
303(d) and 305(b) Integrated Reporting. Guidance #3200-2015-01. March 2015.
Madison, WI.
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¦ ¦ ¦
chapter III
Accounting for Missing Volumes in the
Chesapeake Bay Program Segmentation to
Support Clean Water Act 303(d) Listing
Assessments
BACKGROUND
Criteria attainment assessments for the applicable designated use-based dissolved
oxygen criteria are assessed on the basis of how much of the total volume of the
segment's designated use habitat achieved the criterion values over what time period
(U.S. EPA 2003, 2008, 2010a). Quantifying the water column volume of each of the
92 Chesapeake Bay segments is required for conducting water quality criteria
attainment assessments using the Partnership's Chesapeake Bay interpolator. However,
three segments have not previously been assigned water volumes despite the fact that
long-term water quality monitoring stations are present and active within each segment.
These three segments are the Western Branch Patuxent River Tidal Fresh (WBRTF),
the Anacostia Tidal Fresh Maryland (ANATF MD), and the Patuxent River Tidal Fresh
(PAXTF). The location of these segments is illustrated in Figure III-1. In this chapter,
water volumes are assigned and the basis for decisions on the volume assignments are
provided in Appendix D.
For more than 30 years, the Chesapeake Bay Program partners have used various forms
of a basic segmentation scheme to organize the collection, analysis and presentation of
environmental data (U.S. EPA 2004). Segmentation is the compartmentalizing of the
estuary into subunits based on selected criteria. For diagnosing anthropogenic impacts,
segmentation is a way to group regions having similar natural characteristics so that
differences in biological communities among similar segments can be identified and
their sources elucidated. For management purposes, segmentation is a way to group
similar regions to define a range of water quality and resource objectives, target specific
actions and monitor ecosystem responses. It provides a meaningful way to summarize
and present information in parallel with these objectives and it is a useful geographic
pointer for data management.
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31
The Chesapeake Bay Program Analytical Segmentation Scheme: Revisions, Decisions
and Rationales 1983-2003 (U.S. EPA 2004) provides documentation on the
development of the spatial segmentation scheme and their associated water volumes
for Chesapeake Bay and its tidal tributaries and embayments. Subsequently, a U.S.
Figure 11-1. The location of three segments that previously lacked volume estimates needed to assess
their Chesapeake Bay water quality standards attainment: Western Branch Patuxent tidal Fresh
(WBRTF). Patuxent River tidal fresh (PAXTF) and Anacostia River tidal fresh in Maryland (ANATF_IVID).
EPA (2005) addendum to U.S. EPA (2004) updated the segmentation scheme. Finally,
Chapter 2 in U.S. EPA (2008) reviews the 1985, 1997, and 2003 segmentation schemes
for Chesapeake Bay and documents the present (i.e., 2008) 92-segment scheme that
was the foundation segmentation for the 2010 Chesapeake Bay Total Maximum Daily
Load (TMDL) (U.S. EPA 2010b).
Washinaton
.ANATFMD
WBRTF
PAXTF
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32
WBRTF SEGMENT VOLUME
The Western Branch Patuxent River Tidal Fresh (WBRTF) has been a segment within
the Chesapeake Bay analytical segmentation schemes published in the years 1997/8,
2003 and 2008 (U.S. EPA 2004, 2008). In the past, no volume estimate was available
for WBRTF (see Table 1 in U.S. EPA 2004) due to an absence of bathymetry data.
However, recently the Chesapeake Bay Program Scientific, Technical Assessment and
Reporting Team's Criteria Assessments Protocol Workgroup and Tidal Monitoring
Analysis Workgroup coordinated with EPA and Maryland Department of the
Environment (MDE) staff to establish a volume for WBRTF of 111,567 cubic meters
(m3) (Appendix D). Water volumes and the data used to determine the volume
assignment are provided in Appendix D and E.
ANATF MD AND PAXTF SEGMENT VOLUMES
Insufficient bathymetry data have prevented development of volume estimates for the
Anacostia River Tidal Fresh Maryland (ANATF MD) and Patuxent River Tidal Fresh
(PAXTF) segments. As interim volume estimates to allow for calculations of water
quality standards attainment assessments using the Chesapeake Bay Interpolator, the
CBP Criteria Assessments Protocol Workgroup worked with MDE to reach agreement
on using interim segment volumes as they are expressed in the Partnership's
Chesapeake Bay Water Quality Sediment Transport Model (U.S. EPA 2010b)
(Appendix D) used to support the 2017 mid-point assessment of the Chesapeake Bay
TMDL:
• PAXTF segment model-based volume is 11,025,000 m3; and
• ANATF MD model-based volume estimate is 172,500 m3.
These interim volume estimates will continue to be used until the time at which more
detailed field measurements of the bathymetry of both segments becomes available.
LITERATURE CITED
U.S. EPA (U.S. Environmental Protection Agency). 2003. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries. EPA 903-R-03-002. U.S. Environmental Protection
Agency, Region III, Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2004. Chesapeake Bay Program
Analytical Segmentation Scheme: Revisions, Decisions and Rationales 1983-2003.
October 2004. Region III Chesapeake Bay Program Office, Annapolis, MD. EPA 903-
R-04-008.
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33
U.S. EPA (U.S. Environmental Protection Agency). 2005. Chesapeake Bay Program
Analytical Segmentation Scheme: Revisions, Decisions and Rationales 1983-2003.
2005 Addendum. December 2005. Region III Chesapeake Bay Program Office,
Annapolis, MD. EPA 903-R-05004.
U.S. EPA (U.S. Environmental Protection Agency). 2008. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries: 2008 Technical Support for Criteria Assessment
Protocols Addendum. EPA 903R-08-001. Region III Chesapeake Bay Program Office,
Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2010a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2010 Technical Support for Criteria Assessment
Protocols Addendum. May 2010. EPA 903-R-10-002. Region III Chesapeake Bay
Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2010b. Chesapeake Bay Total
Maximum Daily Load for Nitrogen, Phosphorus and Sediment - Technical Appendices.
U.S. Environmental Protection Agency, Region 3 Chesapeake Bay Program Office,
Annapolis, MD.
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¦
chapter IV
Development of a Multi-metric Chesapeake
Bay Water Quality Indicator for Tracking
Progress toward Chesapeake Bay Water
Quality Standards Achievement
BACKGROUND
For decades, the Chesapeake Bay Program partnership has separately tracked and
reported on dissolved oxygen, water clarity/underwater bay grasses and chlorophyll a
indicators to chronicle changes in Chesapeake Bay ecosystem health. However, all of
these individual CBP reporting indicator assessments were not precisely aligned with
their respective water quality standards attainment assessment methods. Therefore, in
order to track the composite of water quality standards attainment for the 92
Chesapeake Bay segments in the 2010 Chesapeake Bay TMDL (U.S. EPA 2010b), a
new indicator was needed. This new indicator needed to be a combined, multi-metric
indicator measuring progress toward meeting the complete set of Chesapeake Bay
water quality standards, based on the water quality standards attainment results, and
applied to all designated uses adopted by Delaware, District of Columbia, Maryland
and Virginia into their respective water quality standards. This chapter documents this
water quality standards based multi-metric Chesapeake Bay water quality indicator
used for tracking progress in response to nutrient and sediment load reduction actions
taken across the Chesapeake Bay watershed and airshed.
In order to achieve and maintain the water quality conditions necessary to protect the
aquatic living resources of the Chesapeake Bay and its tidal tributaries, the EPA has
developed and published guidance in Ambient Water Quality Criteria for Dissolved
Oxygen, Water Clarity and Chlorophyll a for the Chesapeake Bay and Its Tidal
Tributaries (Regional Criteria Guidance) (U.S. EPA. 2003a) and subsequent
supporting documentation (U.S. EPA 2003b, 2004a, 2004b, 2005, 2007a, 2007b, 2008,
2010a). The documentation presents EPA's recommended regionally-based nutrient
and sediment enrichment criteria expressed as dissolved oxygen, water
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35
clarity/underwater grasses and chlorophyll a criteria applicable to the Chesapeake Bay,
its tidal tributaries and embayments.
Quantified water quality criteria contained within water quality standards are essential
to a water quality-based approach to pollution control providing a reference for the
measuring, tracking and reporting of progress towards attaining the standards. The
original 2003 Regional Criteria Guidance and subsequently published supporting
documentation has provided Delaware, Maryland, Virginia and the District of
Columbia with recommendations for establishing water quality standards consistent
with Section 303(c) of the Clean Water Act. These four jurisdictions have subsequently
adopted into their water quality standards regulations a set of scientifically defensible
water quality criteria that are protective of designated and existing uses for Chesapeake
Bay and its tidal tributaries (U.S. EPA 2010b). The four tidal water jurisdictional
partners and EPA continue to work collaboratively to assess water quality standards
attainment based on the criteria applicable to the five Chesapeake Bay designated uses
(Figure IV-1).
Refined Designated Uses for
the Bay and Tidal Tributary Waters
A. Cross Section of Chesapeake Bay or Tidal Tributary
Use
B. Oblique View of the "Chesapeake Bay" and its Tidal Tributaries
Use
Figure IV-1. Conceptual illustration of the five Chesapeake Bay tidal water designated use zones.
Source: U.S. EPA 2003b
Shallow-Water
Bay Grass Use
Deep-Water
Seasonal Fish and
Shellfish Use
Open-Water
Fish and Shellfish
Deep-Channel
Seasonal Refuge Use
Migratory
Open-Water
Habitat
Deep-Channel
Fish
Spawning and
Nursery Use
Shallow-Water
Bay Grass Use
Deep-Water
Seasonal Fish and
Shellfish Use
Seasonal Refuge
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36
The Presidential Chesapeake Bay Executive Order 13508 and supporting strategy
published in 2010 supported a water quality outcome based on Chesapeake Bay water
quality standards attainment:
"Meet water quality standards for dissolved oxygen, clarity/underwater
grasses and chlorophyll a in the Bay and tidal tributaries by meeting
100 percent of pollution control reduction actions for nitrogen,
phosphorus and sediment no later than 2025, with 60 percent of
segments attaining water quality standards by 2025".
This chapter provides a brief overview of the attainment assessment method, the
hierarchy of attainment measures providing context on bay-wide attainment, segment
attainment, designated use attainment and criterion attainment, and the structure and
calculation of the multi-metric indicator including the rules that support indicator
computation.
CRITERIA ATTAINMENT ASSESSMENT METHODOLOGIES
Attainment for dissolved oxygen and chlorophyll a criteria is computed by using water
quality monitoring data collected from the Chesapeake Bay Program partnership
Chesapeake Bay Mainstem and Tidal Tributary Water Quality Monitoring Programs'
fixed station network or through DATAFLOW data collections in the Partnership's
Shallow-Water Water Quality Monitoring Program during a 3-year assessment period
and applying the cumulative frequency distribution (CFD) criteria attainment
assessment methodology (Table IV-1) (U.S.EPA 2003a, 2004a, 2007a, 2007b, 2008,
2010a). Attainment for water clarity/underwater bay grasses criteria is calculated as the
single best year of underwater bay grass acres coverage in the 3-year assessment period
to compare with segment specific goal acreages or as water clarity goal acres, or as the
published measures that combine the two measures to compare against the water clarity
goal acres (U.S. EPA 2003a, 2004a, 2007a, 2008, 2010a).
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37
Table IV-1. Chesapeake Bay dissolved oxygen, water clarity/underwater bay grasses and chlorophyll a
criteria assessment methodologies.
Dissolved Oxygen
The published dissolved oxygen criteria assessment methodology used for assessing
Chesapeake Bay water quality standards attainment involves the comparison of two
cumulative frequency distribution (CFD) curves—one based on a healthy habitat and
one based on monitoring data collecting during the 3-year assessment period—in a
two dimensional space of percent time and percent space to determine compliance
with standards. The procedure for assessing dissolved oxygen criteria attainment is
described in detail in Appendix A of Ambient Water Quality Criteria for Dissolved
Oxygen, Water Clarity and Chlorophyll a for the Chesapeake Bay and Its Tidal
Tributaries 2008 Technical Support for Criteria Assessment Protocols Addendum.
Water Clarity
Attainment of the water clarity/underwater bay grasses criteria may be computed
through one of three methods: measured underwater grass bed acres compared with
the segment's restoration goal acreage; water clarity acres; or a combination of the
two measures. The methodologies are described in Appendix E of Ambient Water
Quality Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the
Chesapeake Bay and Its Tidal Tributaries 2008 Technical Support for Criteria
Assessment Protocols Addendum.
Chlorophyll a
EPA provided states guidance for the assessment of chlorophyll a criteria through the
publication of Ambient Water Quality Criteria for Dissolved Oxygen, Water Clarity
and Chlorophyll a for the Chesapeake Bay and Its Tidal Tributaries: 2007
Chlorophyll Criteria Addendum. The published chlorophyll a criteria assessment
methodology currently used for assessing Chesapeake Bay chlorophyll a criteria
attainment involves the comparison of two CFD curves—one based on a healthy
habitat and one based on monitoring data collecting during the 3-year assessment
period—in a two dimensional space of percent time and percent space to determine
compliance with standards.
Sources: U.S. EPA 2007b, 2008.
FOUR LEVELS OF WATER QUALITY ATTAINMENT ASSESSMENT
Chesapeake Bay water quality criteria attainment is assessed at four levels (Figure IV-
2):
1. Criterion level, each individual criterion applicable to the protection of a specific
designated use;
2. Designated-use level, the combined set of criteria applicable to the protection of a
specific designated use;
3. Chesapeake Bay segment level the combined set of applicable designated uses
within an individual Chesapeake Bay segments; and
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38
4. Chesapeake Bay-wide level, the combined set of all 92 Chesapeake Bay segments
that cover all the tidal waters of the Chesapeake Bay mainstem, its tidal tributaries,
and embayments.
Water Quality Standards Attainment Assessment for Chesapeake Bay Dissolved Oxvaen. Water Clarity and Chlorophyll a
Chesapeake Bay-
Chesapeake
Tidal Water
Criteria
Assessment
Criteria Duration
wide Attainment
Bay Segments
Designated Uses
Season
Bay
Attainment
— Segment
— Segment
I
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— Segment -
—Segment
I
Segment
Segment
Migratory
Open Water
Deep Water
— Deep Channel
¦ Shallow water
Bay grasses
-P
Lchla^-QSpnng
June-Jan
Yearround
Summer
June-Sept
Oct-May
June-Sept
Oct-May
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- 7-day mean
• Instantaneous minimum
7-day mean
instantaneous minimum
'TFypSlO TFto=15 OH=15 MH=12 PH=12
.TF^IS TFte=23 OH=22 MH=10 PH=10; DC= 25
30 day mean
1-day mean
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TF= 30 day mean; OH-PH 30 day mean
7-day mean
Instantaneous m
instantaneous minimum
TF= 30 day mean; OH-PH 30 day mean
7-day mean
Instantaneous m
J" uu
L Water
Clarity/SAV
Dependent upon Open Water attainment
SAV season-
" Segment-specific water clarity/bay grasses acreage goals.
1. There are 92 Chesapeake Bay segments (USEPA 2008)
2. Designated uses are segment specific. Not all designated uses apply to each Chesapeake Bay segment
3. Salinity zone-specific thresholds on the James River, VA: TFup=Tidal Fresh upper segment, TF|0=Tidal Fresh lower segment, OH=Oligohaline, MH=Mesohaline,
PH=Polyhaline. DC= Washington District of Columbia.
4. The James River chlorophyll a criteria are assessed for attainment of a geometric mean measure of the water quality.
Figure IV-2. The relationships between Chesapeake Bay segments, designated uses, applicable water
quality criteria, assessment seasons and criteria durations.
Criterion Assessment Level
At the criterion level of assessment, each dissolved oxygen, water clarity/underwater
bay grasses or chlorophyll a criterion is assessed for attainment for protection of a
specific designated use within an individual segment (Figure IV-2). Dissolved oxygen
criteria apply at the summer (June-September), the rest of the year (October-May), or
the migratory spawning and nursery (February 15-May 31) seasons. Chlorophyll a
criteria apply in the tidal James River mainstem's open-water designated uses during
separate spring (March-May) and summer (July-September) seasons. In the District of
Columbia's tidal waters, the District's chlorophyll a criterion applies to all open-water
segments only during the summer season (July-September).
Designated Use Assessment Level
At the designated use assessment level, all criteria applicable to a specific designated
use must be determined to be in attainment in order for a segment's designated use to
be considered in attainment. Each segment can have as few as one and as many as five
applicable designated uses. Within each applicable designated uses for a segment, all
the applicable criteria for protection of that use must attain all their respective dissolved
oxygen, water clarity/underwater bay grasses or chlorophyll a criteria. A criterion may
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39
have a season-specific threshold in its application and some criteria may only apply to
specific salinity zones. All those season-specific and salinity zone-specific criteria
must also be achieved.
Chesapeake Bay Segment Assessment Level
At the Chesapeake Bay segment assessment level, for an individual Chesapeake Bay
segment to be in attainment, all criteria for all applicable designated uses must be
attained.
Chesapeake Bay-wide Assessment Level
Producing a Chesapeake Bay-wide water quality standards attainment assessment is
based on combining all the criteria attainment results from all 92 Chesapeake Bay
segments and all their applicable designated uses (Figure IV-3). There are 289
segment*designated use combinations (see Table 3-3 in U.S. EPA 2010b).
STRUCTURE OF THE MULTI-METRIC WATER QUALITY
STANDARDS INDICATOR
The Multi-metric Water Quality Standards Indicator (Indicator) reports on the
proportion of segment*designated use*criterion class combinations that meet all
applicable season-specific thresholds for each 3-year assessment period (Figure IV-3,
Table IV-2). Criterion class represents the water quality standard parameters as either
dissolved oxygen, water clarity/underwater bay grasses or chlorophyll a. Further, each
of the 92 Chesapeake Bay segments has been assigned its own unique surface area (see
Table F-l in Appendix F). Recognize that in addition, each designated use within each
segment has been assigned its own unique surface area. The segments and their
designated uses also have unique volumes. However, because there are wide disparities
in size and volume of designated uses and segments, the Indicator avoided using a
simple proportion of the number of criterion class*designated use-segments achieving
attainment and dividing it by 289 criterion class*designated use*segment combinations
for its tracking metric. While dissolved oxygen is evaluated for its volume-based
attainment, water clarity/underwater bay grasses and chlorophyll a water quality
standards attainment are assessed on a surface area basis. Since dissolved oxygen
attainment could be expressed based on a surface area as well, segment surface area, as
opposed to volume, was chosen as the common weighting factor. Recognizing the
open-water designated uses' surface area is considered constant when measured at
mean low water, but deep-water and deep-channel designated use surface areas vary in
size depending on the water column conditions observed during each monitoring
cruise, the open water surface area of each respective segment was therefore applied as
a constant multiplier for all criterion class*designated use combinations in the indicator
calculation.
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Table IV-2. For the 289 Designated Use*criterion class*Segment combinations (contained within the
92 Chesapeake Bay segments), the Segment areas are summed1.
Chesapeake Bay Tidal Water Designated Use*Criterion class.
Total Surface
Area of
Designated-Use
Segments (km2)
Migratory Fish Spawning and Nursery*Dissolved oxygen
5565101169.36
Open Water*Dissolved oxygen
11660174083.95
Open Water*CHLA = Open*CHLA(springVirgmia j„m« River only) + Open
Water*CHLA (SUlTimervirginia James River + Washington DC waters)
620327627.29
Deep Water*Dissolved oxygen
6932558324.18
Deep Channel*
4404190644.45
Shallow-Water Bay Grasses/Water Clarity
11558645485.84
Total area of the Segment*Designated Use*Criterion Class
combinations used in the indicator calculations
40740997335.07
1. The sum of the areas by designated use*criterion class is equal to the total area constant used in
the Indicator calculations.
The surface area of each segment multiplied by the number of applicable designated
uses in each segment provides a common denominator for the indicator assessment.
The indicator is, therefore, the sum of the products for the number of designated uses
in attainment with all applicable criteria multiplied by their respective segment surface
area across all 92 segments divided by the sum of the products for each segment-
surface-area*number of designated uses applicable in the segment across all 92
segments. The resulting measure is multiplied by 100 to provide a percentage.
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41
Chesapeake Bay 303(d) List Segments
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Figure IV-3. A map of the 92 Chesapeake Bay segments assessed in the Multi-metric Water Quality
Standards Indicator analysis.
Source: USEPA 2008a
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MWQS Indicator =
Step 1) Using the Chesapeake Bay Program Partnerships' water quality monitoring
results for a three year water quality standards assessment period for each segment, if
the criterion class condition is met for the applicable designated use in an assessment
period (i.e., the assessment result passes for water quality standards attainment), add
the surface area - expressed in kilometers2 (km2) - to create a sum of designated
use*criterion class area of attainment
• see Appendix F for segments and their applicable designated use*criterion
classes. There are 289 segment*(designated use*criterion class) combinations
for evaluation.
• see Rules for Computing the Indicator in this chapter for the Indicator
assessment process and results that equal attainment for each designated
use*criterion class
Step 2) Divide the sum of segment*designated use*criterion class from step 1 by the
sum of all available segment*designated use criterion class area (see Table IV-2. This
sum is a constant that equals 40740997335.07 km2)
Step 3) Multiply the quotient by 100 to express the result as a percent of water quality
standards goal attained
RULES FOR COMPUTING THE INDICATOR
The Indicator was derived as an indexed accounting mechanism that estimates the sum
of dissolved oxygen, water clarity/underwater bay grasses and chlorophyll a water
quality standards attainment in Chesapeake Bay and its tidal tributaries. Outputs of the
Indicator are used for tracking and publically reporting progress towards delisting all
impaired segments of Chesapeake Bay and its tidal tributaries. The full set of rules for
computing the Indicator is documented below. These rules apply strictly to computing
the Indicator, not to assessing criteria attainment for making listing and delisting
decisions.
Rule 1. Critical season is summer. Based on the best available science, the first rule
was directed at having a critical season. The summer season was considered the
limiting season for the 2010 Chesapeake Bay TMDL with respect to achieving water
quality standards (U.S. EPA 2010b). Therefore, the first rule was directed at dissolved
oxygen criteria attainment such that if a segment met its summer season criteria, it was
considered to meet all its applicable criteria for the year and, therefore, attain all the
criteria protective of all applicable dissolved oxygen designated uses strictly for the
purposes of computing this indicator (Figure IV-4).
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43
Rule 2. Meet the applicable 30-day mean dissolved oxygen criteria and all short
duration criteria are also considered attained. Until Delaware, the District of
Columbia, Maryland and Virginia's existing Chesapeake Bay water quality standards
regulations are revised to reflect the assessment procedures for the full array of
applicable dissolved oxygen criteria described in Chapter 2 of this document, strictly
for the computing and presentation of this indicator, it is assumed that attainment of
the 30-day mean summer open-water and deep-water dissolved oxygen criterion can
serve as an "umbrella" assessment protective of the remaining short duration dissolved
oxygen criteria in each applicable designated use.
Rule 3. Applicable criteria-based concentrations and durations which apply for
computing the Indicator.
• Migratory Fish and Spawning Nursery Designated Use: 6 mg/L 7-day mean
dissolved oxygen criterion applied as a 30-day mean for February-May
• Open-Water Fish and Shellfish Designated Use: 5 mg/L 30-day mean dissolved
oxygen criteria
• Deep-Water Seasonal Fish and Shellfish Designated Use: 3 mg/L 30-day mean
dissolved oxygen criteria
• Deep-Channel Seasonal Refuge Designated Use: 1 mg/L instantaneous
minimum dissolved oxygen criteria
• Shallow-Water Bay Grasses Designated Use: Refer to the underwater bay
grasses restoration goal acreages by segment to evaluate standards attainment
(See Chapter V, Table V-l this document). However, when water clarity
assessment data is available the shallow-water bay grasses designated use is
considered in attainment if:
1. Sufficient acres of underwater bay grasses are observed within the
segment; or
2. Sufficient acres of shallow-water habitat meet the applicable water
clarity criteria to support restoration of the desired underwater bay
grass acreage for that segment; or
3. Assessment of a combination of both, serves as the basis for
determining attainment or impairment of the shallow-water bay
grasses designated use
• Chlorophyll a numeric criteria as it applied to the open-water designated use
for the tidal mainstem James River segments and the District of Columbia's
tidal upper Potomac River and Anacostia River segments:
1. Tidal mainstem James River segments: criteria attainment assessed
during the spring (March 1-May 31) and summer (June 1-September 30)
seasons; both seasons must meet the applicable criteria for the
segment to be in attainment
2. District of Columbia's tidal Potomac River and Anacostia River
segments: criteria attainment only assessed during the summer (June 1-
September 30) season
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LITERATURE CITED
U.S. EPA (U.S. Environmental Protection Agency). 2003a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake Bay
and Its Tidal Tributaries (Regional Criteria Guidance). April 2003. EPA 903-R-03-002.
Region HI Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2003b. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability.
October 2003. EPA 903-R03-004. Region III Chesapeake Bay Program Office, Annapolis,
MD.
U.S. EPA (U.S. Environmental Protection Agency). 2004a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake Bay
and Its Tidal Tributaries - 2004 Addendum. October 2004. EPA 903-R-04-005. Region
III Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2004b. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability -
2004 Addendum. October 2004. EPA 903-R-04-006. Region III Chesapeake Bay
Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2005. Chesapeake Bay Program
Analytical Segmentation Scheme: Revisions, Decisions and Rationales 1983-2003.
2005 Addendum. December 2005. EPA 903-R-05-004. Region III Chesapeake Bay
Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2007a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2007 Addendum. July 2007. EPA 903-R-07-003.
Region III Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2007b. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries Chlorophyll a Addendum. October 2007. EPA 903-R-
07-005. Region III Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2008. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2008 Technical Support for Criteria Assessment
Protocols Addendum. September 2008. EPA 903-R-08-001. Region III Chesapeake
Bay Program Office, Annapolis, MD.
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45
U.S. EPA (U.S. Environmental Protection Agency). 2010a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2010 Technical Support for Criteria Assessment
Protocols Addendum. May 2010. EPA 903-R-10-002. Region III Chesapeake Bay
Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2010b. Chesapeake Bay Total
Maximum Daily Load for Nitrogen, Phosphorus and Sediment. U.S. Environmental
Protection Agency, Region 3 Chesapeake Bay Program Office, Annapolis, MD.
