.C.CR& Erw^ronme'ntal Protection EPA/600/R-18/378 | February 2020
tl Agency
www.epa.gov/ord
Seasonal and Diel Oxygen and
Phytoplankton Dynamics in an Estuarine
Water Quality Model
Observed
Model
Office of Research and Development
Center for Environmental Measurement and Modeling
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EPA/600/R-18/378 | February 2020
www.epa.gov/ord
Seasonal and Diel Oxygen and
Phytoplankton Dynamics in an Estuarine
Water Quality Model
by
Edward H. Dettmann
Lucner Charlestra
Mohamed A. Abdelrhman
Atlantic Coastal Environmental Sciences Division
Center for Environmental Measurement and Modeling
Narragansett, RI
Center for Environmental Measurement and Modeling
Office of Research and Development
U.S. Environmental Protection Agency
Narragansett, RI 02882
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Disclaimer
This document has been reviewed by the U.S. Environmental Protection Agency, Office of
Research and Development, and approved for publication. Any mention of trade names,
products, or services does not imply an endorsement by the U.S. Government or the U.S
Environmental Protection Agency. The EPA does not endorse any commercial products,
services, or enterprises.
ii | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Table of Contents
List of Figures v
List of Tables viii
Abbreviations and Acronyms ix
Executive Summary xi
Findings xi
Introduction 1
Background 1
Purpose of This Study 1
The Study Site 2
Narragansett Bay and Its Watershed 2
Nutrients and Dissolved Oxygen in Narragansett Bay 5
Water Quality and Ecological Concerns in Narragansett Bay 6
Methods 7
The Hydrodynamic Model 7
The Water Quality Model 7
Modeling Strategy 9
The Model Grid 9
Model Time Step 9
Key Assumptions 9
Quality Assurance 9
Model Parameterization and Calibration 11
Model Inflows, Loads, and Other Forcing Functions 12
Tributary, Groundwater, and Effluent Inflows Entered into EFDC 12
Boundary Concentrations for Water Quality Constituents in Tributaries 14
Wastewater Treatment Facility Discharges into Narragansett Bay 15
Concentrations at the Seaward Boundary 17
Benthic Boundary Fluxes 18
Atmospheric Deposition Rates of N, P, and CBOD 19
Meteorological (Including Solar Radiation) Data 19
In-Bay Monitoring Data and Sources 19
Analysis of Simulation Results 20
Results 22
Near-Surface Oxygen Concentrations 22
Annual Distribution of Simulated Near-Surface Oxygen Concentrations 22
Comparison of Simulated and Observed Near-Surface Oxygen Concentrations 25
Comparison of Daily Averaged Simulated and Observed Near-Surface Oxygen
Concentrations 31
Table of Contents | iii
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Production of Oxygen by Phytoplankton 34
Near-Surface Chlorophyll a Concentrations 35
Annual Distribution of Simulated Near-surface Chlorophyll a Concentrations 35
Effects of Nonphotochemical Quenching on Observed Chlorophyll a Concentrations ... 39
Comparison of Simulated and Observed Near-Surface Chlorophyll a Concentrations.... 41
Comparison of Daily Averaged Simulated and Observed Near-Surface Chlorophyll a
Concentrations 45
Responses of Simulated Near-Surface Oxygen and Chlorophyll a Concentrations to
Changes in Incident Light and Nutrient Inputs 48
Summary and Discussion 52
References 59
Appendix A - Other Recent Modeling Studies on Narragansett Bay 65
References for Appendix A 67
Appendix B. Data Input Values for State Variables, Atmospheric Deposition Rates, and
Model Parameters Used in the Standard Run of the WASP Model 69
References for Appendix B 76
iv | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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List of Figures
Figure 1. Location of Narragansett Bay and its watershed 3
Figure 2. The Narragansett Bay estuary 5
Figure 3. Model grid, with color coding of water depth 11
Figure 4. Narragansett Bay watershed, showing subwatersheds for major tributaries and
the riparian area 13
Figure 5. Narragansett Bay Commission tributary nutrient sampling sites 15
Figure 6. Wastewater treatment facilities with direct discharge into the Estuary and
FSMN stations 18
Figure 7. Locations of sampling stations for the NOAA CHRP surveys are shown as
numbered filled circles 21
Figure 8. Simulated near-surface oxygen concentration and water temperature at
the Bullock's Reach station, March 1-December 31, 2009, with oxygen solubility
calculated from observed near-surface water temperature and salinity 22
Figure 9. Simulated near-surface oxygen concentration and water temperature at
the Conimicut Point station, March 1-December 31, 2009, with oxygen solubility
calculated from observed near-surface water temperature and salinity 23
Figure 10. Simulated near-surface oxygen concentration and water temperature at
the North Prudence Island station, March 1-December 31, 2009, with oxygen
solubility calculated from observed near-surface water temperature and salinity 23
Figure 11. Simulated near-surface oxygen concentration and water temperature at