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chapter V
Aligning the Chesapeake Bay Program's
Underwater Bay Grasses Restoration Goal
with the Jurisdictions' Chesapeake Bay
Water Quality Standards
BACKGROUND
Chesapeake Bay Program Office staff identified the difference between the underwater
bay grasses restoration goal target (185,000 acres) adopted by the Chesapeake Bay
Program partnership in 2003 and the subsequent underwater bay grasses acreage goal
based on the sum of four tidal water jurisdictions' Chesapeake Bay water quality
standards for the 92 Chesapeake Bay segments (192,000 acres) as an issue for
resolution by the CBP partnership. The 2003 goal setting approach was extensive but
included many cases of undercounting underwater bay grasses acres due to estimated
acres of underwater bay grasses that were 'clipped' from underwater bay grasses beds
when applying the GIS analyses. 'Clipped' areas represented the difference between
the GIS-based shoreline delineation and actual shorelines in the aerial photographs.
The Chesapeake Bay Program partners have since adopted a "Water Quality Standards-
based Goal", presently 192,000 acres, as the partnership's official underwater bay grass
restoration goal in place of the current 185,000 acre goal to ensure full consistency with
Delaware, Maryland, Virginia, and the District of Columbia's Chesapeake Bay water
quality standards. This chapter documents the updating the Chesapeake Bay Program
partnership's underwater bay grasses restoration goal.
The underwater bay grasses acreage goals were developed as part of a larger effort to
restore Chesapeake Bay water quality. In 1993, the Chesapeake Executive Council
formally adopted its first underwater bay grasses restoration target as the Chesapeake
Bay Program's first quantitative living resource restoration goal (Chesapeake
Executive Council 1993). Subsequent revision of the goal occurred coincident with
providing target acreages supporting the Chesapeake 2000 agreement, the development
of Chesapeake Bay water quality criteria and the adoption of those criteria along with
Chesapeake Bay designated uses into state water quality standards regulations by the
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47
tidal bay jurisdictions of Delaware, Maryland, Virginia and the District of Columbia
(Chesapeake Executive Council 2000, U.S. EPA 2003a, U.S. EPA 2010).
From 2012 to 2015, the Chesapeake Bay Program's Criteria Assessment Protocol
Workgroup conducted a water quality criteria assessment protocols review process in
support of the Chesapeake Bay TMDL 2017 Midpoint Assessment. Chesapeake Bay
Program Office staff identified the difference between the 2003 bay grass restoration
goal target (185,000 acres) adopted by the Chesapeake Bay Program partnership and
the bay grass target acreage goal based on the sum of four tidal water jurisdictions'
Chesapeake Bay water quality standards for the 92 Chesapeake Bay segments (192,000
acres) as an issue for resolution by the Partnership. The basis, derivation, revision and
adoption of the 185,000 acre bay-wide bay grass restoration acreage goal and
associated assessment protocols is provided in the April 2003 publication Ambient
Water Quality Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the
Chesapeake Bay and its Tidal Tributaries and the October 2003 Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability
(U.S. EPA 2003a, 2003b). The four Chesapeake Bay jurisdictions subsequent
promulgation of their respective Chesapeake Bay water quality standards was not,
however, based on a direct adoption of the published U.S. EPA (2003a) 185,000 acre
underwater bay grasses goal (U.S. EPA 2010).
The Chesapeake Bay Program partnership and its Submerged Aquatic Vegetation
Workgroup assisted the Criteria Assessment Protocol Workgroup in understanding the
historical basis for the differences in the two underwater bay grasses restoration goal
totals. The two workgroups jointly reviewed the details of how the original 185,000
acre underwater bay grasses restoration goal derived which then served as the
foundation for the four Chesapeake Bay jurisdictions promulgating the underwater bay
grasses restoration acres into their Chesapeake Bay water quality standards. In revising
the underwater bay grasses restoration goal, the jurisdictions had the benefit of the body
of history used to develop the 185,000 acre goal, new information available after EPA's
publication of the 2003 Chesapeake Bay criteria and designated uses documents (U.S.
EPA 2003a, 2003b), and the jurisdictions' adoption of the Bay water quality criteria
and tidal water designated uses into their Chesapeake Bay water quality standards
regulations (U.S. EPA 2010). In adopting segment-specific water clarity/underwater
bay grasses restoration acreage-based water quality standards, the four Chesapeake Bay
jurisdictions more accurately reflected segment-based underwater bay grasses goal
acreages (U.S. EPA 2003b). The water quality standards-based acreage goal is better
aligned with the methods used in the annual aerial survey of underwater bay grasses to
assess the status of and track changes towards attaining the shallow-water bay grasses
designated use's water clarity and underwater bay grasses restoration acreages criteria.
This chapter reviews the history of establishing Chesapeake Bay underwater bay
grasses restoration acreage goals supporting the assessment of water quality standards
attainment for the water clarity criteria for protection of the shallow-water bay grass
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48
designated use. The results of this review supported updating the Chesapeake Bay
Program partnership's underwater bay grasses restoration goal to be consistent with the
four tidal Bay jurisdictions combined Chesapeake Bay water quality standards-based
underwater bay grasses restoration acreages, presently totaling 192,000 acres.
HISTORY OF DEVELOPING THE UNDERWATER BAY GRASSES
RESTORATION GOAL
The original tiered targets supporting an underwater bay grasses restoration acreage
goal for Chesapeake Bay were first published in the 1992 underwater bay grasses
technical synthesis (Batiuk et al. 1992) in response to commitments set forth in the
Submerged Aquatic Vegetation Policy for the Chesapeake Bay and Tidal Tributaries
(Chesapeake Executive Council 1989). Three tiers of restoration targets were
developed. The tiered set of underwater bay grasses distribution restoration targets was
established to provide a measure of incremental progress for Chesapeake Bay
restoration in response to improvements in water quality. The Tier I restoration target
was the restoration of underwater bay grasses to areas that were currently or previously
inhabited by underwater bay grasses as mapped through regional and bay-wide aerial
surveys from 1971 through 1990 (Batiuk et al. 1992, Dennison et al. 1993). The Tier II
and Tier III restoration targets were supporting the restoration of underwater bay
grasses to all shallow-water areas delineated as existing or potential shallow water
underwater bay grasses habitat, down to the 1- and 2-meter depth contours,
respectively. A complete, detailed description of the original process for developing
the tiered restoration goals and targets is found in Batiuk et al. (1992, pages 109-119).
In 1993 the Chesapeake Executive Council formally adopted the Tier I restoration
target as the Chesapeake Bay Program's first quantitative living resource restoration
goal (Chesapeake Executive Council 1993). Refinements were made to the Tier I
restoration goal as a result of a reevaluation of the historical underwater bay grasses
aerial survey digital data sets, including a thorough quality assurance evaluation, which
resulted in corrections to the original data (Batiuk et al. 2000). The revised Tier I goal
total was 113,720 acres. The Tier I goal and the coincident goal areas for each
Chesapeake Bay segment were published in Chesapeake Bay Submerged Aquatic
Vegetation Water Quality and Habitat-Based Requirements and Restoration Targets:
A Second Technical Synthesis (see Chapter VIII, Table VIII-1 in Batiuk et al. 2000).
U.S. EPA (2003b, p. 118) reported that the Chesapeake 2000 agreement (Chesapeake
Executive Council 2000) committed the Chesapeake Bay Program partners to revising
the existing underwater bay grass restoration goals and strategies: ".... to reflect
historical abundance, measured as acreage and density fi'om the 1930s to present. "
The basis for the goal setting acreages referred to a "historical" underwater bay grasses
distribution as being assessed from aerial photographs from the 1930s to the early
1970s (U.S. EPA 2003b). Single best year assessments were made on each Chesapeake
Bay segment and characterized as "historical" or designated a "best year" in the
contemporary Chesapeake Bay underwater bay grass aerial survey monitoring data
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49
(1978-2000) (U.S. EPA 2003b). Underwater bay grasses abundance was classified
according to Chesapeake Bay segments and depths that were designated for the new
Chesapeake Bay shallow-water bay grass designated use (U.S. EPA 2003a, b).
The new 2003 restoration goal of 185,000 acres was derived from the composited
1930s-2000 time series using the total single best year acreage summed over all the
segment depths that were designated for the shallow-water bay grass use (U.S. EPA
2003a). U.S. EPA (2003b, Table IV-12, p. 114) describes the details of the
methodology used in taking the combination of historical and contemporary
information available and determining the revised 185,000 acre Chesapeake baywide
underwater grasses restoration goal3. Goal options were provided during the revision
process that ranged 17-fold from a low for the area of the 1984 underwater bay grass
distribution (37,356 acres) to a high for the area represented by the total bay shallow-
water habitat out to the 2-meter depth contour (640,926 acres) minus underwater acres
from declared underwater bay grasses no-grow zones (U.S. EPA 2003b, p. 119).
RESTORATION GOAL AND WATER QUALITY STANDARDS
UNDERWATER BAY GRASSES RESTORATION ACREAGES
COMPARISON
During 2013 and early 2014, the CBP Habitat Goal Implementation Team's Submerged
Aquatic Vegetation Workgroup reviewed the goal setting methodology used to derive
the 2003 Chesapeake Bay underwater bay grasses restoration acreage goal.
Chesapeake Bay Program Office staff, working with the SAV Workgroup, identified
differences between the segment-specific underwater bay grasses restoration acreage
targets supporting the 185,000 acre goal published in 2003 and the more recent 192,000
acres adopted by the four tidal water jurisdictions in their Chesapeake Bay water quality
standards. The 185,000 acre underwater bay grasses restoration goal setting effort
preceded the Chesapeake Bay tidal water jurisdiction's adoption of the Chesapeake
Bay water quality criteria into their State's water quality standards regulations. The
Chesapeake Bay Program partnership used data through 2000 for its single best year
assessment and considered a 2001 underwater bay grasses acreage total (U.S. EPA
2003b, Figure IV-31) as a potential goal when setting the 185,000 acre restoration
target. The subsequent water quality standards promulgation process had the benefit of
the analyses and summary information available from the development of the 185,000
acre goal and the published derivation of Chesapeake Bay water quality criteria.
The 2003 goal setting approach leading to the 185,000 underwater bay grass acre
restoration goal included many cases of undercounting underwater bay grasses acres.
The undercounting was due to estimated acres of underwater bay grasses with 'clipped'
underwater bay grass beds within the GIS analyses. 'Clipped' areas represented the
3 Also see Appendix A in U.S. EPA 2003b for a statement about the 185,000 acre goal adoption being consistent
with the goals of the Chesapeake 2000 agreement.
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difference between the GIS-based shoreline delineation and actual shorelines in the
aerial photographs. The process of clipping these areas produced a loss of this clipped
underwater bay grasses from a segment as viewed through the lens of GIS because the
clipped underwater bay grasses acres would be classified as being 'on land' and could
not have an associated bathymetry for that area. The inaccuracy of the GIS shoreline
data layer exists for multiple reasons, examples being the scale of the data and changes
in the shoreline over time not reflected in the shoreline data set (e.g., erosion and sea
level rise). At the same time there was a similar problem of undercounting involved
with underwater bay grasses on underwater flats around islands due to shifting
shorelines. This issue is acknowledged in U.S. EPA 2004 (see pp. 92-93).
To account for the underwater bay grasses acreages undercounting issues, "The chosen
solution was to count all of the SA V (underwater bay grass) acreage for a given segment
that occurred within a single best year regardless of any shoreline, bathymetry data
limitations or water clarity application depth restrictions'" (U.S. EPA 2004). Further,
as described in U.S. EPA 2004, EPA recognized the officially adopted underwater bay
grasses restoration goals involved in defining the 185,000 acre goal but encouraged the
tidal Chesapeake Bay jurisdictions to consider the new information when adopting their
new Chesapeake Bay water quality standards, setting up the CBP partnership with two
different sets of underwater bay grasses restoration goal acreages:
"The U.S. EPA 2004 Technical Support Document 2004 Addendum
documents the 'expanded restoration acreage ' updating existing use
acreage and the available shallow water habitat area for each
Chesapeake Bay Program segment. As described in the 2004
addendum: "The expanded restoration acreage is the greatest acreage
fi'om among the updated existing use acreage (1978-2002; no shoreline
clipping), the Chesapeake Bay Program adopted SA V (underwater bay
grasses) restoration goal acreage (strictly adhering to the single best
year methodology with clipping) and the goal acreage displayed without
shoreline or application depth clipping and including areas fi'om SA V
still lacking bathymetry data. This 'expanded restoration acreage ' is
being documented here andprovided to the partners as the best acreage
values that can be directly compared with SAV acreages reported
through the bay-wide SAV aerial survey. These acreages are not the
officially adopted goals of the watershed partners; they are for
consideration by the jurisdictions when adopting refined and new water
quality standards regulations.
The Chesapeake Bay Program SA V restoration goal of 185,000 acres
and the segment-specific goal acreages stand as the watershed
partners' cooperative restoration goal for this critical living resource
community (Chesapeake Executive Council 2003). EPA recommends
that the jurisdictions with the Chesapeake Bay tidal waters consider
-------
51
adopting the expanded restoration acreages... into their refined and new
water quality standards regulations. "
There were also no bathymetric data for many tidally connected ponds in the
Chesapeake Bay segments. Underwater bay grasses in these ponds, therefore, was
excluded from these restoration acreages. Lack of bathymetric data affected the
accounting for underwater bay grasses in upper portions of the Patuxent River Tidal
Fresh (PAXTF) and Anacostia Tidal Fresh (ANATF) segments. The ANATF segment
had no mapped underwater bay grasses, however, the lack of bathymetry in the upper
Patuxent River excluded most of the known underwater bay grasses acres in that area
of the tidal river.
With respect to setting water quality standards-based underwater bay grass goal
acreages for each of the 92 Chesapeake Bay segments, U.S. EPA (2004) further
highlighted that:
"Since the 2003 publication of both the Regional Criteria Guidance and
the Technical Support Document, new information has become
available to the watershed jurisdictions and EPA in support of state
adoption of SAV restoration goal ...acreages. This new information will
also help the four jurisdictions with Chesapeake Bay tidal waters to
adopt consistent, specific procedures for determining attainment of the
shallow-water bay grass designated uses into their regulations. EPA
continues to support and encourage the jurisdictions' adoption of
segment-specific submerged aquatic vegetation (SAV) restoration goal
acreages ...necessary to support restoration of those acreages of SAV
into each jurisdiction's respective water quality standards regulations. "
After the 185,000 acre restoration goal was set, 2002 data for underwater bay grass
aerial surveys became available to support decision-making for establishing the four
jurisdictions' Chesapeake Bay water quality standards.
WATER QUALITY STANDARDS-BASED
UNDERWATER BAY GRASSES RESTORATION ACREAGES
The Chesapeake Bay Program's Submerged Aquatic Vegetation Workgroup, working
with Chesapeake Bay Program Office staff, determined that the basis for the 185,000
acre goal formed the foundation for the water quality standards-based goal. With few
exceptions, the jurisdictions' Chesapeake Bay water quality standards segment-specific
underwater bay grasses restoration acreages are equal to or greater than the segment-
specific acreage goals supporting the original 185,000 acre goal (Table V-l). In setting
the original underwater bay grasses restoration acreages back in 1993, the Partnership
reached agreement on a methodology for derivation of the acreages which was applied
consistently across all Chesapeake Bay segments.
-------
52
In amending their state water quality standards regulations, however, Virginia made
the decision in 2005 to adjust the Partnership's underwater bay grasses restoration
acreages for four segments — three in the tidal James River and one in the lower
Rappahannock River based on attainability considerations using model simulated
outcomes. This was not the standard approach, but rather an internal state decision
specific to handful of tidal Bay segments. EPA supported Virginia decisions as they
were made on the best available information at that time and reflected Virginia
concerns about their ability to reduce nutrient and sediment pollutant loads down to
levels necessary to restore underwater bay grasses to the restoration acreages based on
historical coverage.
The four Chesapeake Bay tidal water jurisdictions — Maryland, Virginia, Delaware
and District of Columbia — were all consistent in their consideration for adding back
previously missing acres into the segment-specific goals due to GIS method-related
clipping away of visible underwater bay grasses acres on the aerial photographs. Most
of these 'clipped' acres were previously considered as 'on land' even though they were
clearly visible and identifiable between the GIS layer land boundary and the shoreline
of the photographs. Additional excluded acres that were added back to the segments
had previously missing bathymetry or were segments that were lacking established
restoration goals (Table V-l).
For purposes of water quality standards adoption and assessment of criteria attainment,
the Chesapeake Bay and its tidal tributaries and embayments have been sub-divided
into a total of 104 segments, including individual segments split by jurisdiction (U.S.
EPA 2004, 2008). Of these 104 segments, there were 71 segments1 where the
jurisdictions' Chesapeake Bay water quality standards underwater bay grasses
restoration acreages were greater than the actual 1993 CBP underwater bay grasses
restoration goal acreages and 22 segments2 where the acreages were the same. Only in
11 segments3 were the jurisdictions' Chesapeake Bay water quality standards
underwater bay grasses restoration acreages revised to be lower than the original 1993
CBP underwater bay grasses restoration goal acreages. The rationale for these
differences between the 1993 Chesapeake Bay Program's restoration goal acreages and
the four jurisdictions Chesapeake Bay water quality standards underwater grasses
restoration acreages are documented in Table V-2.
For the 11 segments where the jurisdictions' water quality standards acreages were
lower than the original 1993 goal acreages, 7 of those segments were split segments.
In all 7 of those split segments, the total sum of the individual split segments was equal
to or higher than the original 1993 goal acreage for the entire segment. Therefore, only
in the case of the four Virginia segments listed above were the water quality standards
acreages lower than the 1993 goal acreages.
-------
53
Table V-2. Chesapeake Bay segment jurisdiction-specific water quality standards-based underwater bay grasses (SAV) restoration acreages compared with the original
1993 Chesapeake Bay Program SAV restoration goal acreages.
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
Delaware
C&DOH-DE
No Goal
NA
0
-
-
-
-
Source: Rebecca Golden, Maryland Department
of Natural Resources, Pers. Comm.
NANTF-DE
No Goal
NA
-
-
-
-
-
-
District of Columbia
ANATF-DC
1991
6
6
0
7
12
15
No Change
POTTF-DC
1991
368
383
15
376
383
383
Used Single Best Year (1991)
Maryland
ANATF-MD
No Goal
NA
0
-
-
-
-
Source: Rebecca Golden, Maryland Department
of Natural Resources, Pers. Comm.
BACOH
No Goal
NA
30
30
-
-
-
Goal target source is MD COMAR 26.08.02.03-3
regulations. Goal last updated November 2010
(Source: Rebecca Golden, Maryland Department
of Natural Resources, Pers. Comm.)
BIGMH1
Historical
1,991
2,021
30
2,021
2,187
2,187
Total SAV Acreage Out to Split Segment's
Application Depth (accounting for previously
clipped acres). Note the total acres for sum of
the split segments goals for BIGMH1 and
BIGMH2 is greater than acreages of BIGMH
before the split which affected separate
application depths for the two sub-segments.
-------
54
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
BIGMH2
Historical
23
22
-1
25
25
25
Total SAV Acreage Out to Split Segment's
Application Depth (accounting for previously
clipped acres). Note the total acres for sum of
the split segments goals for BIGMH1 and
BIGMH2 is greater than acreages of BIGMH
before the split which affected separate
application depths for the two sub-segments.
BOHOH
2000
97
354
257
112
187
354
Used Single Best Year (2001)
BSHOH
Historical
158
350
192
167
236
350
Used Single Best Year (2002)
C&DOH-MD
1978
0
7
7
-
-
7
Used Single Best Year (2001)
CB1TF1
Historical
833
754
-79
862
874
874
Total SAV Acreage Out to Split Segment's
Application Depth (accounting for previously
clipped acres). Note the total acres for sum of
the split segments goals for CBTF1 and CBTF2
is approximately the total for CBTF1 before the
split which is affected separate application
depths for the two sub-segments.
CB1TF2
Historical
12,075
12,149
74
12,149
12,354
12,354
Historical Restoration Acreage + Clipped
Acreage which equals Total SAV Acreage Out to
Split Segment's Application Depth (accounting
for previously clipped acres). Note the total acres
for sum of the split segments goals for CBTF1
and CBTF2 is approximately the total for CBTF1
before the split which is affected separate
application depths for the two sub-segments.
CB20H
Historical
302
705
403
327
1,010
1,010
Used Single Best Year (2000)
CB3MH
1978
943
1,370
427
1,018
1,370
1,370
Used Single Best Year (1978)
CB4MH
Historical
2,511
2,533
22
2,533
2,824
2,824
Historical Restoration Acreage + Clipped
Acreage
-------
55
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
CB5MH-MD
Historical
8,257
8,270
13
8,270
8,575
8,575
Historical Restoration Acreage + Clipped
Acreage
CHOMH1
Historical
8,044
8,184
140
8,184
8,721
8,721
Historical Restoration Acreage + Clipped
Acreage
CHOMH2
Historical
1,499
1,621
122
1,621
2,020
2,020
Historical Restoration Acreage + Clipped
Acreage
CHOOH
Historical
63
72
9
72
89
89
Historical Restoration Acreage + Clipped
Acreage
CHOTF
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
CHSMH
Historical
2,724
2,928
204
2,928
3,762
3,762
Historical Restoration Acreage + Clipped
Acreage
CHSOH
Historical
63
77
14
77
117
117
Historical Restoration Acreage + Clipped
Acreage
CHSTF
No Goal
NA
1
1
-
-
-
Goal target source is MD COMAR 26.08.02.03-3
regulations. Goal last updated November 2010
(Source: Rebecca Golden, Maryland Department
of Natural Resources, Pers. Comm.)
EASMH
Historical
6,108
6,209
101
6,209
6,397
6,397
Historical Restoration Acreage + Clipped
Acreage
ELKOH1
2000
1,593
1,844
251
1,631
1,652
1,844
Used Single Best Year (2001)
ELKOH2
2000
55
190
135
57
57
190
Used Single Best Year (2001)
FSBMH
Historical
193
197
4
197
730
730
Historical Restoration Acreage + Clipped
Acreage
GUNOH1
2000
1,772
1,860
88
1,833
1,860
1,860
Used Single Best Year (2000)
GUNOH2
2000
482
572
90
549
572
572
Used Single Best Year (2000)
-------
56
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
HNGMH
Historical
7,686
7,761
75
7,761
7,943
7,943
Historical Restoration Acreage + Clipped
Acreage
LCHMH
Historical
3,950
4,076
126
4,076
4,134
4,134
Historical Restoration Acreage + Clipped
Acreage
MAGMH
Historical
545
579
34
579
716
716
Historical Restoration Acreage + Clipped
Acreage
MANMH1
Historical
4,264
4,294
30
4,294
4,331
4,331
Historical Restoration Acreage + Clipped
Acreage
MANMH2
Historical
95
59
-36
103
103
103
Total SAV Acreage Out to Split Segment's
Application Depth. Note the total acres for the
sum of the split segments goals for MANMH1
and MANMH2 is approximately the total for the
MANMH before the split.
MATTF
2000
279
792
513
296
331
792
Used Single Best Year (2002)
MIDOH
Historical
838
879
41
879
910
910
Historical Restoration Acreage + Clipped
Acreage
NANMH
Historical
3
3
0
3
6
6
No change
NANOH
Historical
3
12
9
12
13
13
Historical Restoration Acreage + Clipped
Acreage
NANTF-MD
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
NORTF
Historical
88
89
1
89
164
164
Historical Restoration Acreage + Clipped
Acreage
PATMH
Historical
298
389
91
389
585
585
Historical Restoration Acreage + Clipped
Acreage
-------
57
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
PAXMH1
Historical
1,148
1,459
311
1,183
1,474
1,474
Total SAV Acreage Out to Split Segment's
Application Depth accounting for clipped
acreage. Note the total sum of Water Quality
Standards sub-segment acreage goal that
represents PAXMH is greater than the original
restoration goal
PAXMH2
Historical
172
172
0
192
201
201
Historical (USEPA Oct. 2004). No Change
PAXMH3
Historical
0
0
0
-
-
282
Historical (USEPA Oct. 2004). No Change
PAXMH4
Historical
2
1
-1
2
3
348
Total SAV Acreage Out to Split Segment's
Application Depth accounting for clipped
acreage. Note the total sum of Water Quality
Standards sub-segment acreage goal that
represents PAXMH is greater than the original
restoration goal
PAXMH5
Historical
3
2
-1
3
7
378
Total SAV Acreage Out to Split Segment's
Application Depth accounting for clipped
acreage. Note the total sum of Water Quality
Standards sub-segment acreage goal that
represents PAXMH is greater than the original
restoration goal
PAXMH6
Historical
0
0
0
-
-
82
Historical (USEPA Oct. 2004). No Change
PAXOH
2000
68
115
47
104
115
115
Used Single Best Year (2000)
PAXTF
1996
5
205
200
152
158
205
Used Single Best Year (2001)
PISTF
1987
783
789
6
788
788
789
Used Single Best Year (1987)
-------
58
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
POCMH-MD
Historical
859
877
18
877
912
912
Historical Restoration Acreage + Clipped
Acreage
POCOH-MD
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
POCTF
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
POTMH-MD
Historical
6,919
7,088
169
7,088
9,005
9,005
Historical Restoration Acreage + Clipped
Acreage
POTOH1-MD
1998
1,306
1,387
81
1,363
1,387
1,387
Used Single Best Year (1998)
POTOH2-MD
1998
226
262
36
262
262
262
Used Single Best Year (1998)
POTOH3-MD
1998
1,044
1,153
109
1,150
1,153
1,153
Used Single Best Year (1998)
POTTF-MD
1991
1,992
2,142
150
2,063
2,143
2,143
Used Single Best Year (1991)
RHDMH
Historical
48
60
12
60
98
98
Historical Restoration Acreage + Clipped
Acreage
SASOH1
2000
763
1,073
310
814
958
1,073
Used Single Best Year (2001)
SASOH2
2000
1
95
94
2
95
1,938
Used Single Best Year (2001)
SEVMH
1999
329
455
126
351
455
455
Used Single Best Year (1999)
SOUMH
Historical
459
479
20
479
552
552
Historical Restoration Acreage + Clipped
Acreage
TANMH1
Historical
24,451
24,683
232
24,675
26,250
26,250
Total SAV Acreage Out to Split Segment's
Application Depth accounting for clipped acres.
Note the total acres for the sum of the split
segments goals forTANMHI and TANMH2 is
higher than the total for TANMH before the split.
TANMH2-MD
Historical
164
74
-90
165
166
166
Total SAV Acreage Out to Split Segment's
Application Depth accounting for clipped acres.
Note the total acres for the sum of the split
segments goals forTANMHI and TANMH2 is
higher than the total for TANMH before the split.
-------
59
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
WBRTF
No Goal
NA
0
-
-
-
-
No data or no evidence of SAV (USEPA Oct.
2004)
WICMH
Historical
3
3
0
3
7
7
No change
WSTMH
Historical
214
238
24
238
338
338
Historical Restoration Acreage + Clipped
Acreage
Virginia
APPTF
Historical
319
379
60
345
379
379
Historical Restoration Acreage + Clipped + No
Depth Limitation
CB5MH-VA
Historical
6,704
7,633
929
6,779
7,633
7,633
Historical Restoration Acreage + Clipped + No
Depth Limitation
CB6PH
Historical
980
1,267
287
1,015
1,266
1,266
Historical Restoration Acreage + Clipped + No
Depth Limitation
CB7PH
Historical
14,620
15,107
487
14,975
15,108
15,108
Historical Restoration Acreage + Clipped + No
Depth Limitation
CB8PH
1996
6
11
5
6
11
11
Used Single Best Year (1996)
CHKOH
2000
348
535
187
461
535
535
Used Single Best Year (2000)
CRRMH
Historical
516
768
252
518
647
768
Used Single Best Year (2002)
EBEMH
No Goal
NA
-
-
-
-
-
-
ELIPH
No Goal
NA
-
-
-
-
-
-
-------
60
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
JMSMH
Historical
531
200
-331
605
712
712
200 acres were derived as "attainable acres"
developed from the May 2004 Chesapeake Bay
Program Water Quality/Sediment Transport
model confirmation run (Source: Lew Linker
(USEPA) via Cindy Johnson (VADEQ)).
JMSOH
1998
7
15
8
15
15
15
Used Single Best Year (2001)
JMSPH
Historical
604
300
-304
615
693
693
300 acres were derived as "attainable acres"
developed from the May 2004 Chesapeake Bay
Program Water Quality/Sediment Transport
model confirmation run (Source: Lew Linker
(USEPA) via Cindy Johnson (VADEQ)).
JMSTF1
Historical
1,333
1,000
-333
1,409
1,530
1,530
WQS Acreage of unknown origin
JMSTF2
Historical
266
200
-66
372
375
375
WQS Acreage of unknown origin
LAFMH
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
LYNPH
1986
69
107
38
71
107
107
Used Single Best Year (1986)
MOBPH
Historical
15,096
15,901
805
15,395
15,901
15,901
Historical Restoration Acreage + Clipped + No
Depth Limitation
MPNOH
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
MPNTF
1998
75
85
10
76
85
85
Used Single Best Year (1998)
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61
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
PIAMH
Historical
3,256
3,479
223
3,310
3,480
3,480
Historical Restoration Acreage + Clipped + No
Depth Limitation
PMKOH
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
PMKTF
1998
155
187
32
158
187
187
Used Single Best Year (1998)
POCMH-VA
Historical
3,233
4,066
833
3,342
4,066
4,066
Historical Restoration Acreage + Clipped + No
Depth Limitation
POCOH-VA
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
POTMH-VA
Historical
3,254
4,250
996
3,575
4,250
4,250
Historical Restoration Acreage + Clipped + No
Depth Limitation
POTOH1-VA
1998
1,145
1,503
358
1,485
1,503
1,503
Used Single Best Year (1998)
POTTF-VA
1991
2,008
2,093
85
2,082
2,093
2,093
Used Single Best Year (1991)
RPPMH
Historical
5,380
1,700
-3680
5,500
7,814
7,814
1700 acres were derived as "attainable acres"
developed from the May 2004 Chesapeake Bay
Program Water Quality/Sediment Transport
model confirmation run (Source: Lewis Linker
(USEPA) via Cindy Johnson VADEQ)
RPPOH
No Goal
NA
4
4
-
-
-
There were no data or record of SAV, however,
a decision was made to provide the segment
with an acreage target of 4 acres
RPPTF
2000
20
66
46
40
40
66
Used Single Best Year (2001)
SBEMH
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
TANMH1-VA
Historical
13,351
13,579
228
13,520
13,579
13,579
Historical Restoration Acreage + Clipped + No
Depth Limitation
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62
Chesapeake
Bay Segment
Source of
the 1993
CBP SAV
Restoration
Goal
Acreages
1993 CBP
SAV
Restoration
Goals
Acreages
State Water
Quality
Standards
SAV
Restoration
Acreages
Difference
Between
State WQ
Standards
Acreages
and 1993
Restoration
Goal
Actual
Mapped
SAV (up to
2000)
Clipped to
Application
Depth
Actual
Mapped
SAV (up to
2000) Not
Clipped
Actual
Mapped SAV
(including
that mapped
more
recently than
2000) Not
Clipped
Rationale for the Difference in the Acreage
Between the 1993 Chesapeake Bay Program
Restoration Goal and the State Water Quality
Standards SAV Restoration Acreages
WBEMH
No Goal
NA
NGZ
-
-
-
-
Designated SAV No Grow Zone (NGZ)
YRKMH
Historical
176
239
63
187
239
239
Historical Restoration Acreage + Clipped + No
Depth Limitation
YRKPH
Historical
2,272
2,793
521
2,297
2,766
2,766
2793 acres were derived as "attainable acres"
developed from the May 2004 Chesapeake Bay
Program Water Quality/Sediment Transport
model confirmation run (Source: Lew Linker
(USEPA) via Cindy Johnson (VADEQ)).
Totals (acres)
-
184,892
191,921
-
189,863
206,776
211,084
-
Key: NGZ = designated SAY no grow zone; NA = not applicable
Table V-2. Chesapeake Bay segments and their underwater bay grasses goal acreage changes from 1993 Chesapeake Bay Program restoration goal acres to 2004 water quality
standards goal acres.
Segments with declines in goals acres
Segments with no change to the acreage
Segments with an increase in goal acres
BIGMH2, CB1TF1, MANMH2, PAXMH4,
PAXMH5, TANMH2-MD, JMSTF1, JMSTF2,
JMSMH, JMSPH, RPPMH
ANATF-DC, ANATF-MD, C&DOH-DE, CHOTF,
NANTF-DE, NANTF-MD, NANMH, PAXMH2,
PAXMH3, PAXMH6, POCOH, POCTF, WRBTF,
WICMH, EBEMH, ELIPH, LAFMH, MPNOH,
PMKOH, POCOH, SBEMH, WBEMH
POTTF-DC, BACOH, BIGMH1, BIGMH2, BOHOH, BSHOH, C&DOH-MD, CB1TF1,
CB1TF2, CB20H, CB3MH, CB4MH, CB5MH-MD, CHOMH1, CHOMH2, CHOOH,
CHOTF, CHSMH, CHSTF, EASMH, ELKOH1, ELKOH2, FSBMH, GUNOH1,
GUNOH2, HNGMH, LCHMH, MAGMH, MANMH1, MATTF, MIDOH, NANOH,
NORTF, PATMH, PAXMH1, PAXOH, PAXTF, PISTF, POCMH-MD, POTMH-MD,
POTOH1-MD, POTOH2-MD, POTOH3-MD, POTTF-MD, RHDMH, SASOH1,
SASOH2, SEVMH, SOUMH, TANMH1, WSTMH, APPTF, CB5MH-VA, CB6PH,
CB7PH, CB8PH, CHKOH, CRRMH, JMSOH, LYNPH, MOBPH, MPNTF, PIAMH,
PMKTF, POCMH-VA, POTMH-VA, POTOH1-VA, POTTF-VA, RPPOH, RPPTF,
TANMH1-VA, YRKMH, YRKPH.
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63
CHESAPEAKE BAY PROGRAM 192,000 ACRE WATER QUALITY
STANDARDS-BASED UNDERWATER BAY GRASSES ACREAGE GOAL
In the 2014 Chesapeake Bay Watershed Agreement, the Chesapeake Bay Program
partners adopted the 192,000 acres as the partnership's official underwater bay grasses
restoration goal in place of the current 185,000 acre goal to ensure full consistency with
Maryland, Virginia, Delaware and the District of Columbia's Chesapeake Bay water
quality standards (Chesapeake Executive Council 2014). The 185,000 acre underwater
bay grasses restoration goal was recognized by the Partnership as a conservative target
affected by undercounting underwater bay grasses acres in a subset of Chesapeake Bay
segments. Undercounted acres were due to multiple factors included mismatches
between shoreline data layers and present day shorelines that resulted in underwater bay
grasses 'on land' that was actually in the water, or missing bathymetry (e.g., PAXTF).
CONSIDERATIONS FOR FUTURE UNDERWATER BAY GRASSES
RESTORATION ACREAGE GOALS
There are four Virginia segments - upper tidal fresh James River, lower tidal fresh James
River, middle James River and Lower Rappahannock River - which are lower than the
1993 restoration goal acreage because they were based on model simulation attainability
decisions. These acreages are inconsistent with the methodology used in all the other 100
segments in Virginia, Maryland, Delaware and the District of Columbia. Future
consideration should be given to building in additional consistency within and between
the four Chesapeake Bay jurisdictions in their methodologies for basis of setting their
water quality standards' underwater bay grasses restoration goal acreages.
To address one inconsistency, all four jurisdictions would only go out to Chesapeake
Bay segment-specific application depth (the Maryland method) or they would extend out
to include the deep water acres of underwater bay grasses mapped beyond the segment
specific application depth (the Virginia methodology). If, for example, Maryland
adopted the Virginia methodology, then the additional deep water acres beyond the
application depth in Maryland beyond their existing goal acreages would increase the
192,000 goal by about 14,000 acres.
Finally, recognize that there are still five Chesapeake Bay segments without goal
acreages which are not designated as bay grass "no grow zones" (see the eighth column
in Table V-l). The acreage total remains subject to goals being set for these remaining
segments without restoration acreage goals at this time.
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LITERATURE CITED
Batiuk, R. A., R. J. Orth, K. A. Moore, W. C. Dennison, J. C. Stevenson, L. W. Staver,
V. Carter, N. B. Rybicki, R. E. Hickman, S. Kollar, S. Bieber, and P. Heasly. 1992.
Chesapeake Bay Submerged Aquatic Vegetation Habitat Requirements and Restoration
Targets: A Technical Synthesis. Annapolis, MD. CBP/TRS 83/92. 248 pp.
Batiuk, R.A., P. Bergstrom, M. Kemp, E. Koch, L. Murray, J.C. Stevenson, R. Bartleson,
V. Carter, N.B. Rybicki, J.M. Landwehr, C. Gallegos, L. Karrh, M. Naylor, D. Wilcox,
K, A. Moore, S. Ailstock, andM. Teichberg. 2000. Chesapeake Bay Submerged Aquatic
Vegetation Water Quality and Habitat-Based Requirements and Restoration Targets: A
Second Technical Synthesis. CBP/TRS 245/00 EPA 903-R-00-014. U.S. Environmental
Protection Agency, Chesapeake Bay Program, Annapolis, MD.
Chesapeake Executive Council 1989. Submerged Aquatic Vegetation Policy for the
Chesapeake Bay and Tidal Tributaries. Annapolis, MD. July.
Chesapeake Executive Council. 1993. Directive 93-9 Submerged Aquatic Vegetation
Restoration Goals. U.S. EPA. Annapolis, MD.
Chesapeake Executive Council. 2000. Chesapeake 2000. Chesapeake Bay Program,
Annapolis, MD.
Chesapeake Executive Council. 2003. Directive No. 03-02 Meeting the Nutrient and
Sediment Reduction Goals. Chesapeake Bay Program, Annapolis, MD.
Chesapeake Executive Council. 2014. Chesapeake Bay Watershed Agreement.
Chesapeake Bay Program, Annapolis, MD.
Dennison, W. C., R.J. Orth, K.A. Moore, J.C. Stevenson, V. Carter, S. Koller, P.W.
Bergstrom, and R.A. Batiuk. 1993. Assessing water quality with submersed
aquaticvegetation. Bioscience. 143:86-94.
U.S. EPA (U.S. Environmental Protection Agency). 2003a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake Bay
and Its Tidal Tributaries. EPA 903-R-03-002. U.S. Environmental Protection Agency,
Region III, Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2003b. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability.
October 2003. EPA 903-R-03-004. Region III Chesapeake Bay Program Office,
Annapolis, MD.
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65
U.S. EPA (U.S. Environmental Protection Agency). 2004b. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability - 2004
Addendum. October 2004. EPA 903-R-04-006. Region III Chesapeake Bay Program
Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2010. Chesapeake Bay Total
Maximum Daily Load for Nitrogen, Phosphorus and Sediment. U.S. Environmental
Protection Agency, Region 3 Chesapeake Bay Program Office, Annapolis, MD.
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¦
chapter VI
Interim Rules for Water Quality Clean Water
Act Section 303(d) Listing Status Using the
Chesapeake Benthic Index of Biotic
Integrity to Support Aquatic Life Use
Assessments
BACKGROUND
Maryland (Department of the Environment, Department of Natural Resources), Virginia
(Department of Environmental Quality) and U.S. EPA (Region 3 Water Protection
Division and Chesapeake Bay Program Office) reached agreement on the protocol to
assess Chesapeake Bay benthic community health using a Benthic-Index of Biotic
Integrity (B-IBI) (see Appendix J in U.S. EPA 2007a). This chapter documents an
interim rule for an assessment protocol supporting the two states' evaluation of
Chesapeake Bay benthic community data as part of their 305(b)/303(d) Integrated
Reports. This assessment protocol builds directly on the more detailed assessment
methods recommended by Llanso et al. 2005 (see Appendix K in U.S. EPA 2007a).
Managers and practitioners of the B-IBI in the Chesapeake Bay Program partnership
have found several Chesapeake Bay segments consistently classified as unimpaired
while having degraded B-IBI scores coincident with high variability in the segment data
informing those scores. The managers and practitioners, using best professional
judgement, worked with U.S. EPA to use apply an interim rule that reclassified these
special case assessment results into a regulatory Clean Water Act (CWA) 303(d)
impairment listing of 'insufficient available data and/or information to make a use
support determination'.
Coincident with the interim rule decision, a recalibration of the B-IBI was initiated in
2014 that was anticipated to support a more robust scoring of Chesapeake Bay segments,
alleviating the need to apply the interim rule. A recalibrated B-IBI was anticipated to
improve the decision support tool. However, in 2016, the recalibration efforts with the
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B-IBI produced lower classification efficiencies (Llanso et al. 2016 - Appendix G in this
document). The application of a revised B-IBI tool with new lower classification
efficiencies was not supported by the Chesapeake Bay Program partners through a
decision by the Chesapeake Bay Program's Criteria Assessment Protocol Workgroup.
Therefore, the interim 303(d) listing rule for segments that follow the special case
conditions noted by CBP partners during past assessments (i.e., B-IBI scores that suggest
degraded conditions yet result in unimpaired status assignments affected by wide
variability in the sample scores informing the B-IBI score) is recommended to remain in
effect at this time.
REVIEW OF INDEX RECALIBRATION RESULTS
The annual Chesapeake Bay benthic macroinvertebrate community health assessment
supports Maryland's and Virginia's tidal waters Clean Water Act 303(d) listing decisions
for the Aquatic Life designated use. The assessments are separate from the Chesapeake
Bay water quality criteria attainment assessment determinations. B-IBI results provide
stand-alone or supplemental information for the two states to use in making their CWA
Section 303(d) listing cycle decisions (U.S. EPA 2007). The application of the B-IBI
methodology assures bay-wide consistency in determinations of estuarine benthic
community impairments.
Recent CWA Section 303(d) Chesapeake Bay tidal water aquatic life designated use
assessments showed four Chesapeake Bay segments with what managers and
practitioners considered conflicting results. The four segments expressed two
characteristics of concern: 1) a low mean B-IBI score {<2.1) typically associated with
impaired status classification; and 2) high variability in sample results (minimum sample
size is 10 for an assessment) producing wide confidence intervals on the B-IBI segment
assessment.
The CBP's Criteria Assessment Protocol Workgroup considered these results in the
context of B-IBI development history. The B-IBI was last validated for tidal freshwater
and oligohaline habitats by Alden et al. (2002). The limits of the data available at that
time made the index less robust in the tidal freshwater and oligohaline regions than in
the more saline habitats of the mesohaline and polyhaline region (R. Llanso, VERSAR
Inc., and D. Dauer, Old Dominion University, Personal Communication). In addition,
some performance issues for determining the B-IBI scores have been identified
throughout the years of its use (R. Llanso, VERSAR Inc., and D. Dauer, Old Dominion
University, Personal Communication). The issues of concern have included:
1. When applied to small embayments, correct classification levels are lower than
those of the initial calibration effort.
2. Differences in pollution-indicative and pollution-sensitive species lists have been
identified among the different salinity habitats, which affect index performance
depending on which salinity habitat the index is being applied.
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68
3. Low mesohaline regions with abundant clam beds are very productive. The B-IBI
biomass metric receives a "1" for excess biomass, but in these regions excess
biomass is a desirable property of the community and, thus, thresholds need
adjustment for these regions.
4. Benthic communities respond differently to low dissolved oxygen compared to
sediment contaminants. Diagnostic approaches have been developed to determine
sources of anthropogenic stress; however, large data sets that were unavailable to
Weisberg et al. (1997) but are now available and can be used today to calibrate the
B-IBI for diagnostic purposes.
The Chesapeake Bay Program's Criteria Assessment Protocol Workgroup recognized
that most of these issues were under review. A B-IBI recalibration process was initiated
in 2014. In order for Chesapeake Bay Program tidal water partners to make improved
determinations about water quality status in the aquatic life use, interim rules were
developed by the Criteria Assessment Protocol Workgroup and agreed by Maryland,
Virginia, and EPA for application until the above issues are fully addressed through new
research findings. Subsequently published updates to the B-IBI assessment protocol
would be made available for adoption into the State's Chesapeake Bay water quality
standards.
This chapter recognizes this suite of issues of concern that are affecting the use of the
Chesapeake Bay B-IBI in water quality status assignments of the tidal water aquatic life
designated use. Interim decision rules to support a water quality status assignment to a
segment assessment have been agreed upon between Maryland, Virginia and EPA. The
rules are intended to be interim until new research provides a more robust B-IBI tool
than the existing tool and is approved and adopted for use by the CBP partnership.
WATER QUALITY STATUS CLASSIFICATIONS
EPA encourages States or Tribes to use a five-category system for classifying all water
bodies (or segments) within its boundaries regarding the waters' status in meeting the
State's/Tribe's water quality standards (Table VI-1). The classification system uses
designated uses as the basis for reporting on water quality.
The waters from Category 5 constitute the federal Clean Water Act Section 303(d) list
of impaired or threatened waters within the State/Tribe's boundaries. EPA developed the
multi-category classification system to help States/Tribes to report on incremental
progress toward attaining water quality standards. States/Tribes may establish additional
subcategories to refine their classifications further. For example, under Category 3,
subcategories could be used to distinguish between segments for which no
data/information is available and segments for which data/information is available but
insufficient for making a use-support determination.
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Table VI-1. U.S. EPA's 5-category system for classifying water quality status used as the basis for
reporting water quality for Clean Water Act Section 303(d) listing assessments.
Classification Category
for Water Quality Status
Description
Category 1
All designated uses are supported; no use is threatened.
Category 2
Available data and/or information indicate that some, but not all,
designated uses are supported.
Category 3
There is insufficient available data and/or information to make a
use support determination.
Category 4
Available data and/or information indicate that at least one
designated use is not being supported or is threatened, but a
TMDL is not needed
Category 4a
A State developed TMDL has been approved by EPA or a
TMDL lias been established by EPA for any segment-pollutant
combination.
Category 4b
Other required control measures are expected to result in the
attainment of an applicable water quality standard in a
reasonable period of time.
Category 4c
The non-attaimnent of any applicable water quality standard for
the segment is the result of pollution and is not caused by a
pollutant.
Category 5
Available data and/or information indicate that at least one
designated use is not being supported or is threatened, and a
TMDL is needed.
Source: Clean Water Act Section 303(d).
INTERIM RULES FOR DEFINING CHESAPEAKE BAY
AQUATIC LIFE USE WATER QUALITY STATUS
The below recommended interim decision rules address the most inconsistent, unreliable
water quality status classifications output from the Chesapeake Bay B-IBI. To develop
these interim rules, the Chesapeake Bay Program's Criteria Assessment Protocol
Workgroup considered the characteristics of B-IBI results used to classify the status of
Chesapeake Bay segments aquatic life designated use. The Chesapeake Bay B-IBI
assessment methodology incorporates uncertainty in defining the reference condition.
The B-IBI methodology is based on the confidence limit and bootstrap simulation
concept described in Alden et al. (2002). Bootstrap simulation (Efron and Tibshirani
1998) is applied to incorporate uncertainty in reference conditions as well as sampling
variability in the assessment data. For each habitat, a threshold based on percentiles in
an unimpaired reference data set will be applied (i.e. 5th percentile). This threshold is
not intended to serve as criterion for classifying individual B-IBI scores, rather it is used
to categorize the segment as impaired or not based on the proportion of samples below
the threshold and the variance associated with this estimate
The impairment assessment for each segment is based on the proportion of samples
below the threshold with the variance in this proportion estimated by simulation. In each
simulation run, a subset of the reference "unimpaired" data for each habitat is selected
at random, and the threshold is determined (i.e., the B-IBI score at the 5th percentile of
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70
the un-impaired dataset). A random subset of the assessment data is compared to the
threshold value to estimate the proportion of sites below the threshold. By repeating this
process over and over again (2000 runs) an estimate of the variance in the proportion of
sites below the threshold is derived from the bootstrapped estimates.
For this analysis, it is assumed that each reference 'un-impaired" data set (by habitat) is
a representative sample from a "super population" of reference sites. The assessment
result for each benthic segment (i.e., percent of area with IBI score below 5th percentile
threshold) is then statistically compared (p<0.05) with the percentage that would be
expected even if the segment is unimpaired.
Specific considerations in forming the interim rules, therefore, focused on the B-IBI
score and variability associated with the confidence intervals on the score. Based on best
professional judgement input from management practitioners using the B-IBI to support
303(d) listing decisions among the Chesapeake Bay state partners, the Chesapeake Bay
Program's Criteria Assessment Protocol Workgroup used the difference of 0.5 B-IBI
units between confidence interval limits on a segment score as a decision threshold for
defining segments where the B-IBI score deserved further investigation. This magnitude
of the confidence limit on the B-IBI was consistent with high variability in segments
scores. Second, high variability coincident with a mean B-IBI score of 2.7 was used as a
decision threshold because this value was the typical B-IBI score decision threshold for
impairment status of a management segment in Chesapeake Bay.
The resulting interim rules recommended for Chesapeake Bay B-IBI aquatic life
designated use assessment, are:
• For segments where the CWA Section 303(d) listing classification results are
"Impaired = No", Maryland and Virginia would identify those segments that also
have a breadth of confidence limits ((Upper confidence Limit) - (Lower confidence
Limit)) > 0.5) of 0.5 or greater.
• Of that subset of segments with confidence limits > 0.5, those that also have a Mean
B-IBI <2.7 would be classified as Category 3 (insufficient information) until more
conclusive information is available.
• Virginia refines this rule classification further such that a segment will be classified
as Category 3B when the analysis suggests non-impairment but the difference
between the upper and lower 95% confidence limits equals or exceeds 0.5 and the
average B-IBI score is less than 2.7, or, when the number of sites sampled during the
six-year data window is less than 10, (i.e., where some data exist but are insufficient
to determine support of the designated uses).
The application of this set of decision rules affects four Chesapeake Bay segments in the
most recent 303(d) listing assessment. In Virginia, it affects the Corrotoman Mesohaline
(CRRMH), South Branch Elizabeth River Mesohaline (SBEMH), and York River
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71
Polyhaline (YRKPH). In Maryland, it affects the Sassafras River Oligohaline (SASOH).
These four segments that have been previously considered unimpaired will now be
classified as Category 3 in Maryland and Category 3B in Virginia (Table VI-2).
An update of the water quality standards classification table supporting decisions
involving the aquatic life use in Chesapeake Bay water quality standards assessments
consistent with the application of the recommended interim decision rules is provided in
Table VI-2.
Table VI-2. Updated application of U.S. EPA 5-category system for classifying Chesapeake Bay aquatic
life use water quality status as the basis for reporting water quality for Clean Water Act section
303(d) listing assessments1.
Classification
Category for
Water
Quality
Status
Description
Category 1
All designated uses are supported; no use is threatened.
Category 2
Available data and/or information indicate that some, but not all, designated uses are
supported.
Category 3
All jurisdictions: There is insufficient available data and/or information to make a use
support determination.
Category 3 a
VA: no data are available within the data window of the current assessment to determine if
any designated use is attained and the water was not previously listed as impaired.
Category 3b
VA: some data exist but are insufficient to determine support of designated uses. Such
waters will be prioritized for follow up monitoring, as needed.
Category 3 c
VA: data collected by a citizen monitoring or another organization indicating water quality
problems may exist but the methodology and/or data quality has not been approved for a
determination of support of designated use(s). These waters are considered as having
insufficient data with observed effects. Such waters will be prioritized by Department of
Environmental Quality for follow up monitoring.
Category 3d
VA: data collected by a citizen monitoring or other organization indicating designated use(s)
are being attained but the methodology and/or data quality has not been approved for such a
determination.
Category 4
Available data and/or information indicate that at least one designated use is not being
supported or is threatened, but a TMDL is not needed.