the Mount View station, March 1-December 31, 2009, with oxygen solubility
calculated from observed near-surface water temperature and salinity 24
Figure 12. Simulated near-surface oxygen concentration and water temperature at
the Quonset Point station, March 1-December 31, 2009, with oxygen solubility
calculated from observed near-surface water temperature and salinity 24
Figure 13. Simulated and observed near-surface oxygen concentrations at the Bullock's
Reach station, June 1-October 25, 2009 25
Figure 14. Simulated and observed near-surface oxygen concentrations at the Conimicut
Point station, June 1-October 25, 2009 26
Figure 15. Simulated and observed near-surface oxygen concentrations at the
North Prudence Island station, June 1-October 25, 2009 26
Figure 16. Simulated and observed near-surface oxygen concentrations at the
Mount View station, June 1-October 25, 2009 27
Figure 17. Simulated and observed near-surface oxygen concentrations at the
Quonset Point station, June 1-October 25, 2009 27
Figure 18. Simulated and observed near-surface oxygen concentrations at the Mount
View station, July 1-31, 2009 28
Figure 19. Diel range (maximum-minimum) of near-surface simulated and observed
oxygen concentrations at Bullock's Reach station, June 1-October 25, 2009 29
List of Figures | v
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Figure 20. Diel range (maximum-minimum) of near-surface simulated and observed
oxygen concentrations at Mount View station, June 1-October 25, 2009 29
Figure 21. Simulated and observed average summer and early fall near-surface
oxygen concentrations at stations along a longitudinal transect in the Providence
River and West Passage 30
Figure 22. Simulated and observed daily average near-surface oxygen concentrations at the
Bullock's Reach station, June 1-October 25, 2009 31
Figure 23. Simulated and observed daily average near-surface oxygen concentrations at the
Conimicut Point station, June 1-October 25, 2009 32
Figure 24. Simulated and observed daily average near-surface oxygen concentrations at the
North Prudence Island station, June 1-October 25, 2009 32
Figure 25. Simulated and observed daily average near-surface oxygen concentrations
at the Mount View station, June 1-October 25, 2009 33
Figure 26. Simulated and observed daily average near-surface oxygen concentrations
at the Quonset Point station, June 1-October 25, 2009 33
Figure 27. Simulated near-surface light limitation factor for phytoplankton biomass growth
rate and oxygen production rate at the Mount View station, July 1-31, 2009 34
Figure 28. Simulated near-surface gross oxygen production rate by phytoplankton,
and nutrient limitation factor at the Mount View station, July 1-31, 2009 35
Figure 29. Simulated daily gross oxygen production by phytoplankton, integrated
over daylight hours at the Mount View station, June 1-August 31, 2009 36
Figure 30. Simulated near-surface chlorophyll a concentrations at the Bullock's
Reach station, March 1-December 31, 2009 36
Figure 31. Simulated near-surface chlorophyll a concentrations at the Conimicut Point
station, March 1-December 31, 2009 37
Figure 32. Simulated near-surface chlorophyll a concentrations at the North Prudence Island
station, March 1-December 31, 2009 37
Figure 33. Simulated near-surface chlorophyll a concentrations at the Mount View
station, March 1-December 31, 2009 38
Figure 34. Simulated near-surface chlorophyll a concentrations at the Quonset Point station,
March 1-December 31, 2009 38
Figure 35. Observed near-surface concentrations of chlorophyll a at 15-minute intervals
and as diel averages, and total daily incident solar radiation for Mount View station,
June 1-15,2009 40
Figure 36. Observed near-surface concentrations of chlorophyll a at 15-minute intervals
and as diel averages, and total daily incident solar radiation for Mount View station,
June 16-30, 2009 40
Figure 37. Simulated and observed near-surface chlorophyll a concentrations at the
Bullock's Reach station, June 1-October 25, 2009 41
Figure 38. Simulated and observed near-surface chlorophyll a concentrations at the
Conimicut Point station, June 1-October 25, 2009 42
vi | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Figure 39. Simulated and observed near-surface chlorophyll a concentrations at the
North Prudence Island station, June 1-October 25, Figure 2009 42
Figure 40. Simulated and observed near-surface chlorophyll a concentrations at the
Mount View station, June 1-October 25, 2009 43
Figure 41. Simulated and observed near-surface chlorophyll a concentrations at the
Quonset Point station, June 1-October 25, 2009 43
Figure 42. Average simulated and observed summer and early fall near-surface
chlorophyll a concentrations at stations along a longitudinal transect in the Providence
River and West Passage 44
Figure 43. Average simulated and observed summer near-surface chlorophyll a concentrations
at stations along a longitudinal transect in the Providence River and West Passage.