Category 4a
A State developed TMDL has been approved by EPA or a TMDL has been established by
EPA for any segment-pollutant combination.
Category 4b
Other required control measures are expected to result in the attainment of an applicable
water quality standard in a reasonable period of time.
Category 4c
Hie non-attainment of any applicable water quality standard for the segment is the result of
pollution and is not caused by a pollutant.
Category 5
Available data and/or information indicate that at least one designated use is not being
supported or is threatened, and a TMDL is needed.
1. Agreed to by the Chesapeake Bay Program's Criteria Assessment Protocol Workgroup and
approved by the Chesapeake Bay Program's Water Quality Goal Implementation Team in 2013.
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LITERATURE CITED
Alden, R.W. Ill, D.M. Dauer, J.A. Ranasinghe, L.C. Scott, and R.J. Llanso. 2002. Statistical
verification of the Chesapeake Bay Benthic Index of Biotic Integrity. Environmetrics
13:473 498.
Efiron, B. and R. Tibshirani. 1998. An Introduction to the Bootstrap. Chapman & Hall/CRC.
Llanso, R.J., J.H. Volstad, and D.M. Dauer. 2003. Decision Process for Identification of
Estuarine Benthic Impairments. Final Report submitted to Maryland Department of
Natural Resources, Tidewater Ecosystem Assessments, Annapolis, Maryland, by Versar,
Inc., Columbia, Maryland.
Llanso, R.J., D.M. Dauer, and M.F. Lane. 2016. Chesapeake Bay B-IBI recalibration.
August 2016 report to Virginia Department of Environmental Quality. Deliverable to the
U.S. EPA Chesapeake Bay Program. 31pp.
U.S. EPA (U.S. Environmental Protection Agency). 2007. Ambient Water Quality Criteria
for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake Bay and Its
Tidal Tributaries - 2007 Addendum. July 2007. EPA 903-R-07-003. Region III
Chesapeake Bay Program Office, Annapolis, MD.
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73
ACRONYMS
2-D
two-dimensional
ANATF
Anacostia Tidal Fresh
B-IBI
benthic index of biotic integrity
CBP
Chesapeake Bay Program
CIMS
Chesapeake Information Management System
CFD
cumulative frequency distribution
CHLA
chlorophyll a
CONMON
continuous monitoring
CRC
Chesapeake Research Consortium
DC
deep channel
DW
deep water
EMAP
Environmental Monitoring and Assessment Program
EPA
U.S. Environmental Protection Agency
GIS
Geographic Information System
GLM
Generalized linear Model
HRSD
Hampton Roads Sanitation District
km2
square kilometers
m
meters
mg/L
milligrams per liter
MRAT
Monitoring Realignment Action Team
NA
not applicable
NGZ
designated SAV no grow zone
OW
open water
PAXTF
Patuxent River Tidal Fresh
S
surface
SAS
Statistical Analysis Software
SAV
Submerged Aquatic Vegetation
SD
Standard Deviation
STAC
Scientific and Technical Advisory Committee
TMDL
Total Maximum Daily Load
VADEQ
Virginia Department of Environmental Quality
VIMS
Virginia Institute of Marine Science
-------
74
APPENDIX A
Conditional Probability Analysis Support
The first section of this appendix reviews the conditional probability analysis of Elgin
Perry assessing protection of the 7-day mean dissolved oxygen open water criterion
provided by the 30-day mean dissolved oxygen criterion originally documented in the
CBP STAC (2012) publication on the umbrella criteria assessment. The second section
of this appendix furthers the analysis through a parametric simulation approach to
assessing the umbrella concept for assessing simultaneous protection of the 30-day
mean for the instantaneous minimum dissolved oxygen criterion.
CONDITIONAL PROBABILITY ANALYSIS BETWEEN
THE 30-DAY AND 7-DAY MEAN DISSOLVED OXYGEN
CONCENTRATIONS
Perry conducted a conditional probability analysis between the 30-day mean dissolved
oxygen concentrations compared with the 7-day mean dissolved oxygen concentrations
(see Appendix 2 in CBP STAC 2012) using high temporal density tidal Potomac River
continuous monitoring data sets to assess conditions support mutual habitat protection.
The results support that it would be a rare situation where the 30-day mean dissolved
oxygen criterion would be satisfied and the 7-day mean dissolved oxygen criterion
would be violated more than 10 percent of the time.
The method employed is based on the approach that if the variability of the 7-day mean
about the 30-day mean has a standard deviation less than 0.7805, then we can expect
that the 7-day mean dissolved oxygen criterion will be violated less than ten percent of
the time if the 30-day mean dissolved oxygen criterion is being met (Figure A-l).
To use this approach, an estimate of the standard deviation of the 7-day mean about the
30-day mean is needed. To estimate this quantity, Perry used data from the tidal
Potomac River continuous monitoring locations (Table A-l, Figure A-2).
Table A-1. Names, locations, and years of continuous monitoring data used in this analysis.
Location
Latitude
Longitude
Years
Occoquan
38.64038
-77.219416
2007-2009
Pohick Creek
38.67591
-77.16641
2007-2009
Potomac Creek
38.3436
-77.30485
2007-2009
Monroe Bay
38.23197
-76.96372
2007-2009
Nomini Bay
38.1316
-76.71759
2007-2009
Yeocomico River
38.02878
-76.55184
2007-2009
Fenwick
38.66993333
-77.11513333
2004-2008
Piscataway Creek
38.70156667
-77.02593333
2004-2008
Mattawoman Creek
38.55925
-77.1887
2004-2008
-------
75
Figure A-1. Illustration of the level of variability of the 7-day mean about the 30-day mean that results
in up to 10 percent violations of the 7-day mean dissolved oxygen criterion when the 30-day mean
dissolved oxygen criterion is met.
Beginning with the first collection day for each year at each location, blocks of 30 days
were created to represent months. Partial months at the end of each collection year
were counted as a month. Similarly, weeks were created by starting with the first
collection day of each year and counting off blocks of 7 days. With these definitions,
monthly means were computed as the arithmetic average of dissolved oxygen
concentration measurements for each month. Weekly means were computed as the
arithmetic average of dissolved oxygen concentration measurements for the
intersection of month and week. Thus, a week that bridges across two months would
have its data divided by month and a weekly mean computed for each part. Weekly
means and monthly means were merged by month and a residual computed by
subtracting the monthly mean from each weekly mean computed within that month.
Various analyses were conducted on these residuals to assess the variability of weekly
means about the monthly mean (see Appendix 2 in CBP STAC 2012). Graphical
analyses were used to assess the uniformity of variation over other factors. Distribution
functions and quantile estimation was used to estimate the rate of violation of the 7-
day mean dissolved oxygen criterion given that the 30-day mean dissolved oxygen
criterion was satisfied.
The results suggest that we would only see greater than 10 percent violations of the 7-
day mean criterion given that they 30-day criterion is met if the 30-day mean were
hovering at or just above the 30-day mean criterion. Because the 30-day mean rarely
exhibits this behavior, it seems safe to conclude that in most cases the 30-day mean
dissolved oxygen criterion acts to protect habitat under the 7-day mean dissolved
oxygen criterion measure as well. However, slight increases in the variation of the
-------
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this analysis.
mean about the 30-day mean without corresponding increases in the 30-day mean
could start to increase the violation rate for the 7-day criterion to above 10 percent.
Sampling Variability: Sampling Effort Effects the Mutual Criteria
Attainment Assessment
As stated above, the Umbrella Criteria Assessment Team under the CBP Scientific,
Technical Assessment and Reporting Team reviewed the variabi lity of the 7-day mean
dissolved oxygen about the 30-day mean dissolved oxygen and concluded that in
general, that if the 30-day dissolved criterion is satisfied by the 30-day mean, then there
is less than a 10 percent chance that the 7-day mean dissolved oxygen criterion will be
violated by the 7-day mean dissolved concentration. This conclusion is based on
having very accurate estimates of both the monthly mean and the weekly mean derived
from near continuous (e.g. every 15 minutes) high frequency observations of dissolved
oxygen.
However, in many parts of the Chesapeake Bay and its tidal tributaries, the monthly
mean is estimated from as few as one to two point observations per month. Because
the uncertainty of a 30-day mean from two observations is much greater than the
uncertainty of a 30-day mean from near continuous data, it is reasonable to expect that
effectiveness of the mutual habitat protection of the 30-day mean criterion for the 7-
day mean criterion will change when the low sample size mean is employed. The
Umbrella Criteria Assessment Team examined the additional uncertainty that is created
-------
77
by the use of small sample size and further evaluate the consequences of this
uncertainty for the conditional attainment assessment approach.
This study evaluates the additional uncertainty from low sample sizes by resampling
from near continuous records in a manner that simulates the twice monthly sampling
of routine cruises. The near continuous dissolved oxygen concentration time series
records used are from the tidal Potomac River continuous monitoring data collected by
the Chesapeake Bai Shallow-Water Water Quality Monitoring Program. For each
calendar month in the May 1 through September 30 period of each record, a random
day between 1 and 15 was chosen as the first sampling day of the month. To get a
second sampling day, a random increment from 10 to 16 was generated and added to
the first. In the event that there was no data on this second day, then the last day of the
month with data was used. For each selected day, a random selection from the roughly
24 observations taken between 9:00 a.m. and 3:00 p.m. was chosen as the point
estimate. These two estimates were summed and divided by 2 to obtain the monthly
mean estimate. This simulation was repeated 20 times to obtain 20 monthly mean
estimates for each station and month.
Months were calendar months, and weeks were designated as sequential weeks
beginning January 1st of each year. Weekly means were computed for each unique
combination of month and week. Thus, if a month terminus divided a week, then the
week was divided at this point and the resulting partial weeks were assigned to the two
months. Deviations of the weekly means about the monthly mean were computed as
(weekly mean dissolved oxygen - monthly mean dissolved oxygen) for weeks that
occur within a month. In all cases, the weekly mean dissolved oxygen was computed
as the mean of all high frequency observations within a week and is referred to as the
near true weekly mean.
The monthly mean was computed two ways. A near true estimate of the monthly mean
uses all observations in the near continuous record; a small sample estimate of the
monthly mean uses only two observations as described by the resampling methods
above.
The root mean square error (rmse) was computed across months, years, and stations
for both the near true deviations and the small sample deviations. These root mean
square estimates quantify the standard deviation of the 7-day mean about the 30-day
mean for both the near true case and the small sample estimate case. The increase in
the rmse for small sample case relative to the near true case illustrates the loss of
precision in estimating the monthly mean by small samples. Using these estimates of
standard deviation and assuming a normal distribution for these deviations, we estimate
the probability that the 7-day mean is less than 4.0, the 7-day mean criterion, while the
30-day mean is 5.0, the 30-day mean criterion. This probability is a measure of the
efficacy of the 30-day mean criterion as a measure of conditional dissolved oxygen
criterion attainment for the 7-day mean criterion.
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78
Descriptive statistics for the true weekly deviations and the small sample deviations
show a negative bias of small sample deviations relative to the true deviations (Table
A-2). This shows that the resampled monthly means which use daytime data only tend
to be biased high, but on average this effect is not large. The range of the mean of the
deviations over the resampling experiments is (-0.3428 -0.0133). The variability of the
small sample deviations is much greater than that of the near true deviations. The true
deviations have an rmse very close to 1.0 while the rmse from the small sample
deviations always exceeds 1.6 and in one case exceeds 1.9 indicating a 60 to 90 percent
increase in variability (Table A-3).
Table A-2. Summary of comparing weekly DO means to monthly DO means for 'true' means and
monthly means from 20 small sample resampling experiments.
Simulation
Sample
size
Mean
Rmse
Minimum
q25
Median
q75
Maximum
true
833
0.0017
1.005
-4.18
-0.4816
0.0125
0.4828
3.2042
1
833
-0.1344
1.6578
-5.1447
-0.9944
-0.0542
0.8052
4.9893
2
833
-0.0247
1.6903
-5.6588
-0.8519
0.0165
0.8543
4.4843
3
833
-0.2745
1.7132
-6.684
-1.1194
-0.1775
0.6852
4.4353
4
833
-0.2187
1.8037
-7.9388
-0.9968
-0.0879
0.7284
5.3265
5
833
-0.1723
1.8766
-8.2638
-0.9699
-0.0726
0.8603
4.9031
6
833
-0.0666
1.6177
-5.379
-0.8897
-0.0173
0.7745
4.6073
7
833
-0.2252
1.7196
-6.8519
-1.066
-0.2264
0.6948
5.3679
8
833
-0.0133
1.6054
-5.4517
-0.7627
0.0211
0.8046
5.1295
9
833
-0.3428
1.7471
-6.3008
-1.1947
-0.2999
0.5542
4.3745
10
833
-0.1639
1.7156
-7.3597
-1.0652
-0.1465
0.8385
4.7042
11
833
-0.0948
1.7555
-5.7288
-1.0169
-0.0054
0.8369
5.0334
12
833
-0.2193
1.9286
-7.2316
-1.0929
-0.0793
0.7621
5.5595
13
833
-0.2014
1.692
-6.5302
-1.0818
-0.0624
0.7351
5.1557
14
833
-0.1747
1.6198
-6.2597
-1.063
-0.1254
0.8021
3.9682
15
833
-0.1424
1.7216
-6.3428
-1.0468
-0.1171
0.8693
4.8051
16
833
-0.1055
1.7055
-6.114
-1.0153
0.0278
0.9094
4.3039
17
833
-0.1663
1.8126
-6.424
-1.1035
-0.107
0.7703
4.6611
18
833
-0.2157
1.8397
-6.3407
-1.1281
-0.1486
0.8262
5.2234
19
833
-0.0624
1.7048
-5.3103
-1.0217
-0.0165
0.8549
4.7011
20
833
-0.2306
1.7493
-8.2242
-1.1226
-0.1713
0.7209
4.2593
The distribution of the true weekly deviations tends to follow the normal distribution
closely for the bulk of the observations (Figure A-3). However, there is a small
percentage of outliers at both the upper end and the lower end of the distribution that
are more extreme than are expected for the normal distribution. Because of this heavy
tailed feature of the true deviations, when the normal distribution is used to compute
probabilities for this problem, these probabilities may be a slight underestimate of the
true probabilities. There appear to be 10 to 15 extreme outliers in the lower tail of the
distribution and thus the probability bias may be 1.2 to 1.8 percent.
-------
The weekly deviations computed using the small sample monthly mean estimates
appear to fit the normal distribution better than the true week deviations (Figure A-4).
The variability of deviations in the small sample experiment is clearly greater than
variability for the true deviations. Compare for example the frequency of observation
where the weekly mean is greater than 2 units below the monthly mean between Figures
A-3 and A-4.
distribution plots
normal probability plot
boxplot
CN -
CN -
"O
V)
CN -
o « -
^ -
0
—
-2 -1
expected
histogram
density plot
r~
o
observed
\b-
T
4 -2 0
observed
Figure A-3 Distribution plots for the true weekly deviations.
-------
80
distribution plots
normal probability plot boxplot
CN
O
¦3
-2
¦1
0
1
2
3
expected
"T"
4
histogram
1 1—
2 0
observed
density plot
observed
Figure A-4. Distribution plots for weekly deviations computed for the first resampling experiment.
Table A-3. Estimates of risk of violating the 7-day mean dissolved oxygen criterion given the monthly
mean estimate (column 1) and four levels of sampling variation (columns 2-5) illustrating the risk of
violating the 7-day mean dissolved oxygen criterion.
30-Day Mean Dissolved
Oxygen Concentration
Risk of Violating 7-day Mean Criterion
True1
SD=1.73582
SD=1.60543
SD=1.92874
5.0
0.1598
0.2822
0.2666
0.3020
5.1
0.1368
0.2631
0.2466
0.2842
5.2
0.1162
0.2446
0.2273
0.2669
5.3
0.0979
0.2269
0.2090
0.2501
5.4
0.0818
0.2099
0.1915
0.2339
5.5
0.0677
0.1937
0.1750
0.2183
5.6
0.0556
0.1783
0.1594
0.2033
5.7
0.0453
0.1636
0.1448
0.1890
5.8
0.0366
0.1498
0.1311
0.1753
5.9
0.0293
0.1368
0.1183
0.1622
6.0
0.0232
0.1246
0.1064
0.1498
6.1
0.0183
0.1131
0.0954
0.1381
6.2
0.0142
0.1024
0.0852
0.1269
6.3
0.0110
0.0925
0.0759
0.1165
6.4
0.0084
0.0833
0.0674
0.1066
6.5
0.0064
0.0748
0.0597
0.0974
Notes: Column 1 assumes near true weekly deviations, column 2 assumes variation for the
average of 20 small sample estimates of the monthly mean, column 3 assumes variation at
the minimum of the 20 small sample estimates of the monthly mean and column 4 assumes
variation at the maximum of 20 small sample estimates of the monthly mean.
1. Standard deviation of true weekly mean from true monthly mean.
-------
81
2. Standard deviation base on pooling 20 resampling estimates.
3. Standard deviation based on minimum of 20 resampling estimates.
4. Standard deviation based on maximum of 20 resampling estimates.
A Parametric Simulation Approach to Assessing the Umbrella
Concept for the Instantaneous Minimum Criterion
High frequency samples of dissolved oxygen at fixed locations show that there is
considerable serial dependence or autocorrelation in these dissolved oxygen time
series. This lack of independence makes it difficult to analytically compute the
probability that an instantaneous minimum dissolved oxygen criteria will be violated
when an umbrella criterion (e.g. 7-day or 30-day mean) is satisfied to support
conditional attainment assessments. Here we develop and show results from a
simulation approach to addressing this question.
The basic approach of the simulation is to generate time series that have properties
similar to observed dissolved oxygen time series. The data used for this exercise are
the open-water buoy data compiled by Olson (see U.S. EPA 2004; Table C-l in
Appendix C this document). In these data, time series that are more than 1 week in
length were parsed into 1-week time series. A simple AR(2) model that included
structural terms for the mean, linear trend, and diel cycle was fitted to each of these
time series using Proc AutoReg in SAS. Each fitting results in a vector of 7 parameters:
• b int - the intercept which reflects the mean because other covariates are
centered
• b cday - linear trend term for the week fitted as a coefficient of centered day
• b sin, b cos - coefficients for diel trend fitted to trig-transformed time
• b_arl,b_ar2 - autoregressive terms at lags 1 and 2
• mse - residual mean square error
These parameter estimates were obtained for each 1-week time series to yield 251 sets
of parameters. These 251 vector observations were analyzed by Multivariate Analysis
of Variance (MANOVA) using Proc GLM in SAS. The model included terms for
Month, Total Water Depth, Sensor Depth, Latitude and Longitude. Some results from
this overall model are presented.
For the simulation, only data from Chesapeake Bay Segment CB4MH in the surface
layer (sensor < 10 m depth) were used. A MANOVA model which included terms for
Month, Total Water Depth, and Sensor Depth. Coefficients from this model were used
to estimate a mean predicted value for the parameter vector which seeded the
parametric simulation. A multivariate normal random number generator (R-package)
was used to generate 1000 realizations using this mean vector and the
VarianceCovariance matrix estimate from the MANOVA. Each of these 1000
realizations of the parameter vector were passed to a function which estimated a 1-
week time series based on the simulated parameter vector values. The percent of
violations of the instantaneous minimum dissolved oxygen criterion (3.2 mg/L) were
-------
82
tabulated yielding 1000 estimates of this percentage. The range and frequency of these
percentages are compared for various mean vectors associated with different conditions
specified by different values of the independent variables in the MANOVA model.
When examining data from all buoy locations, in a multivariate sense, all of these terms
are statistically significant (Table A-4). Table A-5 shows which independent variables
appeared to have an effect on which dependent variables. Table B-6 shows dissolved
oxygen seems to improve as water depth increases, dissolved oxygen degrades as
sensor depth increases, AR1 terms are stronger in the western bay and mse decreases
with sensor depth.
Table A-4. Manova test results for dependent vector (bjnt, b_cday, b_sin, b_cos, b_AR1, b_AR2,mse).
Source
Pillai's
Trace
Pr > F
month
0.2895
0.0191
TotDep
0.1018
0.0007
SampDep
0.2063
<.0001
lat
0.0592
0.0451
long
0.2102
<.0001
Table A-5. P-values for each manova term and for each dependent variable.
Source
bjnt
b_cday
b_sin
b_cos
b_AR1
b_AR2
mse
month
0.0861
0.9041
0.3811
0.4845
0.0130
0.0909
0.1277
TotDep
<.0001
0.4168
0.9888
0.7560
0.1728
0.2066
0.1374
SampDep
<.0001
0.4214
0.0381
0.5415
0.1808
0.2711
0.0331
lat
0.2065
0.3651
0.2688
0.0563
0.9958
0.2387
0.1713
long
0.7956
0.0432
0.9265
0.9906
<0001
0.2204
0.0290
Table A-6. Coefficient estimates for covariates.
Source
bjnt
b_cday
b_sin
b_cos
b_AR1
b_AR2
mse
TotDep
0.2224
0.0060
0.0001
-0.0031
-0.0106
0.0080
0.0148
SampDep
-0.4079
-0.0072
0.0309
-0.0074
0.0125
-0.0083
-0.0255
Lat
-0.2449
0.0244
-0.0496
0.0703
0.0001
0.0271
0.0493
Long
0.1058
-0.1157
0.0087
-0.0009
-0.3149
0.0595
0.1666
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83
From Table A-7, the partial correlation coefficients from the error SSCP matrix show
the strongest correlation is among parameters that model the error process. The
autoregressive terms b_ARl and b_AR2 have an inverse dependence. The mse term
is correlated with the AR terms and with bcos and b cday. There is little correlation
among terms that model the mean (i.e., b int, b cday, b sin, b cos).
Table A-7. Partial Correlation Coefficients from the Error SSCP Matrix / Prob > Irl DF = 239 .
b_lnt
b_cday
b_sin
b_cos
b_AR1
b_AR2
MSE
b_Int
1.000000
-.052225
0.4206
-.116969
0.0705
0.113032
0.0805
0.252967
<.0001
-.225183
0.0004
-.078779
0.2240
bcda
y
-.052225
0.4206
1.000000
0.128183
0.0473
-.019640
0.7621
0.083167
0.1992
-.026105
0.6874
-.132840
0.0398
bsin
-.116969
0.0705
0.128183
0.0473
1.000000
-.074374
0.2511
-.296165
<.0001
0.205687
0.0014
0.020856
0.7479
bcos
0.113032
0.0805
-.019640
0.7621
-.074374
0.2511
1.000000
0.095132
0.1417
-.089933
0.1649
-.185441
0.0039
b AR
1
0.252967
<.0001
0.083167
0.1992
-.296165
<.0001
0.095132
0.1417
1.000000
-.816881
<.0001
-.297462
<.0001
b AR
2
-.225183
0.0004
-.026105
0.6874
0.205687
0.0014
-.089933
0.1649
-.816881
<.0001
1.000000
0.264092
<.0001
MSE
-.078779
0.2240
-.132840
0.0398
0.020856
0.7479
-.185441
0.0039
-.297462
<.0001
0.264092
<.0001
1.000000
Using the manova model for Chesapeake Bay Segment CB4MH we can obtain a
predicted value of the time series parameter vector as a function of month, water depth,
and sensor depth. In this simulation, month, water depth, and sensor depth were chosen
for which the mean dissolved oxygen is just greater than the 30-day mean criterion of
5.0 mg/L.
The independent variable vector that yields this prediction is:
Water
Sensor
May
June
July
Aug
Sept
Oct
Depth
Depth
0
0
l
0
0
0
10
6
for which the predicted vector of time series parameters is:
b_Int
bcday
bsin
bcos
b_ARl
b_AR2
mse
5.0058
-0.0493
-0.4072
-0.0527
0.9333
-0.0319
0.3164
This predicted vector and the estimated Variance-Covariance matrix is used to seed a
multivariate normal random number generator that creates 1000 realizations of the time
series parameter vector. A one-week time series 15-minute observations is generated
for each realization. The b_Int term of this predicted vector is the weekly mean of the
one-week time series. Based on the 15-minute observations, the percent of
observations below the instantaneous minimum criterion is computed. The conditional
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84
probability concept is assessed by comparing the true monthly mean (5.0058), the
simulated weekly means (b_Int) in the 1000 realizations, and the violation rates of the
instantaneous minimum dissolved oxygen criterion.
By changing the sensor depth of the independent variable vector, the long term mean
can be adjusted to assess the effect of this parameter on the relationship among the
three criteria assessments. Thus, by raising the sensor depth from 6 m to 3 m the mean
dissolved oxygen concentration is increased from 5.0058 to 7.0082 mg/L (Table A-8).
The time series parameters for diel signal and the mse term increase as well. The linear
trend term and the AR terms remain fairly constant.
Table A-8. Time series parameters sensitivity to changes in sensor depth.
Depth
Sensor
b Int
bcday
bsin
bcos
b_ARl
AR2
Mse
6
5.0058
-0.0493
-0.4072
-0.0527
0.9333
-0.0319
0.3164
5
5.6733
-0.0476
-0.5114
0.0094
0.9328
-0.0294
0.4112
4
6.3408
-0.0460
-0.6156
0.0714
0.9324
-0.0268
0.5060
3
7.0082
-0.0443
-0.7198
0.1335
0.9320
-0.0243
0.6008
To compare violation rates of the 7-day mean criterion and instantaneous minimum
criterion, we cross tabulate cases where the 7-day mean is less than 4.0 mg/L against
cases where the violation rate of the instantaneous minimum exceeds 10 percent in each
1-week time series.
Table A-9. Sensor depth with mean dissolved oxygen and criterion failure rates.
a)
Sensor Depth = 6
7-day mean
7-day mean
marginal failure
mean DO = 5.0058
>4.0
<4.0
instantaneous
minimum
failure Instantaneous
520
4
524
minimum < 10%
62.35%
2.41%
52.4%
failure Instantaneous
314
162
476
minimum > 10%
37.65%
97.59%
47.6%
marginal for failure
of 7-day mean
834
166
1000
b)
Sensor Depth = 5
mean DO= 5.6733
7-day mean
>4.0
7-day mean
<4.0
marginal failure
instantaneous
minimum
failure Instantaneous
minimum < 10%
671
71.01%
4
7.27%
675
67.5%
failure Instantaneous
minimum > 10%
274
28.99%
51
92.73%
325
32.5%
marginal for failure
of 7-day mean
945
55
1000
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85
c)
Sensor Depth = 4
mean = 6.3408
7-day mean
>4.0
7-day mean
<4.0
marginal failure
instantaneous
minimum
failure Instantaneous
minimum < 10%
747
75.84%
0
0%
747
74.7%
failure Instantaneous
minimum > 10%
238
24.16%
15
100%
253
25.3%
marginal for failure
of 7-day mean
985
15
1000
Sensor Depth = 3
mean = 7.0082
7-day mean
>4.0
7-day mean
<4.0
marginal failure
instantaneous
minimum
failure Instantaneous
minimum < 10%
815
81.91%
0
0%
815
81.5%
failure Instantaneous
minimum > 10%
180
18.09%
5
100%
185
18.5%
marginal for failure
of 7-day mean
995
5
1000
When the long term mean dissolved oxygen is at a 'just passing' level, the simulation
predicts that the 7-day mean criterion will be violated about 16.6 percent of the weeks
(Table A-10). If the long term mean dissolved oxygen concentration increases to 5.7
mg/L, then we expected fewer than 5.5 percent of the weeks with failure of the 7-day
mean criterion. Thus if the 30-day mean criterion is satisfied, it is quite likely that
violations of the 7-day mean criterion will be satisfied unless the 30-day mean hovers
in the 'just passing' zone for an extended period.
Table A-10. Prediction of 7-day mean criterion failure rate.
Sensor Depth
6
5
4
3
Monthly mean
dissolved oxygen
5.0058
5.6732
6.3407
7.0082
7-day criterion failure
rate
16.6%
5.5%
1.5%
0.5%
Rate of instantaneous
criterion > 10%
47.6%
32.5%
25.3%
18.5%
Looking the violations of the instantaneous minimum is not so encouraging. When the
long term dissolved oxygen mean is 'just satisfied', the simulation predicts that the
instantaneous minimum criterion exceedance rate will exceed 10 percent in about 47
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86
percent of the weeks. Even when the long term mean dissolved oxygen is 7, the
simulation predicts 18.5 percent of weeks will have an instantaneous minimum
dissolved oxygen criterion exceedance rate in excess of 10 percent (Table A-10).
LITERATURE CITED
CBP STAC (Chesapeake Bay Program Scientific and Technical Advisory Committee).
2012. Evaluating the Validity of the Umbrella Criterion Concept for Chesapeake Bay
Tidal Water Quality Assessment. Findings of the Umbrella Criterion Action Team,
Tidal Monitoring and Analysis Workgroup. August 2012, STAC Publication. 12-02.
U.S. EPA (U.S. Environmental Protection Agency). 2004. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2004 Addendum. October 2004. EPA 903-R-04-005.
Region III Chesapeake Bay Program Office, Annapolis, MD.
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87
APPENDIX B
Rationale for Sub-segmenting Open-Water
Designated Use Segments into Zones
The following sections of this appendix discuss the development of a basis for sub-
segmenting Chesapeake Bay open-water designated use segments for supporting the
Chesapeake Bay Program partners Clean Water Act water quality standards attainment
assessments. These five sections:
1. Provide a historical review on the comparability of nearshore and offshore water
quality in Chesapeake Bay tidal waters;
2. Describe characteristics of Chesapeake Bay high frequency dissolved oxygen
dynamics with an emphasis on shallow water habitat;
3. Document support for a 2-zone sub-segmentation option in the open-water
designated use based on nearshore-offshore dissolved oxygen relationships;
4. Document support for a 3-zone sub-segmentation options in the open-water
designated use and;
5. Provide recommendations regarding sub-segmenting habitats in the open-water
designated use for water quality monitoring, water quality standards attainment
assessment and Chesapeake Bay restoration management decision-making.
CHESPEAKE BAY SEGMENTATION SCHEME
The Chesapeake Bay Program partners have used various forms of a basic segmentation
scheme to organize collection, analysis and presentation of environmental data for over
three decades. The Chesapeake Bay Program Segmentation Scheme Revisions,
Decisions and Rationales: 1983-2003 (U.S. EPA 2004a) provides documentation on
the development of the spatial segmentation scheme of the Chesapeake Bay and its
tidal tributaries. Segmentation has been used to compartmentalize the estuary into
subunits based on selected criteria for setting boundaries, grouping regions having
similar natural characteristics, so that differences in water quality and biological
communities among similar segments can be identified and the source of their impacts
elucidated (U.S. EPA 2004a). Segmentation also serves management purposes as a way
to group regions to define a range of water quality and resource objectives, target
specific actions and monitoring the response.
Factors previously considered in development and revision of the Chesapeake Bay
segment scheme include salinity and natural geographic partitions and features (e.g.,
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88
river mouths of major tidal tributaries). Segment lines near mid-Bay islands were
revised in the 1990s based on their surrounding shallow water habitat with submerged
aquatic vegetation (SAV) assessments in mind (U.S. EPA 2004a). Bathymetry and
large scale circulation patterns influenced small shifts in boundary lines in segments
CB7PH and CB8PH located in the lower mainstem Bay (U.S. EPA 2004a).
SUB-SEGMENTING CHESAPEAKE BAY SEGMENTS
Sub-segments have been previously been created for state water quality standards
applications (U.S. EPA 2004a). The 2003 Chesapeake Bay segmentation update
included split segments in Maryland in order to establish sub-segment specific water
clarity application depths and SAV acreage restoration goals within those segments
(U.S. EPA 2004a). When actually defining the subdivision boundaries digitally in GIS,
physical features in the landscape such as points or mouths of streams were used as
endpoints wherever possible. In some segments, a 'natural break' between an area
containing a lot of SAV and an area with little or no SAV was used to guide where the
division boundary lines were drawn (U.S. EPA 2004b). In Virginia, the James River
tidal fresh segment (JMSTF) was sub-divided into an upper segment (JMSTF2) and a
lower segment (JMSTF 1) for application of the new water clarity/SAV restoration
acreage and chlorophyll a water quality criteria (U.S. EPA 2004a). The upper James
River tidal fresh segment is narrower and faster flowing with a lower residence time
for algal biomass to build up. The lower James River tidal fresh segment is wider with
a greater photic zone and longer residence time.
The U.S. EPA published Chesapeake Bay designated use boundary definitions are
another form of sub-segmentation within a segment (U.S. EPA 2003b). The designated
use boundary definition for open water adopted by Delaware, the District of Columbia,
Maryland and Virginia into their water quality standards regulations is:
From June 1 through September 30, the open-water designated use includes
tidally influenced waters extending horizontally from the shoreline to the
adjacent shoreline. If a pycnocline is present and, in combination with bottom
bathymetry and water-column circulation patterns, presents a barrier to
oxygen replenishment of deeper waters, the open water fish and shellfish
designated use extends down into the water column only as far as the
measured upper boundary of the pycnocline. If a pycnocline is present but
other physical circulation patterns (such as influx of rich oceanic bottom
waters), provide for oxygen replenishment of deeper waters, the open-water
fish and shellfish designated use extends down into the water column to the
bottom water-sediment interface.
From October 1 through May 31, the open-water designated use includes all
tidally influenced waters extending horizontally from the shoreline to the
adjacent shoreline, extending down through the water column to the bottom
water-sediment interface (U.S. EPA 2003b).
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89
The shoreline to shoreline definition of open water is based on the assumption that the
dissolved oxygen requirements for the species and communities inhabiting open-water
habitat (e.g., >2 m in depth) and shallow-water habitats (e.g., <2 m in depth) are similar
enough to ensure protection of both the open-water and shallow-water bay grasses
designated uses with a single set of dissolved oxygen criteria (U.S. EPA 2003a). As a
reference here, the shallow-water bay grass designated use is delineated based on light
penetration through the water column that, within a range of water clarity
characteristics, can penetrate to a specific water column depth. The science behind light
limitation and photosynthesis coupled with the physics of light penetration through the
water column was translated to depth-based restoration targets for each Chesapeake
Bay segment (U.S. EPA 2003a). These depth-based targets provide bathymetric-based
boundaries that constrain the water clarity criteria attainment assessments in space
within Chesapeake Bay and its tidal tributaries.
DIFFERENCES IN NEARSHORE VS. OFFSHORE WATERS
With respect to separating nearshore and offshore waters for separate water quality
standards criteria attainment assessments, Caffrey (2004) suggests management
changes in a watershed, such as changes affecting nutrient loading, may be more
apparent in shallow water than offshore waters of an estuary. Lyerly et al. (2014)
highlights management successes in similar shallow-water environments described by
Caffrey (2004) with examples of subestuaries of Chesapeake Bay illustrating positive
water quality responses to local management actions (e.g., Gunston Cove, Virginia on
the Potomac River and Corsica River, Maryland).
However, according to U.S. EPA (2007a), "Neither the need nor the requirement exists
for a separate assessment of dissolved oxygen criteria attainment strictly within shallow
waters (0-2 meters in depth)". U.S. EPA (2007a) goes on to state that conditions in
these nearshore waters are considered to vary greatly from the mid-channel habitats of
the open water, but there was no scientific basis for a dissolved oxygen-based
delineation between the two habitats. Acknowledging that habitat differences do exist,
a jurisdiction may, however, specifically delineate sub-segments within a Chesapeake
Bay segment for purposes of criteria attainment assessment (U.S. EPA 2007a).
RECOGNITION OF A THREE-ZONE APPROACH
TO SUB-SEGMENTATION
The U.S. EPA (2003c) 305(b) guidance highlights a three zone approach option to
water quality assessment in estuarine habitats. Estuarine habitats are divided to define
monitoring site representativeness by open water, sheltered bays, and highly sheltered
bays. The presence of fixed boundaries (e.g., mouth of a river) and transient water
column features, e.g., the pycnocline, are already concepts represented in the boundary
definition of the open-water designated use.
Analyses were conducted by the Chesapeake Bay Program's Umbrella Criteria
Assessment Team in conjunction with newly published reports quantifying
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90
characteristics of dissolved oxygen behavior between nearshore and offshore habitats
in Chesapeake Bay and its tidal tributaries (Boynton et al. 2014, Lyerly et al. 2014).
This combination of new science provided fresh insights and decision-support for
options to be considered on sub-segmenting open-water habitats for dissolved oxygen
criteria attainment assessment purposes. With such scientific support, a similar zone-
type assessment construct as that suggested in U.S. EPA (2003c) 305(b) guidance for
dividing estuarine habitats could be developed for application in Chesapeake Bay and
its tidal tributaries and embayments supporting sub-segmenting options for the open-
water designated use segments.
IMPORTANCE OF SHALLOW-WATER AREA IN CHESAPEAKE BAY
A supplemental issue was expressed by the CBP partners in that the sheer volume of
offshore water regions may overwhelm signals of distress in shallow waters for
Chesapeake Bay and its tidal tributaries and embayments (MRAT 2009, CBP STAC
2012). Significant differences in dissolved oxygen behavior for nearshore and offshore
open-water habitats could translate to disproportionate effects on segment-specific
dissolved oxygen criteria attainment assessments due to their relative and varied
habitat-area contributions across the Bay's tidal waters (Figure B-l).
Ill
4—»
05
5
£
_o
IB
CO
Summer Open Water habitat:
As Chesapeake Bay segment size
increases, shallow water habitat
decreases
100
tX
3.001
0.1
Grl-
10
Segment Volume km3
Figure B-1. The relationship of proportion of shallow-water habitat as it relates to the size of the
Chesapeake Bay segments. Total segment volumes (km3) were based on the U.S. EPA 2003b. Percent
shallow water volumes were calculated from SAV Tier III acres (0-2m), converted to volume by assuming
a rectangular volume 3 feet deep is roughly equivalent to a triangular volume with maximum depth of 2m,
converted to gallons, then converted to km3) and used to compare with the total segment volume for the
proportion.
As a general reference, shallow-water habitat in Chesapeake Bay can be considered <2
meters (p 38, U.S. EPA 2007a). Approximating the area and volume of all such
shallow-water habitat for the Chesapeake Bay and the tidal tributaries and embayments
that are less than 2 meters in depth, there are at least 700,000 acres (2,833 km2) less
than or equal to 6 feet deep4. The total surface area of the tidal waters of Chesapeake
Bay and its tidal tributaries and embayments is estimated to be 11,601 km2. Therefore,
4 http://www.chesapeakebav.net/discover/bavl01/facts.
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91
the shallow water habitat of the tidal Chesapeake Bay waters is approximately 24
percent of its total surface area.
Assuming an average shallow water depth to be half the maximum depth of those acres,
i.e., 3 feet, then an estimate for the volume of Chesapeake Bay, tidal tributary and
embayment shallow water habitat is 4.6% of the total Bay waters volume or 2.6 km3.
The importance of this volume, for comparison, is that 2.6 km3 is typically greater than
the observed peak volume for estimates of late summer deep water anoxia in
Chesapeake Bay between 1985 and 2010 (Figure B-2)5.
Improving the deep water hypoxic volume of Chesapeake Bay to restore bay habitat
health for living resources is a critical restoration outcome associated with the long
term success of the Chesapeake Bay TMDL (U.S. EPA 2010b). While not all available
nearshore habitat of Chesapeake Bay, its tidal tributaries and embayments may be
exhibiting low dissolved oxygen or hypoxic events, significant examples exist such as
occurs in South River, MD (Muller and Muller 2014), Severn River, MD (see 2008
Severn River Report Card6), and Corsica River, MD (see Figure B-6).
Between 1987 and 2001, fish kill distributions in Maryland have been widespread and
point to many areas over time where Maryland Department of the Environment
attributed a portion of the observed fish kills potential causal effects may be due to
hypoxia (Figure B-3). Mitigating the effects of nearshore hypoxia, therefore, has
similar importance to the health of the Bay and its living resources as correcting deep
water hypoxia issues due to its representative volume and area.
Late summer anoxia volume and forecast
¦ Forecast
I Observed
3-
85 90 95 00 05 10
Historic anoxic volume for late summer (mid-July to September) and the 2010 late
summer forecast of anoxic volume.
Figure B-2. Historical time series of anoxic volume for late summer also showing the 2010 IAN Ecocheck
forecast. Source: http://ian.umces.edu/ecocheck/
5 http://ian.umces.edu/ecocheck/summer-review/chesapeake-
bav/2010/indicators/anoxia/.
6 http://ian.umces.edu/pdfs/ian report card 212.pdf.
-------
pjtvpicv ftlHf
Figure B-3 Fish kills attributed to low dissolved oxygen Chesapeake Bay, Maryland, upper western
shore area, 1987-2001.
Sources: Maryland Department of Environment Fish Kill Investigation Section, Fish Kill Database.
HISTORICAL REVEW OF THE COMPARABILITY OF NEARSHORE AND
OFFSHORE WATER QUALITY IN CHESAPEAKE BAY
The question of comparability of nearshore to offshore, midchannel water quality is a
Chesapeake Bay issue that has been subjected to analysis for decades. Batiuk et al.
(2000) noted several such studies between 1991 and 1996 suggesting mid-channel data
can be used to describe nearshore conditions. However, not all the studies were in
agreement. This issue was further assessed with Chesapeake Bay Program's
Chesapeake Bay Mainste and Tidal Tributaries Water Quality Monitoring Program
data by Karrh (1999) and Batiuk et al. (2000). In a 1999 study, the Maryland
Department of Natural Resources investigated the validity of using mid-channel data
to assess water quality conditions in nearshore areas (Karrh 1999). The 13-tidal
tributary study examined water quality at 127 nearshore stations compared to 54
adjacent mid-channel stations and found wide variations between nearshore and mid-
channel conditions both within and between tidal tributaries (U.S. EPA 2007a).
However, all these studies focused on parameters important to SAY habitat (Secchi
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93
depth, dissolved organic nitrogen, dissolved inorganic phosphorus, chlorophyll a, total
suspended solids and salinity) and did not evaluate dissolved oxygen behavior.
At the time of publishing the 2003 Ambient Water Quality Criteria for Dissolved
Oxygen, Water Clarity and Chlorophyll a for the Chesapeake Bay and its Tidal
Tributaries (U.S. EPA 2003a), there remained insufficient information to support
separating the open-water designated use into nearshore and offshore zones for the
purpose of dissolved oxygen criteria attainment assessments (U.S. EPA 2003a).
However, with the evolution of the CBP Shallow Water Monitoring Program's
measurement of water quality conditions in high-temporal and spatial densities,
multiple years of nearshore habitat data were collected across a wide range of site
conditions from across the tidal waters of the Chesapeake Bay, and in neighboring
estuaries (e.g., the Maryland and Virginia Coastal Bays).
The CBP's Umbrella Criteria Assessment Team used more than a decade of
Chesapeake Bay derived high temporal density dissolved oxygen data to help
characterize dissolved oxygen behavior across multiple time scales and habitats (CBP
STAC 2012). The combined data sets contained more than 1 million data points. Intra-
site, inter-site and inter-annual variability are described within CBP STAC 2012. A
foundation of new dissolved oxygen focused analyses was created from the work of
the CBP's Chesapeake Bay Monitoring Realignment Action Team (MRAT 2009) and
the CBP's Umbrella Criteria Assessment Team (CBP STAC 2012).
CHARACTERISTICS OF CHESPEAKE BAY HIGH FREQUENCY
DISSOLVED OXYGEN DYNAMICS WITH EMPHASIS ON
SHALLOW-WATER HABITAT
The analysis of high temporal density dissolved oxygen data from the nearshore
habitats, often show a diel scale of hypoxia (CBP STAC 2012). Some locations
experience severe hypoxia (e.g., Ben Oaks, Severn River, MD in Figure B-4; see also
Boynton et al. Appendix 4 in CBP STAC 2012). Dissolved oxygen concentrations
drop to low levels during the hours of darkness and sometimes reach dangerously low
concentrations to most Chesapeake Bay aquatic life at or just after sunrise (see also
Boynton et al. Appendix 4 in CBP-STAC 2012, U.S. EPA 2007a).
Time series of nearshore continuous dissolved oxygen monitoring data further illustrate
hypoxic and anoxic events beyond the routinely observed day/night diel fluctuations.
One example, illustrated from the Maryland Department of Natural Resources' Piney
Point monitoring site on the lower Potomac River, shows the intrusion of anoxic deep
layer waters from the mainstem Bay into shallow water during a seiching event (Figure
B-5). Degraded dissolved oxygen conditions persisted beyond a 24-hour diel cycle with
habitat impacts evident for 48-72 hours while temperature and salinity were slower to
recover to pre-event conditions. A second example from the Corsica River, MD
illustrated the impact of a nearly week-long water quality and fish kill event involving
an algal die off during late September 2005 (Figure B-6). Bacterial decomposition
effects reduced dissolved oxygen measures to anoxia followed by a multiday recovery
-------
to normoxic conditions (CBP STAC 2012). Boynton et al. (2014) examined 57 high
temporal density dissolved oxygen data records for full summer seasons showing
nearshore locations across Maryland tidal waters can experience a gradient of hypoxia
from minutes to weeks.
Dissolved Oxygen (DO)
concentration
.05--
O) 6.04-
o 4'°2-l
Q 2.01 -¦
0.00
ld m
CO m ~
r-- r-- r-- r-- r-- r-- r-- r-- r--
date
Figure B-4 Ben Oaks, Severn River, MD example of diel hypoxia in shallow water with data collected
every 15 minutes.
Source: Maryland Department of Natural Resources
June 5, 2006. Thousands of fish dead in lower Potomac River
June 3. 8 hrs
Salinity incr
Dissolved o
12:00 pm- 8 pi
declines
»ases +2.8 ppl
¦ygen drops fror
n
5.3 "C
S to 0 mg/L
—
,r~
Citizen observed fish washing
ashore starting June 4lh.
Reported to hotline June 5th.
/
wvM
v
\ iAi/i
r
*V V s
L
V#
Vi
May 31 June 1 June 2 June 3 June 4 June 5 June 6
Date
Piney Point Continuous Monitoring data for dissolved oxygen (mg O^b),
salinity (ppt) and (oC), May 31-June 6, 2006.
Figure B-5, Lower Potomac River Piney Point Continuous Monitoring data, Maryland
Department of Natural Resources, from May 31 to June 6, 2006 shows intrusion of deeper water anoxic
waters from the mainstem Chesapeake Bay. Such an intrusion affecting nearshore dissolved oxygen
resources was linked with climate forcing effects of wind direction changes on June 3, 2006 and a
resulting seiche of bottom waters of the adjoining mainstem Bay.
Source: Maryland Department of Natural Resources
-------
Citizen:Evidence
offish in distress
MDE and DNR
find tens of
thousands of
dead fish
throughout the
river
18 n
o) 14 -
£
16 -
DNR finds
hundreds of
dead fish
9/22/2005 9/24/2005 9/26/2005 9/28/2005 9/30/2005 10/2/2005 10/4/2005
Minimum dissolved oxygen
requirements:
Time
Water Quality
Healthy above 5 mg/L
Hypoxic (low) 2-5 mg/L
Severely hypoxic 0.2-2 mg/L
Anoxic below 0.2 mg/L
Striped bass 5-6
American shad 5 m
5-6 ms'L i=i Sycamore Pt Cedar Pt.
5 mg/L
3 mg/L
2 mg/L
1 mg/L
Bay anchovy
Spot
Worms
Figure B-6. Corsica River, MD, 2005. Chronology of a fish kill arid associated water quality.
Sources: Maryland Department of Natural Resources, 2005 Waterman's Gazette.
Based on Potomac River continuous monitoring data over multiple years and across
seasons, seasonal shifts in dissolved oxygen concentration frequency distributions were
shown to have lower concentrations and broader ranges in mid-summer, higher
concentrations and less variation for spring/early summer and autumn (see Buchanan
Appendix 1, Perry Appendix 11 in CBP STAC 2012). Perry (Appendix 11 in CBP
STAC 2012) combined data from 9 tidal Potomac River sites and suggested spring may
be more variable than summer and autumn. Buchanan (Appendix IB in CBP STAC
2012) computed daily means at the 20 tidal Potomac embayment and river flank
stations from 2004-2008 and showed a spring season range between 1.0 and 16.8 mg/L,
a summer range from 0.36-14.9 mg/L and an autumn range of 3.1-14.0 mg/L dissolved
oxygen. The tidal Potomac River data further showed that the range of diel dissolved
oxygen variability experienced in shallow waters reached 11.0 mg/L in spring, 17.52
mg/L in summer and 10.8 mg/L in autumn. Diel patterns in dissolved oxygen
concentrations showed a positive bias with daytime measurements and negative bias
for nighttime measures (Figure 8 from Perry Appendix 11 in CBP-STAC 2012).
Based on the Chesapeake Bay Program Umbrella Criteria Assessment Team's analysis
of high frequency continuous monitoring data from multiple tidal tributaries across the
Chesapeake Bay's tidal waters, the behavior of nearshore dissolved oxygen
concentrations was statistically similar to offshore dissolved oxygen concentrations at
long time scales (i.e., 7-day and 30-day mean assessments). However, nearshore
SUPPORT FOR A 2-ZONE SUB-SEGMENTATION OF
OPEN-WATER DESIGNATED USE SEGMENTS
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96
dissolved oxygen concentration patterns through time were, statistically dissimilar at
daily or shorter time steps (CBP STAC 2012).
In 2013, the Chesapeake Bay Program Scientific, Technical Assessment and Reporting
Team's Tidal Monitoring and Analysis Workgroup revisited the question of
comparability of nearshore and offshore dissolved oxygen behavior with a paired
comparison analysis of the best available high frequency, nearshore and offshore water
quality monitoring data sets. Robertson and Lane, as reported in CBP STAC 2012,
previously used comparisons of nearshore continuous dissolved oxygen concentration
monitoring data with synthesized offshore dissolved oxygen concentration data
developed using a spectral casting technique. Robertson (2013) updated the analysis by
replacing synthesized offshore data and using direct measurements from Virginia's
offshore tidal York River and tidal Rappahannock River vertical water quality
monitoring profilers to compare with co-located nearshore continuous water quality
monitoring measurements. Robertson's 2013 analyses reconfirmed the initial findings
reported by CBP STAC (2012) of similarity between nearshore and offshore dissolved
oxygen behavior at the 7-day and 30-day mean scales of comparison but dissimilarity
at 1-day and instantaneous minimums scales.
Trice (2013) provides additional insights into Robertson's (2013) findings regarding
differences in dissolved oxygen patterns at the shortest (daily or less) time scales. Trice
(2013) compared 2004 and 2005 summer season hourly average data for co-located
monitoring stations of Pin Oak (nearshore) and CBL (offshore) on the lower tidal
Patuxent River (Figure C-7). Trice (2013) showed nearshore conditions were worse
22 more days nearshore than offshore in summer 2004, and 39 more days nearshore
than offshore in summer 2005. Boynton et al. 2014 described few differences between
hourly averaged and 15 minute interval data for examining violation rate assessments.
These findings support sub-segmentation between nearshore and offshore habitats for
the criteria attainment assessment of the shortest duration dissolved oxygen criteria
(e.g., instantaneous minimum) applicable to protection of the open-water designated
use.
SUPPORT FOR A 3-ZONE SUB-SEGMENTATION OPTION OF
THE OPEN-WATER DESIGNATED USE
An extension of the 2-zone option to a 3-zone sub-segmentation option in the open
water designated use is supported by the data analyses described below. Caffrey (2004)
and Boynton et al. (2014) found that nearshore monitoring sites with greater exposure
to mainstem tidal bay and mainstem tidal tributary habitats show better water quality
conditions than nearshore sites with more restricted exposures. Boynton et al. (2014)
pointed to "tributaries of tributaries" having greater violation rates on average than
monitoring stations located in the nearshore zone of the mainstem of a tributary. Both
the tributary of tributary sites and the nearshore zones of tributaries had greater
violation rates than monitoring sites exposed to the open waters of the mainstem
Chesapeake Bay.
-------
Thes findings are consistent with the 3-zone approach recommended in U.S. EPA
(2003) 305(b) guidance highlighting how Washington State Department of Ecology
similarly divides estuarine habitats to define monitoring site representativeness: open
water, sheltered bays and highly sheltered bays. Virginia Department of Environmental
Quality already cites the U.S. EPA (2003) 305(b) guidance to support the same three
habitats for their existing non-Chesapeake Bay Program tidal and estuarine monitoring
station location considerations (VADEQ 2014). The 3-zone approach, therefore, offers
a logical extension of the 2-zone approach option to sub-segmenting the open water
designated use considering an additional zone accommodating the finer resolution of
small waters in the tributaries of tributaries that are most sheltered (e.g., like the highly
sheltered bays category suggested by Washington State Department of Ecology).
2005 June 1 - Sept 30
Hourly Average Regression
Figure B-7 2005 example of hourly average comparisons illustrating the tendency for nearshore shallow
water conditions to be lower than offshore, Patuxent River.
Source: Maryland Department of Natural Resources
LITERATURE CITED
Batiuk, R., W.M. Kemp, P. Bergstrom, M. Kemp, E. Koch, L. Murray, J. Court
Stevenson, R. Bartleson, V. Carter, N.B. Rybicki, J. M. Landwehr, C. Gallegos, L.
Karrh, M. Naylor, D. Wilcox, K.A. Moore, S. Ailstock and M. Teichberg. 2000.
Chesapeake Bay Submerged Aquatic Vegetation Water Quality and Habitat-Based
Requirements and Restoration Targets: A Second Technical Synthesis. CBP/TRS
245/00. EPA 903-R-00-014. December 2000. EPA Chesapeake Bay Program,
Annapolis, MD. 220pp.
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98
Boyton, W.R., J.M. Testa, C.L.S. Hodgkins, J.L. Humphrey, and M.A.C. Ceballos.
2014. Maryland Chesapeake Bay Water Quality Monitoring Program. Ecosystem
Processes Component. Level one Report No. 31. Interpretive Report. August 2014.
Tech. Report Series No. TS-665-14 of the University of Maryland Center for
Environmental Science. UMCES-CBL 2014-051.
Caffery, 2004. Factors controlling net metabolism in U.S. Estuaries. Estuaries
27(1):90-101.
CBP STAC (Chesapeake Bay Program Scientific and Technical Advisory Committee).
2012. Evaluating the Validity of the Umbrella Criterion Concept for Chesapeake Bay
Tidal Water Quality Assessment. Findings of the Umbrella Criterion Action Team
Tidal Moni toring and Analysis Workgroup (TMAW) August 2012, STAC Publ. 12-
02.
Karrh. L. 1999. Comparison ofNearshore andMidchannel Water Quality Conditions.
200pp. Chesapeake Bay Program, Annapolis, MD.
Muller, A. and D. Muller. 2014. Analysis of nontidal point pollution, variability and
sustainability in mesohaline tidal creeks. Marine Pollution Bulletin. 85:204-213.
Lyerly C.M., A.L. Hernandez Cordero, K.L. Foreman, S.W. Phillips, W.C. Dennison.
2014. New insights: science-based evidence of water quality improvements, challenges
and opportunities in the Chesapeake.
Trice, M. 2013 http://www.chesapeakebav.net/calendar/event/20745/ July 12, 2013
Umbrella Criteria Action Team, Shallow water vs. Open Water Dissolved Oxygen
(DO). Power point presentation.
Robertson, T. 2013. http://www.chesapeakebav.net/calendar/event/20745/ July 12,
2013 Umbrella Criteria Action Team, Nearshore vs. Offshore York and Rappahannock.
Power point presentation.
U.S. EPA (U.S. Environmental Protection Agency). 2003a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries. EPA 903-R-03-002. U.S. Environmental Protection
Agency, Region III, Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2003b. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability.
EPA 903-R-03-004. U.S. Environmental Protection Agency, Region III, Chesapeake
Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2003c. Guidance for 2004 Listing
and Reporting Requirements Pursuant to Sections 303(d) and 305(b) of the Clean
Water Act, July 21, 2003. U.S. Environmental Protection Agency Office of Water,
Office of Wetlands, Oceans and Watersheds, Assessment and Watershed Protection
Division, Watershed Branch, Washington D.C.
-------
99
U.S. EPA (U.S. Environmental Protection Agency). 2004a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries. 2004 Addendum. EPA 903-R-03-002. U.S.
Environmental Protection Agency, Region III, Chesapeake Bay Program Office,
Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2004b. Technical Support
Document for Identification of Chesapeake Bay Designated Uses and Attainability -
2004 Addendum. EPA 903-R-04-006. U.S. Environmental Protection Agency, Region
III, Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2007a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries— 2007 Addendum. EPA 903-R-07-003. CBP/TRS 285-
07. U.S. Environmental Protection Agency, Region III, Chesapeake Bay Program
Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2007b. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries— 2007 Chlorophyll Criteria Addendum. EPA 903-R-07-
005. CBP/TRS 288-07. U.S. Environmental Protection Agency, Region III,
Chesapeake Bay Program Office, Annapolis, MD.
U.S. EPA (U.S. Environmental Protection Agency). 2010. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries - 2010 Technical Support for Criteria Assessment
Protocols Addendum. May 2010. EPA 903-R-10-002. Region III Chesapeake Bay
Program Office, Annapolis, MD.
VA DEQ (Virginia Department of Environmental Quality). 2014. Water Quality
Assessment Guidance Manual for 2014 305(b) 303(d) Integrated Water Quality
Report. April 2014, Richmond, VA.
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100
APPENDIX C
Chesapeake Bay Water Quality Data
Supporting Development and Testing of
Short-Duration Dissolved Oxygen Criteria
Attainment Assessments
Quality assured, quality controlled water quality data sets were targeted by the
Chesapeake Bay Program's Umbrella Criteria Assessment Team to conduct their
method evaluations (Table C-l). The nearly three decades-long Chesapeake Bay
Program long-term water quality monitoring network data set formed the foundation
of the low frequency monitoring data needs. During the U.S. EPA (2004) analyses
evaluating umbrella-like dissolved oxygen criteria protection, the temporally dense,
high frequency monitoring data sets were largely limited to U.S. EPA EMAP short-
term buoy deployments. At that time, season-long continuous dissolved oxygen
monitoring data sets from tidal waters of Chesapeake Bay were not widely available.
The focus on high frequency dissolved oxygen data collection was on the threshold of
being incorporated into the new, shallow-water focused station network in an expanded
Chesapeake Bay Program tidal Bay monitoring framework. In 2004, the Chesapeake
Bay Program formalized this monitoring network expansion and invested in what is
now known as the Shallow-water Monitoring Program. During the 2000s, Federal,
State and local agencies along with academic institutions further made investments into
nearshore and offshore water quality monitoring technologies.
Application of the new technologies produced water quality time series with temporally
dense dissolved oxygen measurements at fixed depth and in vertical profile. Alternative
technologies were also attached to a boat at fixed depth or pulled behind a boat to get
multiple depths over space with high resolution, underway monitoring efforts.
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101
Table C-1. Data sources serving the umbrella criterion assumption analyses.
Program Description
Data Collection and
Availability
Sampling Locations and
Habitats
CBP long-term water quality
monitoring program: Low temporal
frequency and spatial resolution, good
vertical profile resolution of the data.
198 5-present.
Biweekly to monthly sampling.
Water column profiles taken with grab
samples and sensors.
Web accessible data: CBP ClhlS
Fixed site, mid-channel. Bay and tidal
tributaries, approximately 150 stations.
Covers tidal fresh to polyhaline habitat
conditions.
USEPA EMAP: Historical short-term
buoy deployments with high temporal
frequency at a station. Single depth
sensor evaluations.
Mix of short term (days to weeks) time
series with high temporal frequencies
by sensor. See USEPA (2004).
Fixed site, off shore locations, varied
depths. Tidal fresh to polyhaline
habitat conditions.
CBP Shallow Water Monitoring
Program Continuous Monitoring
(CONMON): High temporal frequency
at moored locations.
Approximately 2000-present.
Mostly seasonally, near continuous (15
min interval) time series April-
October.
Fixed depth sensor, usually lm off
bottom.
Web accessible data: Eyes on the Bay
in MD. VECOS in Virginia.
Fixed site, shallow water, nearshore
locations, approximately 70 sites
Baywide with 1-9 yrs of data. Tidal
fresh to mesohaline conditions.
VIMS, MD DNR Vertical Profilers:
High temporal frequency in 2
dimensions.
VIMS: Bottom sonde .
Approximately 2006-present. Limited
seasons. Sensors provide water column
profiles at sub-daily scales. Bottom
sonde.
Web accessible data: MD DNR and
VADEQ.
Fixed sites (n<5). offshore locations in
MD (Potomac River) and VA (York
and Rappahannock Rivers).
Dominantly mesohaline lower tidal
tributary data.
CBP Shallow Water Monitoring
Program: surface water quality
mapping with DATAFLOW. High
Spatial resolution along temporally
dense collection track.
Approximately 2000-present.
Biweekly to monthly mapping
assessments within April-October
season.
Multi-year assessments (3 yr sets).
Sensor 0.5m below surface
Web accessible data: Eyes on the Bay
in MD. VECOS in Virginia.
Chesapeake Bay Program management
segments. Approximately 40 of 92
segments assessed to date. Tidal fresh
to polyhaline habitats.
VIMS Volumetric Assessment with
ACROBAT: (towed sensor
underwater at variable depths). High
spatial resolution.
Approximately 2003-present
Limited seasons.
3-dimensional sensor assessment of
water column water quality.
VIMS data. Brush et al.
York and Rappahannock Rivers (VA)
study sites, deep water reaches.
Dominantly mesohaline habitat.
LITERATURE CITED
U.S. EPA (U.S. Environmental Protection Agency). 2004a. Ambient Water Quality
Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake
Bay and Its Tidal Tributaries. 2004 Addendum. EPA 903-R-03-002. U.S.
-------
102
Environmental Protection Agency, Region III, Chesapeake Bay Program Office,
Annapolis, MD.
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103
APPENDIX D
Western Branch Patuxent River Tidal
Freshwater Segment Metadata
This appendix contains data and metadata on the ten Western Branch Patuxent River
Tidal Fresh (WBRTF) segment transects as reported by Maryland Department of the
Environment. Water volumes are assigned to their segments and the data used to
determine the volume assignment are provided here. Please note that only stations
numbered 1-6 were located within the WBRTF segment. The segment starts from the
southern bank of the river.
To compute the segment volume, the area of each cross-section was computed by an
integration method. The volume between the two cross-sections is computed by
multiplying the average of the two cross section area measurements and the distance
between them. The total volume is the sum of all the volumes in the segment.
River name: Western Branch Station Code: Station #1 Date: 9/7/2001
Scientist(s): DJR/SGL Riverbed Description: Soft Mud
Site location: N 38 47.139 W 76 42.794
Site description: 25 yards upstream of pier at Calvert Manor
Digital Photo Series: MD Department of Environment. Folder 113, images 1-2
Comments: 165 feet wide, when measurements were taken there was a 1.5 foot high tide
mark visible.
Orientation: Looking downstream, the measurements were collected left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0
0
7.50
0
15
2.50
15.00
37.50
30
4.50
15.00
67.50
45
5.00
15.00
75.00
60
5.00
15.00
75.00
75
5.00
15.00
75.00
90
5.30
15.00
79.50
105
5.30
15.00
79.50
120
4.50
15.00
67.50
135
3.50
15.00
52.50
150
1.50
15.00
22.50
165
0
7.50
0
Sum of (depth*width) = area of streambed = 631.50 ft2
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104
River name: Western Branch Station Code: Station #2 Date: 9/7/2001
Scientist(s): DJR/SGL Riverbed Description: Soft Mud
Site location: N 38 47.305 W 76 42.898
Site description: 10 yards downstream of Horse Cavern Branch
Digital Photo Series: MD Department of Environment. Folder 113, images 3-5
Comments: 135 feet wide, when measurements were taken there was a 1.5 foot high tide
mark visible.
Orientation: Looking downstream, the measurements were collected left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0
0
5.0
0
10
3.00
12.5
37.50
25
3.50
15.0
52.50
40
5.20
15.0
78.00
55
6.30
15.0
94.50
70
7.30
15.0
109.50
85
7.10
15.0
106.50
100
5.00
15.0
75.00
115
3.00
15.0
45.00
130
2.00
10.0
20.00
135
0
2.5
0
Sum of (depth*width) = area of streambed = 618.50 ft2
River name: Western Branch Station Code: Station #3 Date: 9/7/2001
Scientist(s): DJR/SGL Riverbed Description: Harder more solid mud
Site location: N 38 47.490 W 76 43.022
Site description: No additional details.
Digital Photo Series: MD Department of Environment. Folder 113, images 6-8
Comments: 150 feet wide, when measurements were taken there was a 1.5 foot high tide
mark visible.
Orientation: Looking downstream, the measurements were collected left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0
0
7.5
0
15
3.00
15.0
45.00
30
6.20
15.0
93.00
45
5.50
15.0
82.50
60
5.00
15.0
75.00
75
4.75
15.0
71.25
90
4.50
15.0
67.50
105
4.00
15.0
60.00
120
3.00
15.0
45.00
135
1.75
15.0
26.25
150
0
7.5
0
Sum of (depth*width) = area of streambed = 565.50 ft2
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105
River name: Western Branch Station Code: Station #4 Date: 9/7/2001
Scientist(s): DJR/SGL Riverbed Description: Harder more solid mud
Site location: N 38 47.485 W 76 43.239
Site description: downstream of small unnamed tributary
Digital Photo Series: MD Department of Environment. Folder 113, images 9-11
Comments: 135 feet wide, when measurements were taken there was a 1.5 foot high tide
mark visible.
Orientation: Looking downstream, the measurements were collected left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0
0
5.0
0
10
2.00
12.5
25.00
25
3.00
15
45.00
40
3.50
15
52.50
55
4.25
12.5
53.13
65
5.50
10
55.00
75
6.50
10
65.00
85
8.00
12.5
100.00
100
2.70
15
40.50
115
2.00
12.5
25.00
125
2.00
10
20.00
135
0
5
0
Sum of (depth*width) = area of streambed = 481.13 ft2
River name: Western Branch Station Code: Station #5 Date: 9/7/2001
Scientist(s): DJR/SGL Riverbed Description: Sand/mud, hard bottom
Site location: N 38 47.777 W 76 43.316
Site description: No additional details
Digital Photo Series: MD Department of Environment. Folder 113, images 12-13
Comments: 120 feet wide, when measurements were taken there was a 1.5 foot high tide
mark visible.
Orientation: Looking downstream, the measurements were collected left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0
0
6.0
0
12
1.50
12.0
18.00
24
5.00
12.0
60.00
36
4.00
12.0
48.00
48
4.00
12.0
48.00
60
4.25
12.0
51.00
72
4.50
12.0
54.00
84
4.00
12.0
48.00
96
3.50
12.0
42.00
108
1.75
12.0
21.00
120
0
6.0
0
Sum of (depth*width) = area of streambed = 390.00 ft2
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106
River name: Western Branch Station Code: Station #6 Date: 9/7/2001
Scientist(s): DJR/SGL Riverbed Description: Sandy hard mud
Site location: N 38 47.832 W 76 43.746
Site description: 50 yards downstream of WSSC outfall
Digital Photo Series: MD Department of Environment. Folder 113, images 14-18
Comments: 66 feet wide, when measurements were taken there was a 1.5 foot high tide
mark visible.
Orientation: Looking downstream, the measurements were collectec
left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0
0
2.5
0
5
4.00
7.5
30.00
15
4.50
12.5
56.25
30
5.25
10.0
52.50
35
6.00
5.0
30.00
40
6.50
5.0
32.50
45
7.50
5.0
37.50
50
8.00
5.0
40.00
55
4.00
5.0
20.00
60
3.00
5.5
16.50
66
0
3.0
0
Sum of (depth*width) = area of streambed = 315.25 ft2
River name: Western Branch Station Code: Station #7 Date: 9/7/2001
Scientist(s): DJR/SGL Riverbed Description: hard mud
Site location: N 38 47.858 W 76 44.046
Site description: 700 yards upstream of effluent
Digital Photo Series: MD Department of Environment. Folder 113, images 19-21
Comments: 48 feet wide
Orientation: Looking downstream, the measurements were collected left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0
0
3.0
0
6
4.25
6.0
25.50
12
4.50
6.0
27.00
18
5.00
6.0
30.00
24
5.00
6.0
30.00
30
5.25
6.0
31.50
36
5.25
6.0
31.50
42
4.50
6.0
27.00
48
0
3.0
0
Sum of (depth*width) = area of streambed = 202.50 ft2
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107
River name: Western Branch Station Code: Station #8 Date: 9/7/2001
Scientist(s): DJR/SGL Riverbed Description: Sandy hard mud
Site location: N 38 47.957 W 76 43.874
Site description: No additional details
Digital Photo Series: MD Department of Environment. Folder 113, images 22-24
Comments: 48 feet wide
Orientation: Looking downstream, the measurements were collected left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0
0
2.5
0
5
2.50
7.5
18.75
15
3.25
7.5
24.38
20
3.50
7.5
26.25
30
4.50
10.0
45.00
40
4.00
7.5
30.00
45
3.00
4.0
12.00
48
0
1.5
0
Sum of (depth*width) = area of streambed = 156.38 ft2
River name: Western Branch Station Code: Station #9 Date: 9/7/2001
Scientist(s): DJR/SGL Riverbed Description: Hard mud
Site location: N 38 48.550 W 76 44.435
Site description: Rt 301 crossing
Digital Photo Series: MD Department of Environment. Folder 113, images 25-26
Comments: 47 feet wide, had to do the geometry off of the bridge.
Orientation: Looking downstream, the measurements were collected left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0
0
2.5
0
5
1.00
5.0
5.00
10
1.00
5.0
5.00
15
1.60
5.0
8.00
20
1.60
5.0
8.00
25
1.70
5.0
8.50
30
2.30
5.0
11.50
35
2.50
5.0
12.50
40
2.90
5.0
14.50
45
2.50
3.5
8.75
47
0
1.0
0
Sum of (depth*width) = area of streambed = 81.75 ft2
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108
River name: Little Patuxent River Station Code: RM-28, LTX0248 Date: 7/1/2002
Scientist(s): DJR/GWL/RKN Riverbed Description: 10% Silt, 70% sand, 10%
gravel, 10% cobble
Site location: N 39 12.555 W 76 51.359
Site description: no additional details
Digital Photo Series: N/A
Comments: 29.5 feet wide
Orientation: Looking downstream, the measurements were collectec
left to right.
Length (feet)
Depth (feet)
Cell width (feet)
Depth*width (feet2)
0.5
0.10
0.25
0.03 Low bank
1
1.00
0.75
0.75
2
3.00
1.00
3.00 water's edge
left bank
3
4.50
2.00
9.00
6
4.00
3.00
12.00
9
3.50
3.00
10.50
12
3.40
3.00
10.20
15
3.40
3.00
10.20
18
3.20
3.00
9.60
21
3.20
3.00
9.60
24
3.30
3.00
9.90
27
3.00
2.50
7.50 water's edge
right bank
29
2,70
1.50
4.05
30
0.10
0.50
0.05 high bank
Sum of (depth*width) = area of streambed = 29.50 ft2
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109
Appendix E
Centroid Coordinates for Grid Cells Used
to Define the Chesapeake Bay Western
Branch Tidal Fresh Segment
The Chesapeake Bay Western Branch Patuxent River Tidal Fresh segment (WBRTF)
is represented by 45 Cartesian grid cells, each with dimensions 50m x 50m. Table E-l
of this appendix provides the centroid coordinates for the 45 grid cells used to define
the WBRTF segment. The coordinates are in the UTM Zone 18 NAD83 projection.
Table E-l. Centroid coordinates for the 45 grid cells used to define the Western Branch
Tidal Fresh segment. The coordinates are in the UTM Zone 18 IS
AD83 projection.
Id
X
Y
Depth (m)
1
351200
4294300
1
2
351200
4294350
1
3
351150
4294400
1
4
351150
4294450
1
5
351150
4294500
1
6
351100
4294550
1
7
351100
4294600
1
8
351050
4294650
1
9
351050
4294700
1
10
351050
4294750
1
11
351000
4294800
1
12
351000
4294850
1
13
351000
4294900
1
14
351000
4294950
1
15
350550
4295000
1
16
350600
4295000
1
17
350650
4295000
1
18
350700
4295000
1
19
350750
4295000
1
20
350800
4295000
1
21
350850
4295000
1
22
350900
4295000
1
23
350950
4295000
1
24
350550
4295050
1
25
350550
4295100
1
26
350550
4295150
1
27
350550
4295200
1
28
350550
4295250
1
29
350550
4295300
1
30
350600
4295350
1
-------
110
31
350600
4295400
1
32
350600
4295450
1
33
350550
4295500
1
34
350450
4295550
1
35
350500
4295550
1
36
350350
4295600
1
37
350400
4295600
1
38
350250
4295650
1
39
350300
4295650
1
40
350100
4295700
1
41
350150
4295700
1
42
350200
4295700
1
43
349950
4295750
1
44
350000
4295750
1
45
350050
4295750
1
-------
Ill
Appendix F
Accounting for the Segment*Designated
Use*Criteria Combinations Used to
Compute the Multi-metric Water Quality
Standards Indicator
Table F1. Segment*designated use*criteria combinations for Chesapeake Bay and its tidal
tributaries.
Waterbody
CBP Segments
& Split
Jurisdiction
Migratory
Spawning &
Nursery
Open
Water
Deep
Water
Deep
Channel
Shallow
Water Bay
Chlorophyll-a
(applies to
Segments
Dissolved
Oxygen
Dissolved
Oxygen
Dissolved
Oxygen
Dissolved
Oxygen
grasses
open water)
Anacostia River
ANATF_DC
DC
X
X
X
X
Anacostia River
ANATF_MD
MD
X
X
X
Appomattox River
APPTF
VA
X
X
X
Back River
BACOH
MD
X
X
X
Big Annemessex River, Lower
BIGMH1
MD
X
X
X
Big Annemessex River, Upper
BIGMH2
MD
X
Bohemia River
BOHOH
MD
X
X
X
Bush River
BSHOH
MD
X
X
X
C&D Canal
C&DOH_DE
DE
X
X
C&D Canal
C&DOHJVID
MD
X
X
X
Northern Chesapeake Bay,
Turkey Pt. South
CB1TF1
MD
X
X
X
Northern Chesapeake Bay,
Susquehanna River and Flats
CB1TF2
MD
X
Upper Chesapeake Bay
CB20H
MD
X
X
X
Upper Central Chesapeake
Bay
CB3MH
MD
X
X
X
X
X
-------
112
Middle Central Chesapeake
Bay
CB4MH
MD
X
X
X
X
X
Lower Central Chesapeake
Bay
CB5MH_MD
MD
X
X
X
X
Lower Central Chesapeake
Bay
CB5MH_VA
VA
X
X
X
X
Western Lower Chesapeake
Bay
CB6PH
VA
X
X
X
Eastern Lower Chesapeake
Bay
CB7PH
VA
X
X
X
Mouth of the Chesapeake Bay
CB8PH
VA
X
X
Chickahominy River
CHKOH
VA
X
X
X
Mouth of the Choptank River
CHOMH1
MD
X
X
X
Lower Choptank River
CHOMH2
MD
X
X
X
Middle Choptank River
CHOOH
MD
X
X
X
Upper Choptank River
CHOTF
MD
X
X
Lower Chester River
CHSMH
MD
X
X
X
X
X
Middle Chester River
CHSOH
MD
X
X
X
Upper Chester River
CHSTF
MD
X
X
X
Corrotoman River
CRRMH
VA
X
X
X
Eastern Bay
EASMH
MD
X
X
X
X
Eastern Branch Elizabeth
River
EBEMH
VA
X
Mouth of the Elizabeth River
ELIPH
VA
X
Elk River, Upper
Elk River, Lower
ELKOH1
ELKOH2
MD
MD
X
X
X
X
Fishing Bay
FSBMH
MD
X
X
X
Gunpowder River, Upper
Gunpowder River, Lower
GUNOH1
GUNOH2
MD
MD
X
X
X
X
Honga River
HNGMH
MD
X
X
Lower James River
JMSMH
VA
X
X
X
X
-------
113
Middle James River
JMSOH
VA
X
X
X
X
Mouth of the James River
JMSPH
VA
X
X
X
Upper James River
JMSTF1
VA
X
X
X
X
Upper James River
JMSTF2
VA
X
X
X
X
Lafayette River
LAFMH
VA
X
Little Choptank River
LCHMH
MD
X
X
Lynnhaven River
LYNPH
VA
X
X
Magothy River
MAGMH
MD
X
X
X
X
Manokin River, Lower
MANMH1
MD
X
X
X
Manokin River, Upper
MANMH2
MD
X
Mattawoman Creek
MATTF
MD
X
X
X
Middle River
MIDOH
MD
X
X
X
Mobjack Bay
MOBPH
VA
X
X
Lower Mattaponi River
MPNOH
VA
X
X
Upper Mattaponi River
MPNTF
VA
X
X
X
Lower Nanticoke River
NANMH
MD
X
X
X
Middle Nanticoke River
NANOH
MD
X
X
X
Upper Nanticoke River
NANTF_DE
DE
X
X
Upper Nanticoke River
NANTFJVID
MD
X
X
Northeast River
NORTF
MD
X
X
X
Patapsco River
PATMH
MD
X
X
X
X
X
Lower Patuxent River, Lower
PAXMH1
MD
X
Lower Patuxent River, Upper
PAXMH2
MD
X
Lower Patuxent River, Mill
Creek
PAXMH3
MD
X
X
X
X
Lower Patuxent River, Cuckold
Creek
PAXMH4
MD
X
Lower Patuxent River, St.
Leonard Creek
PAXMH5
MD
X
-------
114
Lower Patuxent River, Island
Creek
PAXMH6
MD
X
Middle Patuxent River
PAXOH
MD
X
X
X
Upper Patuxent River
PAXTF
MD
X
X
X
Piankatank River
PIAMH
VA
X
X
Piscataway Creek
PISTF
MD
X
X
X
Lower Pamunkey River
PMKOH
VA
X
X
Upper Pamunkey River
PMKTF
VA
X
X
X
Lower Pocomoke River
POCMHJVID
MD
X
X
X
Lower Pocomoke River
POCMH_VA
VA
X
X
X
Middle Pocomoke River
POCOH_MD
MD
X
X
Middle Pocomoke River
POCOH_VA
VA
X
X
Upper Pocomoke River
POCTF
MD
X
X
Lower Potomac River
POTMH_MD
MD
X
X
X
X
X
Lower Potomac River
POTMH_VA
VA
X
X
X
X
X
Middle Potomac River, MD
Mainstem
POTOH_VA
VA
X
X
X
Middle Potomac River, MD
Port Tobacco River
POTOHl_MD
MD
X
X
X
Middle Potomac River, MD
Nanjemoy Creek
POTOH2_MD
MD
X
X
X
Middle Potomac River
POTOH3_MD
MD
X
X
X
Upper Potomac River
POTTF_DC
DC
X
X
X
X
Upper Potomac River
POTTF_MD
MD
X
X
X
Upper Potomac River
POTTF_VA
VA
X
X
X
Rhode River
RHDMH
MD
X
X
X
Lower Rappahannock River
RPPMH
VA
X
X
X
X
X
Middle Rappahannock River
RPPOH
VA
X
X
X
Upper Rappahannock River
RPPTF
VA
X
X
X
Sassafras River, Lower
SASOH1
MD
X
X
X
-------
115
Sassafras River, Upper
SASOH2
MD
X
Southern Branch Elizabeth
River
SBEMH
VA
X
X
Severn River
SEVMH
MD
X
X
X
X
South River
SOUMH
MD
X
X
X
X
Tangier Sound
TAHMH_VA
VA
X
X
Tangier Sound, MD Main
Body
TANMH1_MD
MD
X
X
Tangier Sound, MD Deal Island
to Mouth of Nanticoke River
TANMH2_MD
MD
X
Western Branch Elizabeth
River
WBEMH
VA
X
Western Branch Patuxent
River
WBRTF
MD
X
X
X
Wicomico River
WICMH
MD
X
X
X
West River
WSTMH
MD
X
X
X
Middle York River
YRKMH
VA
X
X
X
Lower York River
YRKPH
VA
X
X
X
TOTAL Number of Segments by Designated Use &
Applicable Criteria
72
92
18
10
90
7
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116
Appendix G
Chesapeake Benthic Index of Biotic
Integrity Recalibration Report
CHESAPEAKE BAY B-IBI RECALIBRATION
Prepared by
Principal Investigators:
Roberto J. Llanso* Versar, Inc.
Daniel M. Dauer ODU
Michael F. Lane ODU
VERSAR, INC.*
Ecological Sciences and Applications
9200 Rumsey Road, Columbia, Maryland 21045
OLD DOMINION UNIVERSITY
Department of Biological Sciences
Old Dominion University, Norfolk, Virginia 23529
Submitted to:
Cindy S. Johnson
Chesapeake Bay Monitoring Manager
Virginia Department of Environmental Quality
629 East Main Street
Richmond, Virginia 23219
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117
August 2016
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118
BACKGROUND AND OBJECTIVES
The Chesapeake Bay Benthic Community Restoration Goals (Ranasinghe et al. 1994)
and the Benthic Index of Biotic Integrity (B-IBI) by which goal attainment is measured
(Weisberg et al. 1997), are today standard tools in management decision making. The
B-IBI is used to assess and monitor trends in Chesapeake Bay health, report condition
for impaired waters assessments under the Clean Water Act (305b reports), support
ambient water quality criteria development and assessment, and characterize benthic
condition in tributary basins to assist in setting restoration goals. The B-IBI was last
validated for tidal freshwater and oligohaline habitats by Alden et al. in 2002.
However, the paucity of data available at that time made the index less robust in the
tidal freshwater and oligohaline regions than in the more saline habitats of the Bay. In
addition, some performance issues have been identified throughout the years, such as:
(1) correct classification efficiencies for the B-IBI seem to be lower than those of the
initial calibration effort for some regions of the Bay, (2) differences in pollution
indicative and sensitive taxa metrics have been identified among the different salinity
habitats which may affect index performance, and (3) high biomass is a desirable
property in low salinity regions but excess biomass in the B-IBI is scored as degraded
and thresholds may need modification. Large datasets that were unavailable to
Weisberg et al. can be used today to test the performance of the B-IBI for the various
salinity habitats, and used to recalibrate the B-IBI.
In this study we used the data available to Weisberg et al. (1997) and new data
assembled from multiple sources and programs that were conducted in Chesapeake Bay
from 1994 to the present. The aim of the study was to re-evaluate the metric thresholds.
Classification efficiencies of samples classified a priori by biological, physical, and
contaminant data were computed on the original Weisberg et al. thresholds and new
thresholds. In addition, the scoring procedure for the biomass metric was re-evaluated,
from a current scoring system (1,3,5,3,1) in which low biomass values (below the lower
restorative threshold) and high biomass values (above the upper restorative threshold)
are considered degraded, to a modified scoring system (1,3,5) in which only low
biomass values are considered degraded. The study considered single replicate and
means of replicate data, and post-1997 data separately because during the course of the
project it became apparent that benthic conditions in Chesapeake Bay had changed
from conditions on which the original calibration effort was based. Validation
assessments were conducted for the following threshold iterations:
1. Original thresholds
2. New thresholds based on data available to Weisberg et al. and new data
3. New thresholds as above and modified biomass procedure
4. New thresholds based on means of replicate samples
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119
5. New thresholds based on means of replicate samples and modified biomass
procedure
6. New threshold based on post-1997 data
Weisberg et al. (1997) classification efficiencies were in the 80-90% range, but
classification efficiencies on new data were somehow lower (70-75% range) in a
subsequent study (Llanso et al. 2009). The present study addresses the question of
whether adjusting thresholds using a larger dataset than that available to Weisberg et
al. (iterations 2-6 above) produce better classification efficiencies than the baseline
(iteration 1). The results of these validation assessments will be taken as the basis for
accepting or rejecting the new thresholds.
DATA ASSEMBLAGE
Source
The datasets in this study were assembled from multiple sources (Table 1) and in a
variety of formats either from: (1) data files downloaded from Internet websites
maintained by the collecting agencies; (2) archived databases maintained by the
participants of this study; (3) direct delivery via email transfer from the collecting
agencies; and (4) data entry/cut and paste from electronic or hard copy versions of
project final reports (Table 1). All samples met a set of selection criteria based on
series of limitations that excluded observations based on geographic location, season
of collection, and compatibility of sample processing.
All data selected were located strictly within the latitude and longitude boundaries of
Chesapeake Bay and its contiguous tidal tributaries and were collected within the B-
IBI index period (Weisberg et al., 1997). This period typically extends from July 1st
through September 30th in any given year; however, additional samples from the first
two weeks of October were included in this study to allow for samples collected later
in the season due to storm events or other issues. With the exception of Virginia's
National Coastal Condition Assessment (NCCA) data, all samples were collected using
a 440-cm2 surface sampling area Young grab. Virginia's NCCA data were collected
using two ponar grabs per sample for a total sample area of 495 cm2. All samples were
sieved through a 0.5-mm mesh screen, and the organisms identified to the lowest
possible taxonomic level. A comparison study between the Young grab and double
ponar grab sampling approach for the Virginia NCCA samples indicated no significant
differences in B-IBI metrics or benthic community dominant species at multiple
stations in multiple habitat types, indicating that these data were compatible for
combined analyses in this study (Dauer and Lane, 2005). Finally, no data were deemed
acceptable for inclusion into the database unless they were accompanied by bottom
salinity and dissolved oxygen measurements, estimates of the percentage of sediment
silt-clay, sediment metal and contaminant concentrations, and 10 or 20-day endpoint
amphipod toxicity test results for either Ampelisca abdita, Leptocheirusphmndosus or
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120
Hyallela azteca. This process resulted in a final dataset comprised of 1,831 samples
(including replicates) collected at 1,051 separate sampling events throughout the length
of the Chesapeake Bay tidal watershed.
Several websites in addition to those listed in Table 1 provided useful assistance in the
construction of the final dataset. National Institute of Standards and Technology's
website for CAS number searches was an extremely helpful tool for assisting with the
standardization of chemical variable names and for help with using CAS numbers to
identify chemical parameter names (and vice-versa) that were absent from data sets
(see http://webbook.nist.gov/chemistrv/cas-ser.html). The Integrated Taxonomic
Information System website and the World Register of Marine Species were also
helpful with resolving taxonomic issues (see http://www.itis.gov/ and
http://www.marinespecies.org/about.php.respectivelv). Verification of station
locations was made by visual inspection of maps created using freeware available at
HamsterMap.com http://www.hamstermap.com/custommap.html.
Reference Site Selection
Prior to the calculation of new thresholds all sites were divided into two a priori stress
categories, i.e. Degraded and Reference (non-degraded). Table 2 summarizes the
Reference selection criteria for this study. All Reference site criteria needed to be met
before a site could be classified as Reference while violation of only one of the criteria
resulted in a site being classified as Degraded. If dissolved oxygen concentrations were
greater than 3.0 ppm, no chemical contaminant concentration exceeded Long et al.'s
(1995) effects range-median concentrations, no more than three chemical contaminants
exceeded Long et al.'s (1995) effects range-low concentrations, the ERM quotient as
defined by Hyland et al. (2003) did not exceed a value of 0.0440, and sediments were
not toxic based on the amphipod toxicity test, sites were classified as Reference.
Additionally samples with less than three species were classified as depauperate and
therefore as being degraded under the assumption that some minimum number of
species would be expected in reference conditions. These criteria were similar to those
of previous studies (Weisberg et al. 1997; Van Dolah et al. 1999; Llanso, et al., 2002)
but derived primarily from those of Llanso et al. (2009) with some modifications.
Previous studies have included samples with toxicity tests conducted with Ampelisca
cibditci; however, this study has included many samples with survival endpoints for
different species, specifically Leptocheirusplumulosus and Hyallela azteca.
Two thirds of the Reference dataset was randomly selected for the computation of new
thresholds and scoring of metric and B-IBI values. This became the Calibration dataset.
One third was reserved to conduct sensitivity and reliability tests, i.e., efficiencies
based on a priori site impact classifications. This became the Validation dataset. The
baseline, i.e., classification efficiencies based on the Weisberg et al. (1997) and Alden
et al. (2002) thresholds, was conducted on the entire dataset, using both the Reference
and Validation datasets.
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121
Table 1. List of data sources and number of observations. An asterisk indicates that the probability-based
monitoring program samples listed were combined with sediment chemistry data and sediment toxicity
data that were collected separately as part of ambient sediment toxicity assessments for the Chesapeake
Bay Program Ambient Toxicity Program.
Project
Time
Period
Number
of
Samples
Source of Biological and Dissolved Oxygen Data
Source of
Chemistry
and
Toxicity
Data
Environmental Monitoring and
Assessment Program Virginian
Province Data (EMAP)
1990-
1993
738
https://archive.epa.gov/emap/archive-
emap/web/html/geographic.html
Same as
Biological
Mid-Atlantic Integrated Assessment 1997-
(MAIA) 1998
370 Versarlnc.
Same as
Biological
Chesapeake Bay Program Ambient 1997-
Toxicity Program (AMTOX) 2003
Versar Inc. and Old Dominion University Long-Term
104 Data
Databases
National Oceanic and Atmospheric
Administration National Status &
Trends Program (NOAA NS&T)
Same ss
1998- https://products.coastalscience.noaa.gov/collections/ltmo ....
2001 nitoring/nsandt/
Maryland Chesapeake Bay Probability- 1997-
Based Monitoring Program (MDRBP)* 2010
55 www.chesapeakebav.net
AMTOX
Reports
Virginia Chesapeake Bay Probability-
Based
Monitoring Program (VARBP)*
1997-
2005
36 www.chesapeakebav.net
AMTOX
Reports
National Coastal Condition Assessment 2005-
(NCCA) 2014
337 Donald Smith, Virginia Department of Environment Quality
Same as
Biological
Total
1831
Table 2. Degraded and Reference site classification criteria based on number of species collected,
dissolved oxygen, sediment chemistry, and sediment toxicity.
Criteria Degraded Reference
Number of Species Collected <3 >3
Bottom Dissolved Oxygen (psu) <2 >3
Effects Range Median Exceedances Any None
Effects Range Low Exceedances >10 <3
<80% and significant difference from
Toxicity , Not toxic
control
ERM Quotient
>0.044 (High and Very High Benthic
Risk Level)
<0.044 (Low to Medium Benthic
Risk Level)
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122
THRESHOLDS
Original Thresholds
Thresholds published in Weisberg et al. (1997) and Alden et al. (2002) were entered in
the project database (Table 3) and used to score metrics and the B-IBI using current B-
IBI protocols whenever data sources did not contain these data, or where the
computations in these data sources were old (EMAP, MAIA) and did not employ the
latest B-IBI methods.
Table 3. B-IBI thresholds derived by Weisberg et al. (1997) and further updated by Alden et al. (2002). Metrics:
Shan = Shannon index, Abun = Abundance (#/m2), Bmas = Biomass (g AFDW/m2), OPA4 = Abundance of
pollution indicative taxa (%), EQA4 = Abundance of pollution sensitive taxa (%), OPBM = Biomass of pollution
indicative taxa (%), EQBM = Biomass of pollution sensitive taxa (%), CAAB = Abundance of carnivore and
omnivores (%), DDAB = Abundance of deep-deposit feeders (%), OPA8 = Abundance of pollution indicative
freshwater taxa (%), OPA = Abundance of pollution indicative oligohaline taxa (%), EQA8 = Abundance of pollution
sensitive oligohaline taxa (%), SCOR = Tolerance Score, PCR = Tanypodinae to Chironomidae abundance ratio
(%). Numbers after metric name indicate percentile threshold, 5th to 95th.
HABITAT
SHAN_05
SHAN_50
ABUN_05
ABUN_25
ABUN_75
ABUN_95
BMAS_05
BMAS_25
BMAS_75
BMAS_95
Tidal Freshwater
800
1,050
4,000
5,500
Oligohaline
180
450
3,350
4,050
Low Mesohaline
1.7
2.5
500
1,500
2,500
6,000
1
5
10
30
High Mesohaline
Sand
2.5
3.2
1,000
1,500
3,000
5,000
1
3
15
50
High Mesohaline
Mud
2
3
1,000
1,500
2,500
5,000
0.5
2
10
50
Polyhaline Sand
2.7
3.5
1,500
3,000
5,000
8,000
1
5
20
50
Polyhaline Mud
2.4
3.3
1,000
1,500
3,000
8,000
0.5
3
10
30
OPA4_50
OPA4_95
EQA4_05
EQA4_50
OPBM_50
OPBM_95
EQBM_05
EQBM_50
CAAB_05
CAAB_50
Tidal Freshwater
Oligohaline
15
35
Low Mesohaline
10
20
5
25
40
80
High Mesohaline
Sand
10
25
10
40
20
35
High Mesohaline
Mud
20
50
10
30
5
30
30
60
10
25
Polyhaline Sand
10
40
25
50
5
15
Polyhaline Mud
15
50
25
40
5
20
30
60
25
40
DDAB_05
DDAB_50
DDAB_95
OPA8_50
OPA8_95
OPA_50
OPA_95
EQA8_05
EQA8_50
Tidal Freshwater
70
95
39
87
Oligohaline
27
95
0.2
26
Low Mesohaline
-------
123
High Mesohaline
Sand
High Mesohaline
Mud
Polyhaline Sand
10
25
Polyhaline Mud
SCOR_50
SCOR_95
PCR_05
PCR_50
Tidal Freshwater
8
9.35
Oligohaline
6
9.05
64
17
Low Mesohaline
High Mesohaline
Sand
High Mesohaline
Mud
Polyhaline Sand
Polyhaline Mud
New Thresholds
New thresholds were calculated for each metric using the Calibration dataset (Table 4).
This dataset included data available to Weisberg et al. (EMAP data) as well as the new
data specified in the data assemblage section of this report. Other threshold iterations
included thresholds based on means of replicate samples, and thresholds based on post-
1997 data, i.e., separating the older data (EMAP, MAIA) from the most current data
(Ambient Toxicity, probability-based monitoring, NOAA NS&T, and NCCA).
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124
Table 4. New thresholds derived with data assembled for this project, including data available to
Weisberg et al. (EMAP data) and new data. See Table 3 for metric names and numbers after metric
names.
HABITAT
SHAN_05
SHAN_50
ABUN_05
ABUN_25
ABUN_75
ABUN_95
BMAS_05
BMAS_25
BMAS_75
BMAS_95
Tidal Freshwater
1,409
2,864
6,773
9,817
Oligohaline
432
1,318
3,977
16,318
Low Mesohaline
1.5
2.4
750
1,886
3,682
11,932
0.128
0.445
1.6
6.2
High Mesohaline
Sand
1.5
2.7
566
1,307
3,352
9,455
0.101
0.386
1.6
8.6
High Mesohaline
Mud
1.6
2.7
523
1,068
2,318
5,999
0.143
0.303
0.909
1.8
Polyhaline Sand
1.4
3.2
909
1,778
4,932
9,591
0.119
0.505
5.1
14.9
Polyhaline Mud
1.6
3
682
1,776
6,175
9,636
0.202
0.524
2.3
33.7
OPA4_50
OPA4_95
EQA4_05
EQA4_50
OPBM_50
OPBM_95
EQBM_05
EQBM_50
CAAB_05
CAAB_50
Tidal Freshwater
Oligohaline
0
26.3
Low Mesohaline
5.5
71.7
0.94
18.3
4.4
26.8
High Mesohaline
Sand
16.3
75.8
0.72
22.3
3.4
23.2
High Mesohaline
Mud
21.9
68.4
2
19.5
27.3
79
0.52
7.5
4.5
18.2
Polyhaline Sand
6.3
35.3
3.9
53.4
4.8
46.3
Polyhaline Mud
19.9
73.1
5.7
33.8
16.5
62
0.57
20.6
2.8
29.7
DDAB_05
DDAB_50
DDAB_95
OPA8_50
OPA8_95
OPA_50
OPA_95
EQA8_05
EQA8_50
Tidal Freshwater
71
95.1
39
87
Oligohaline
15.8
93.8
0
2.3
Low Mesohaline
High Mesohaline
Sand
High Mesohaline
Mud
Polyhaline Sand
0.16
20.3
Polyhaline Mud
SCOR_50
SCOR_95
PCR_05
PCR_50
Tidal Freshwater
8.7
9.7
Oligohaline
7.3
9.6
0
0
Low Mesohaline
High Mesohaline
Sand
High Mesohaline
Mud
Polyhaline Sand
Polyhaline Mud
-------
125
Comparison Among Thresholds
New thresholds derived with the reference dataset assembled for this project were
lower than the original Weisberg et al. (1997) and Alden et al. (2000) thresholds for
metrics for which low numbers indicate degraded conditions, and this difference was
larger for the lower, 5th percentile threshold. These metrics include Shannon index
(Figure 1), abundance and biomass of pollution sensitive taxa (Figures 5 and 7),
abundance of carnivore and omnivores (Figure 8), abundance of deep-deposit feeders
(Figure 9, but see below), and abundance of pollution sensitive oligohaline taxa (Figure
10).
For metrics for which high numbers indicate degraded conditions, the new thresholds
were higher than the original thresholds (Figures 4, 6, and 11), except for abundance
of pollution indicative taxa in the Polyhaline Sand habitat. For pollution indicative
taxa, this difference was larger for the upper, 95th percentile threshold (Figures 4 and
6).
For abundance, for which low numbers and high numbers indicate degraded conditions,
the new 5th percentile threshold was lower than the original 5th percentile threshold, and
the new 95th percentile threshold was higher than the original 95th percentile threshold
(Figure 2). This was true for the high salinity habitats, but for the low salinity habitats
(Tidal Freshwater, Oligohaline, and Low Mesohaline), the new 5th percentile threshold
was higher than the original threshold (Figure 2).
For biomass, for which low numbers and high numbers also indicate degraded
conditions in the current B-IBI, the new 5th percentile threshold was lower than the
original 5th percentile threshold; however,
the new 95th percentile threshold was much lower (not higher, as with abundance) than
the original 95th percentile threshold (Figure 3).
Deep-deposit feeder abundance is defined differently in the Polyhaline Sand habitat
than in the Tidal Freshwater habitat. In the Polyhaline Sand habitat low numbers of
deep-deposit feeders indicate degraded conditions whereas in the Tidal Freshwater,
high numbers of deep-deposit feeders indicate degraded conditions. In the Tidal
Freshwater habitat there was no difference between the new and the original thresholds
for deep-deposit feeders (Figure 9). Also, in the same habitat there was little difference
between the new 95th percentile threshold and the original 95th percentile threshold for
pollution indicative taxa (Figure 10).
The above results can be interpreted as follows:
1. Lowered thresholds relative to those of Weisberg et al.'s effort indicate lower
metric values in recent samples. Conversely, for metrics for which high
numbers indicate degraded conditions, higher thresholds indicate higher metric
values in recent samples.
-------
126
2. Differences between the new and the original thresholds are larger at the 5th
and 95th percentile thresholds than at the 25th, 50th, or 75th percentile thresholds,
indicating increased depauperate conditions in Chesapeake Bay.
3. As thresholds are lowered (5th) or raised (95th), the number of samples in the
validation dataset that score "1" for degraded conditions decrease, therefore
increasing the B-IBI and giving the false impression that conditions in
Chesapeake Bay have improved should these thresholds be adopted.
4. High biomass values (above restorative thresholds) have traditionally been
viewed as indicating degraded conditions. However, lower values in recent
samples for all biomass samples suggest that this concept needs revision.
5. The percentage of pollution tolerant organisms in the Tidal Freshwater
(tubificid oligochaetes and many insect larvae) has not changed substantially
in more recent samples, suggesting that conditions in this habitat have not
changed.
As shown in the next section, classification efficiencies of the B-IBI using the new
thresholds did not improve over the baseline or current condition using the Weisberg
et al. (1997) and Alden et al. (2002) thresholds.
-------
127
Low Mesohaline
High Mesohaline Sand
WFISBFRG
WFISBFRG
NEW
High Mesohaline Mud
Polyhaline Sand
M WFISBFRG
¦ NCW
Polyhaline Mud
Figure 1. Comparison of thresholds between the original Reference dataset ofWeisberg etal. (1997)
and the new Reference dataset assembled for this project for Shannon index (H').
-------
128
I. ii
Tidal Freshwater
9,81 /
6.773
A KM
i /•ii'";
ABUN 05 A8UN 2S ABUN 75 ABUN 95
14000
12000
10000
ROOO
6000
4000
2000
Low Mesohaline
11,932
3,682
500 750
ABUN 05 ABUN 25 ABUN 75 ABUN 05
High Mesohaline Mud
5,999
! .'I .i;: I
ABUN 05 ABUN 25 ABUN 75 ABUN 95
Polyhaline Mud
1 snf."6
¦m
M
ABLJN 05 ABUN 25 ABUN 75 ABUN 95
¦ WEISBERG
iNfW
¦ WEISBERG
¦ NEW
¦ WEISBERG
¦ NEW
I WEISBERG
¦ NEW
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
Oligohaline
1.318
180 432 450m
ABUN_05 ABUN2S ABUN75 ABIJN_95
High Mesohaline Sand
8000
6000
4000
2000
1^"fi307
ABUN_05 ABU N_25 ABUN_75 ABUN_95
Polyhaline Sand
8 000
*>,00®,932
1500
3,000
km
_909
ABUN 05 ABUN 25 ABUN 75 ABUN 95
¦ WEISBERG
¦ Nrw
¦ WEISBERG
¦ NEW
I WEISBERG
¦ NEW
Figure 2 Comparison of thresholds between the original Reference dataset ofWeisberg et al. (1997)
and the new Reference dataset assembled for this project for abundance (#/m2).
-------
129
Low Mesohaline
5
1 0.1
0.4
DMAS 05 BMAS 25 BMAS 75 BMAS 95
BMAS 05 BMAS 25 BMAS 75 BMAS 95
Polyhaline Mud
i WFISBFRG
¦ NFW
High Mesohaline Mud
50
10
0.5 0 1 ^0.3 ^09^
1.8
¦ WEISBERG
¦ NEW
High Mesohaline Sand
50
i
8.6
j_o.i
¦
BMAS 05 RMAS 25 BMAS 75 BMAS 95
I WFISBFRG
¦ NFW
BMAS_05 BMAS_25 BMAS 75 BMAS 95
Polyhaline Sand
50
20
14.9
5
1 0.1 HBO.S
,
¦ ,
BMAS 05 BMAS ?5 RMAS 75 BMAS 95
Figure 3. Comparison of thresholds between the original Reference dataset of Weisberg et al. (1997)
and the new Reference dataset assembled for this project for biomass (g AFDW/m2).
-------
130
Low Mesohaline
71.7
¦
20
10
> WEISBFRG
¦ NEW
High Mesohaline Sand
I WEISBERG
¦ NEW
High Mesohaline Mud 684
50 ¦
m
¦
OPA4_50
OPA4_%
I WEISBERG
> NFW
Polyhaline Sand
I
¦ WEISBERG
¦ NFW
Polyhaline
Mud
73.1
¦
50
19.9
J
I WEISBFRG
¦ NEW
Figure 4. Comparison of thresholds between the original Reference dataset of Weisberg et al. (1997)
and the new Reference dataset assembled for this project for abundance of pollution indicative taxa (%).
-------
131
Low mesohaline
2b
1
18.3
-
EQA4 05
EQA4 50
¦ WEISBERG
¦ NEW
High mesohaline Mud
30
19.5
¦
I WEISBERG
¦ NEW
Polyhaline Mud
40
¦ 33.8
2 S
¦
1
5.7
I WEISBERG
¦ NEW
High Mesohaline Sand
40
22.3
¦¦
WzL
EQA4 05
EQA40S
EQA4 50
EQA4S0
I WEISBERG
¦ NEW
Polyhaline Sand
53.4
i
25
¦
I WEISBERG
i NFW
EQA4_05 FQA4_50
Figure 5. Comparison of thresholds between the original Reference dataset of Weisberg et al. (1997)
and the new Reference dataset assembled for this project for abundance of pollution sensitive taxa (%).
-------
132
90
80
70
60
'j0
40
30
20
10
High Mesohaline Mud 79.0
U. J
LI
¦ WFISBFRG
¦ NEW
Polyhaline Mud
62.0
I
16.5
20
¦ WFISBFRG
¦ NEW
Polyhaline Sand
¦
¦ WEISBERG
¦ NEW
OPBM_50 f)PBM_95
Figure 6. Comparison of thresholds between the original Reference dataset ofWeisberg et al. (1997)
and the new Reference dataset assembled for this project for biomass of pollution indicative taxa (%).
Low Mesohaline so
40
1
?68
EQBMOS
70
60
SO
40
30
20
EQBM_S0
Polyhaline Mud
60
¦
30
¦
20.6
¦
High Mesohaline Mud
60
I
30
7.S
k
¦
¦ WEISBERG
¦ NEW
Figure 7. Comparison of thresholds between the original Reference dataset ofWeisberg et al. (1997)
and the new Reference dataset assembled for this project for biomass of pollution sensitive taxa (%).
-------
133
_
,
Oligohaline
High Mesohaline Sand
35
35
1
!
26.3
23 ?
¦ WEISBERG
20
¦ WEISBERG
»
¦ NFW
¦ NEW
¦
3.4
I1
¦
CAAB_05
CAAB_50
CAAB_05
CAAB_50
_
AC
40
High Mesohaline Mud
40
Polyhaline Mud to
29.7
25
25
¦ WEISBERG
18 ?
¦ WEISBERG
¦ NFW
¦ NFW
10
M45
mm
CAA605
CAAB_S0
CAAB05
CAAB_50
Figure 8.Comparison of thresholds between the original Reference dataset ofWeisberg et al. (1997) and
the new Reference dataset assembled for this project for abundance of carnivore and omnivores (%)
Tidal Freshwater
70 71-0
¦ NEW
DDAR.SO
DDABJ55
Polyhaline Sand
10
1
Figure 9. Comparison of thresholds between the original Reference dataset ofWeisberg et al. (1997)
and the new Reference dataset assembled for this project for abundance of deep-deposit feeders (%).
-------
134
100
90
80
70
60
50
40
30
20
10
0
Tidal freshwater
S0.8
39
Oligohaline
36
0.3 0
2.3
¦ WCISBERG
¦ NEW
Oligohaline
93 8
-
1
¦
Figure 10. Comparison of thresholds between the original Reference dataset ofWeisberg et al. (1997)
and the new Reference dataset assembled forthis project for abundance of pollution indicative freshwater
and oligohaline taxa (%, upper panel), and abundance of pollution sensitive oligohaline taxa (%, lower
panel).
10
9
Tidal Fre§^water
9.35 9-7
¦
8
7
6
¦ WEISBFRG
4
3
2
1
SCOR_50 SCOR_95
Oligohaline
srOK so
Figure 11. Comparison of thresholds between the original Reference dataset ofWeisberg et al. (1997)
and the new Reference dataset assembled forthis project for Tolerance Score.
-------
135
VALIDATION ASSESSMENTS
Original Thresholds
Validation assessment of the original B-IBI thresholds developed by Weisberg et al.
(1997) and later updated by Alden et al. (2002) showed classification efficiencies
ranging from a minimum of 45% correct classification in the Tidal Freshwater habitat
type to a maximum of 81% correct classification in the Polyhaline Mud habitat (Table
5). Classification efficiencies for Low Mesohaline, High Mesohaline Sand, High
Mesohaline Mud, and Polyhaline Mud habitat types were higher for Degraded sites
than for Reference sites ranging from 55% to 92% (Table 5). Classification efficiencies
were higher for Reference sites for Tidal Freshwater, Oligohaline, and Polyhaline Sand
habitats in the 68-73% range (Table 5).
Table 5. Classification efficiencies within habitat type and across all habitat types for both Reference and
Degraded sites based on B-IBI values scored using thresholds defined in Weisberg et al. (1997) and
Alden et al. (2002) and the entire calibration and validation datasets assembled for this project. Provided
are the total number of validation samples (Sample #) and the number and percentages of samples
correctly classified within each habitat type and a priori impact classifications. Overall classification
efficiency for this B-IBI is provided in bold.
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Tidal Freshwater
Reference
55
40
72.7
Degraded
161
58
36.0
Total
216
98
45.4
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Oligohaline
Reference
24
17
70.8
Degraded
111
70
63.1
Total
135
87
64.4
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Low Mesohaline
Reference
92
51
55.4
Degraded
214
156
72.9
Total
306
207
67.6
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
High Mesohaline Sand
Reference
189
91
48.2
Degraded
58
32
55.2
Total
247
123
49.8
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
High Mesohaline Mud
Reference
106
30
28.3
Degraded
309
241
78.0
Total
415
271
65.3
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Polyhaline Sand
Reference
240
163
67.9
Degraded
46
23
50.0
Total
286
186
65.0
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Polyhaline Mud
Reference
47
18
38.3
Degraded
179
164
91.6
Total
226
182
80.5
Overall
1831
1154
63.0
-------
136
New Thresholds With and Without Modified Biomass Scoring
Validation of the B-IBI scored using new thresholds developed from old (data available
to Weisberg et al.) and new probability-based data showed total classification
efficiencies ranging from a minimum of 31% correct classification in the Oligohaline
habitat type to a maximum of 68% correct classification in the Polyhaline Sand habitat
(Table 6). Classification efficiencies for Reference sites were substantially higher than
for Degraded sites (Table 6) ranging from 56% in the Oligohaline to 100% correct
classification in Polyhaline Sand. Classification efficiencies for Degraded sites were
less than 50% in all habitat types (Table 6). Modification of the procedure for scoring
biomass using the same thresholds resulted in little and often no change in classification
efficiency for all of the habitat types for both Reference and Degraded sites (Table 7).
Table 6. Classification efficiencies within habitat type and across all habitat types for both Reference and
Degraded sites based on B-IBI values scored using new thresholds and the validation dataset assembled
for this project. Provided are the total number of validation samples (Sample #) and the number and
percentages of samples correctly classified within each habitat type and a priori impact classifications.
Overall classification efficiency for this B-IBI approach is provided in bold.
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Tidal Freshwater
Reference
22
15
68.2
Degraded
161
49
30.4
Total
183
64
35.0
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
9
5
55.6
Oligohaline
Degraded
111
32
28.8
Total
120
37
30.8
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Low Mesohaline
Reference
33
25
75.8
Degraded
214
101
47.2
Total
247
126
51.0
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
High Mesohaline Sand
Reference
65
53
81.5
Degraded
58
18
31.0
Total
123
71
57.7
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
High Mesohaline Mud
Reference
39
32
82.1
Degraded
309
159
51.5
Total
348
191
54.9
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Polyhaline Sand
Reference
81
77
95.1
Degraded
46
9
19.6
Total
127
86
67.7
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Polyhaline Mud
Reference
15
15
100
Degraded
179
70
39.1
Total
194
85
43.8
Overall
1342
660
49.2
-------
137
Table 7. Classification efficiencies within habitat type and across all habitat types for both Reference and
Degraded sites based on B-IBI values scored using new thresholds, the validation dataset assembled for
this project, and a modified procedure for scoring biomass. Provided are the total number of validation
samples (Sample #) and the number and percentages of samples correctly classified within each habitat
type and a priori impact classifications. Overall classification efficiency for this B-IBI approach is provided
in bold.
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Reference
22
15
68.2
Tidal
Freshwater
Degraded
161
49
30.4
Total
183
64
35
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Reference
9
5
55.6
Oligohaline
Degraded
111
32
28.8
Total
120
37
30.8
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Reference
33
28
84.9
Low
Mesohaline
Degraded
214
96
44.9
Total
247
124
50.2
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
High
Reference
65
56
86.2
Mesohaline
Degraded
58
18
31
Sand
Total
123
74
60.2
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
High
Reference
39
34
87.2
Mesohaline
Degraded
309
149
48.2
Mud
Total
348
183
52.6
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Reference
81
76
93.8
Polyhaline
Sand
Degraded
46
9
19.6
Total
127
85
66.9
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Reference
15
14
93.3
Polyhaline
Mud
Degraded
179
72
40.2
Total
194
86
44.3
Overall
1342
653
48.7
-------
138
New Thresholds Based on Means With and
Without Modified Biomass Scoring
Classification efficiencies obtained for the B-IBI based on thresholds developed using
a calibration dataset of mean replicate values were, in general, similar to those obtained
from thresholds developed using a calibration dataset of individual replicate values
(presented above), although the overall classification efficiency improved slightly
(Table 8). Total classification efficiencies by habitat type ranged from a minimum of
32% correct classification in the Oligohaline habitat type to a maximum of 71% correct
classification in Polyhaline Sand habitat (Table 8). In general, classification
efficiencies for Reference sites were substantially higher within habitat types than for
Degraded sites (Table 8). Modification of the procedure for scoring biomass resulted
in almost no changes in classification efficiencies with the exception of a slight
improvement in the classification of Degraded sites within the Polyhaline Sand habitat
(Table 9).
Table 8. Classification efficiencies within habitat type and across all habitat types for both Reference and
Degraded sites based on B-IBI values scored using new thresholds (developed from mean replicate
values) and the validation dataset assembled for this project. Provided are the total number of validation
samples (Sample #) and the number and percentages of samples correctly classified within each habitat
type and a priori impact classifications. Overall classification efficiency for this B-IBI approach is provided
in bold.
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
7
4
57.1
Tidal Freshwater
Degraded
84
46
54.8
Total
91
50
54.9
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
5
4
80
Oligohaline
Degraded
55
15
27.3
Total
60
19
31.7
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
15
13
86.7
Low Mesohaline
Degraded
107
37
34.6
Total
122
50
41
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
39
37
94.9
High Mesohaline Sand
Degraded
32
9
28.1
Total
71
46
64.8
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
High Mesohaline Mud
Reference
Degraded
18
181
16
85
88.9
47
-------
Total
199
101
50.8
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
52
49
94.2
Polyhaline Sand
Degraded
26
6
23.1
Total
78
55
70.5
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
11
11
100
Polyhaline Mud
Degraded
109
40
36.7
Total
120
51
42.5
Overall
741
372
50.2
-------
140
Table 9. Classification efficiencies within habitat type and across all habitat types for both Reference and
Degraded sites based on B-IBI values scored using new thresholds (developed from mean replicate
values), the validation dataset assembled for this project, and a modified procedure for scoring biomass.
Provided are the total number of validation samples (Sample #) and the number and percentages of
samples correctly classified within each habitat type and a priori impact classifications. Overall
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
7
4
57.1
Tidal Freshwater
Degraded
84
46
54.8
Total
91
50
54.9
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
5
4
80.
Oligohaline
Degraded
55
15
27.3
Total
60
19
31.7
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
15
14
93.3
Low Mesohaline
Degraded
107
35
32.7
Total
122
49
40.2
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
39
36
92.3
High Mesohaline Sand
Degraded
32
28.1
9
Total
71
45
63.4
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
18
16
88.9
High Mesohaline Mud
Degraded
181
84
46.4
Total
199
100
50.3
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
52
49
94.2
Polyhaline Sand
Degraded
26
6
23.1
Total
78
55
70.5
Correctly Classified
Habitat
a priori Classification
Sample #
Number
Percentage
Reference
11
11
100
Polyhaline Mud
Degraded
109
45
41.3
Total
120
56
46.7
Overall
741
374
50.5
-------
141
Table 10. Classification efficiencies within habitat type and across all habitat types for both Reference
and Degraded sites based on B-IBI values scored using new thresholds (developed from mean replicate
values of post-1997 samples), the validation dataset assembled for this project, and a modified procedure
for scoring biomass. Provided are the total number of validation samples (Sample #) and the number
and percentages of samples correctly classified within each habitat type and a priori impact classifications.
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Tidal Freshwater
Reference
Degraded
Total
7
50
57
7
18
25
100
36
43.9
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Oligoha line
Reference
Degraded
Total
4
27
31
4
10
14
100
37
45.2
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Low Mesohaline
Reference
Degraded
Total
10
56
66
9
7
16
90
12.5
24.2
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
High Mesohaline Sand
Reference
Degraded
Total
30
20
50
26
10
36
86.7
50
72
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
High Mesohaline Mud
Reference
Degraded
Total
20
120
140
17
54
71
85
45
50.7
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Polyhaline Sand
Reference
Degraded
Total
41
18
59
39
4
43
95.1
22.2
72.9
Correctly Classified
Habitat
a priori
Classification
Sample #
Number
Percentage
Polyhaline Mud
Reference
Degraded
Total
12
74
86
12
12
24
100
16.2
27.9
Overall
489
229
46.8
-------
142
Thresholds based on data collected after 1997
Classification efficiencies obtained for the B-IBI based on thresholds developed using a
calibration dataset of mean replicate values and only post-1997 data (i.e., EMAP and MAIA
datasets excluded) were slightly lower overall to those obtained using other methods (Table
10). Total classification efficiencies by habitat type ranged from a minimum of 24% correct
classification in the Low Mesohaline habitat to a maximum of 73% correct classification in the
Polyhaline Sand habitat (Table 10). In general, classification efficiencies for Reference sites
were substantially higher within habitat types than for Degraded sites.
Summary
Overall, modifications to the original thresholds of Weisberg et al. (1997) and Alden
et al. (2002) based either on changes to the datasets used or the procedure for scoring
biomass resulted in decreases in overall classification efficiencies (Figure 12). A closer
examination of classification efficiencies within habitat types and a priori impact
classification groups indicates that the B-IBI based on new thresholds (Iteration 1), in
general, had higher classification efficiencies for Reference sites while the B-IBI based
on original thresholds (the baseline) had higher classification efficiencies for Degraded
sites for most habitat types (Figure 13). Similar results were obtained for other
iterations, including modifications to the existing biomass scoring procedure (see
Tables 7 to 10). These results indicate that additional datasets or modifications to
existing procedures did not improve the classification efficiency of the B-IBI in any of
the habitats to a degree that would warrant adoption of any of the iterations here
examined.
Overall Percent Correct
Classification By Scenario
70.0 ¦
g __
li 60.0 ¦
"IT?
M
nj
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Weisberg et al., 1997 New Thresholds Modified Biomass Means of All Data Means with Post 1997 Data
Scoring Modified Biomass
Scoring
Figure 12. Overall classifications efficiencies for data assembled in this project using the original
Weisberg et al. (1997) and Alden et al. (2002) thresholds (the baseline), and new thresholds with or
without further modifications to datasets or biomass scoring procedure
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143
¦ Reference (Weisberg et al., 1997)
¦ Reference (New)
¦ Degraded (Weisburg et al., 1997)
Degraded (New)
Tidal Freshwater Oligohaline Low Mesohaline High Mesohaline High Mesohaline Polyhaline Sand Polyhaline Mud
Sand Mud
Figure 13. Classification efficiencies for validation dataset for Reference and Degraded sites by habitat
type obtained using the original (Weisberg et al., 1997) thresholds and new thresholds for the B-IBI
WATER DEPTH ANALYSIS
The validation assessments indicated that additional data did not improve the
classification efficiency of the B-IBI. Further, the new calibration data included many
more depauperate samples than the data of the initial calibration effort. Also, the new
data did not improve the challenges in the low salinity habitats. When the calibration
data were segregated by depth, it was noted shallow versus deep differences among the
values of a metric. For data after 1996 (i.e., excluding the EMAP samples), the lowest
values in the calibration dataset below the lower 5th percentile threshold (or the highest
values above the upper 95th percentile threshold) were on average in shallow water for
most metrics (Table 11). Some of the differences were statistically significant. The
Polyhaline Sand and Polyhaline Mud habitats have a water depth boundary of about 3-
4 m (Table 12). This corresponds to Reilly's 4 m boundary, an area of "maximum
interaction between human activities and biological resources" (Reilly 1996). Thus,
water depth may be a surrogate for nearshore anthropogenic effects.
Comparison of Classification
Efficiencies By Habitat Types
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144
Table 11. Average water depth (m) of calibration samples for metrics below the original Weisberg et al.
(1997) 5th percentile threshold, or above the 95th percentile threshold. Data after 1996. Numbers in bold
and underlined are significantly different by t-test at the 0.05 probability level. Shaded cells indicate
depths that are, on average, lower for "bad" values of a metric (values below the 5th percentile threshold
or above the 95th percentile threshold) than for "good" values. Blanks denote metrics that are not
Habitat
Shannon (H')
Abundance
Biomass
Pollution
Indicative
Abundance
Pollution
Sensitive
Abundance
Pollution
Indicative
Biomass
Low
High
Low/High
Medium
Low
High
High*
Low
Low
High
High*
Low
Polyhaline Sand
4.0
4.8
3.2
5.1
3.7
5.5
4.5
4.5
3.4
5.1
Polyhaline Mud
3.1
7.1
3.6
6.1
4.4
6.0
4.5
7.1
High Mesohaline Mud
3.8
2.7
3.3
2.6
2.4
3.4
2.8
2.9
High Mesohaline Sand
2.4
2.7
2.2
2.8
2.8
2.4
2.8
2.4
1.9
2.9
Low Mesohaline
1.9
2.1
3.2
1.9
1.8
2.5
2.1
2.1
Oligohaline
4.1
2.3
3.2
2.5
2.0
3.2
Tidal Freshwater
3.0
3.0
n/a
3.0
Habitat
Pollution
Sensitive
Biomass
Carnivore and
Omnivore
Abundance
Deep Deposit
Feeder
Abundance
Tolerance
Score
Tanypodinae/
Chironomidae
Abundance
Ratio
Low
High
Low
High
Low
High
High*
Low
High*
Low
Polyhaline Sand
4.8
4.3
Polyhaline Mud
4.0
7.3
3.2
8.7
High Mesohaline Mud
2.7
3.5
2.1
3.1
High Mesohaline Sand
2.1
3.0
Low Mesohaline
1.9
2.5
Oligohaline
2.0
2.9
2.4
2.7
1.5
2.8
Tidal Freshwater
3.0
n/a*
5.5
2.8
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145
Table 12. Comparisons of B-IBI component metrics between shallow (<=4 m) and deep (>4 m) samples
in the Polyhaline Sand Reference habitat. Provided are descriptive statistics, results of two-tailed
Student's t-tests and equality of variance tests for each metric. If test for equality of variance is significant,
then t-test provided is for unequal variances.
Abundance (#/m2)
Descriptive Statistics
t Test
Equality of Variance
Test
Class
N
Mean
Std.
Dev.
Std.
Error
DF
1 P>t
Value
Num
DF
Den
DF
F P>F
Shallow
52
7,876
21359.8
2962.1
52.1
-1.64 0.11
51
42
109.4 <0.001
Deep
43
2,997
2042
311.4
Biomass (g AFDW/m2)
Descriptive Statistics
t Test
Equality of Variance
Test
Class
N
Mean
Std.
Dev.
Std.
Error
DF
1 P>t
Value
Num
DF
Den
DF
F P>F
Shallow
52
3.19
16.01
2.22
52.4
-0.68 0.5
51
42
86.66 <0.001
Deep
43
1.67
1.72
0.26
Shannon Index (H')
Descriptive Statistics
t Test
Equality of Variance
Test
Class
N
Mean
Std.
Dev.
Std.
Error
DF
1 P>t
Value
Num
DF
Den
DF
F P>F
Shallow
52
2.58
0.9
0.12
93
1.85 0.07
51
42
1.03 0.93
Deep
43
2.92
0.89
0.14
Pollution Sensitive Abundance (%)
Descriptive Statistics
t Test
Equality of Variance
Test
Class
N
Mean
Std.
Dev.
Std.
Error
DF
1 P>t
Value
Num
DF
Den
DF
F P>F
Shallow
52
48.9
27.73
3.85
93
-1.29 0.2
51
42
1.24 0.47
Deep
43
41.9
24.89
3.8
Pollution Indicative Biomass (%)
Descriptive Statistics
t Test
Equality of Variance
Test
Class
N
Mean
Std.
Dev.
Std.
Error
DF
1 P>t
Value
Num
DF
Den
DF
F P>F
Shallow
52
19
18.22
2.53
90.7
-2.97 <0.001
51
42
2.03 0.02
Deep
43
9.48
12.78
1.95
Deep Deposit Feeder Abundance (%)
Descriptive Statistics
t Test
Equality of Variance
Test
Class
N
Mean
Std.
Dev.
Std.
Error
DF
1 P>t
Value
Num
DF
Den
DF
F P>F
Shallow
52
23.8
20.69
2.87
87.9
-1.92 0.06
51
42
2.44 <0.001
Deep
43
17.1
13.25
2.02
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146
POLLUTION TOLERANCE
The pollution tolerance of benthic species typically is categorized based on their life-
history characteristics (Dauer 1993). However, in some cases life-history
characteristics are inconsistent with pollution tolerance (Seitz and Schaffner 1995).
Capitellid polychaetes, for example, have been identified as opportunistic (high
reproductive output, rapid growth), but in Chesapeake Bay a key species, Mediomastus
ambiseta, was found in higher numbers in reference sites than in degraded sites
(Weisberg et al. 1997). This species is currently listed as pollution sensitive in the B-
IBI. One concern with this species listed as pollution sensitive is its dominance
throughout the Elizabeth River. Of special concern is its dominance in the Southern
Branch and some smaller creeks of the Southern Branch, all considered highly
anthropogenically stressed. In addition this species has increased greatly in dominance
over the years. Based on these concerns, Mediomastus ambiseta classification as
pollution sensitive in the B-IBI was reconsidered during the present effort by testing
for differences in abundance among sites in the more recent data.
Results of t-test comparing the abundance of M. ambiseta between Reference and
Degraded sites indicated no significant differences in means for any of the habitat types
(Table 13). However, results were more complicated when examined using
nonparametric procedures and distribution tests. Wilcoxon two-sample tests for both
High Mesohaline Mud, High Mesohaline Sand, and Polyhaline Mud habitats indicated
median abundances of M. ambiseta significantly higher in Reference than in Degraded
sites. Additionally there were significantly differences in the distribution of this species
between Reference and Degraded sites for these habitat types (Table 13). In the
Polyhaline Sand, no significant differences between medians or distributions were
observed.
These results indicate thatM ambiseta could not be consistently characterized as being
strictly representative of either Reference or Degraded sites. This species has been
referred to as opportunistic and pollution indicative based both on ecological surveys
(Grassle and Grassle, 1974; Boesch, 1977; Billheimer et al., 1997) and experimental
results (Shaffner, 1990). Given the evidence from the literature in combination with
the results of this study, it is likely that retaining M. ambiseta as either pollution
sensitive or pollution indicative for the purposes of the B-IBI calculation is likely to
result in sample misclassifications, and is therefore unwarranted.
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147
Table 13. Summary of two sample comparisons of mean and median abundance of Mediomastus
ambiseta between Degraded and Reference sites for High Mesohaline Sand, High Mesohaline Mud,
Polyhaline Sand and Polyhaline Mud habitat types. Provided for each habitat type are descriptive
statistics, t-test results, equality of variance tests (all indicating significantly different variances), Wilcoxon
two-sample, and Kolmogorov-Smirnov comparisons of distributions.
High Mesohaline Sand
Descriptive Statistics
t-T est
(unequal Variances)
Equality of
Variance Test
Wilcoxon
Two Sample test
Kolmogorov-
Smirnov Test
Impact Classification
Std.
N Mean Dev.
Std.
Error
D.F. tValue P>t
F P > F
W
Value Z P>Z
KSa P>KSa
Degraded
56 27.7 184.40
24.64
57.78 0.47 0.641
12.99 <0.001
5506 -2.43 0.008
1.49 0.023
Reference
172 16.0 51.16
3.90
High Mesohaline Mud
Descriptive Statistics
t-T est
(unequal Variances)
Equality of
Variance Test
Wilcoxon
Two Sample T-test
Kolmogorov-
Smirnov Test
Impact Classification
Std.
N Mean Dev.
Std.
Error
D.F. tValue P>t
F P > F
W
Value Z P>Z
KSa P>KSa
Degraded
264 7.3 49.69
3.06
211.85 -1.21 0.224
1.47 0.027
22307 6.52 <0.001
2.72 <0.001
Reference
99 13.5 40.98
4.12
Polyhaline Sand
Descriptive Statistics
t-T est
(unequal Variances)
Equality of
Variance Test
Wilcoxon
Two Sample T-test
Kolmogorov-
Smirnov Test
Impact Classification
Std.
N Mean Dev.
Std.
Error
D.F. tValue P>t
F P > F
W
Value Z P>Z
KSa P>KSa
Degraded
41 28.3 36.40
5.69
78.38 -0.09 0.933
1.93 0.016
4602 -0.13 0.4463
0.8 0.540
Reference
185 28.9 50.55
3.72
Polyhaline Mud
Descriptive Statistics
t-T est
(unequal Variances)
Equality of
Variance Test
Wilcoxon
Two Sample T-test
Kolmogorov-
Smirnov Test
Impact Classification
Std.
N Mean Dev.
Std.
Error
D.F. tValue P>t
F P > F
W
Value Z P>Z
KSa P>KSa
Degraded
152 26.4 63.26
5.13
78.62 -1.58 0.119
1.74 0.045
5338 4.78 <0.001
2.35 <0.001
Reference
40 40.8 47.97
7.58
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148
CONCLUSIONS
1. Additional data did not improve the classification efficiency of the B-IBI in any of the
habitats.
2. Data did not improve the challenges in the lower salinity habitats. This is a global issue
with no obvious solution.
3. Samples meeting the reference criteria included enough samples with low diversity,
abundance, biomass, and numbers of pollution indicate and sensitive taxa to bias the
data toward too many false positives of undegraded condition.
4. There are at least two hypotheses relative to the lowered thresholds and unacceptable
correct classification efficiencies compared to the baseline:
a. Anthropogenic stress criteria not accounted for by this study might better classify
samples into Reference and Degraded categories. However, the same criteria that were
used in the initial calibration effort were used in this study. Water depth as a surrogate
for nearshore anthropogenic effect is one possible new criterion.
b. There is a subtle deterioration of water quality in the Bay that has resulted in false
positives in our calibration dataset.
5. A reasonable next step is a best professional judgement approach to determining
biological criteria, similar to that of Weisberg et al. (2008).
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149
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