The averaging period is June 1-August 31, 2009 44
Figure 44. Simulated and observed daily average near-surface chlorophyll a
concentrations at the Bullock's Reach station, June 1-October 25, 2009 45
Figure 45. Simulated and observed daily average near-surface chlorophyll a concentrations
at the Conimicut Point station, June 1-October 25, 2009 46
Figure 46. Simulated and observed daily average near-surface chlorophyll a
concentrations at the North Prudence Island station, June 1-October 25, 2009 46
Figure 47. Simulated and observed daily average near-surface chlorophyll a concentrations
at the Mount View station, June 1-October 25, 2009 47
Figure 48. Simulated and observed daily average near-surface chlorophyll a concentrations
at the Quonset Point station, June 1-October 25, 2009 47
Figure 49. Near-surface modeled chlorophyll a concentrations for 2009 at Mount View,
with full incident light (standard run) and with incident light reduced to zero 48
Figure 50. Near-surface modeled oxygen concentrations for 2009 at Mount View,
with full incident light (standard run) and with incident light reduced to zero 49
Figure 51. Near-surface modeled chlorophyll a concentrations for 2009 at Mount View, with
standard nutrient input rates (standard run) and with halved and doubled nutrient input
rates from WWTFs, tributaries, atmospheric deposition, and the seaward boundary 50
Figure 52. Near-surface modeled oxygen concentrations for 2009 at Mount View, with
standard and halved nutrient input rates from WWTFs, tributaries, atmospheric deposition,
and the seaward boundary 50
Figure 53. Near-surface modeled oxygen concentrations for 2009 at Mount View, with
standard and doubled nutrient input rates from WWTFs, tributaries, atmospheric
deposition, and the seaward boundary 51
Figure 54. Diel ranges (maximum-minimum) at Mount View of near-surface observed
oxygen concentrations and of simulated diel ranges for observed (standard) and doubled
nutrient input rates from WWTFs, tributaries, atmospheric deposition, and the seaward
boundary 51
List of Figures | vii
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List of Tables
Table 1. Rhode Island saltwater dissolved oxygen criteria 2
Table 2. State variables included in the WASP Advanced Eutrophication Module 8
Table 3. Wastewater Treatment Facilities discharging directly into Narragansett Bay,
and water quality parameters relevant to this study 16
Table 4. Locations, sensor depths, and total water depths for Fixed-Site Monitoring
Network stations 20
Table 5. Average observed and simulated diel oxygen concentration ranges at station MV
and their ratios for the months of June, July, August, September, October 1-25, 2009,
and the period (June 1-October 25), 2009 30
Table 6. Average observed and simulated diel ranges of oxygen concentrations at Mount
View for the periods June 1-October 25, 2009 and the subperiod June 1-September 15 52
Acknowledgments
We wish to thank Dr. Collin Roesler (Bowdoin College) for providing insights into
nonphotochemical quenching of chlorophyll a fluorescence, and Drs. Candace Oviatt (Graduate
School of Oceanography, University of Rhode Island), and Daniel Codiga (Massachusetts Water
Resources Authority) for helpful advice. This report was reviewed by Drs. Christopher Knightes,
Betty Kreakie, Wayne Munns, Brenda Rashleigh, and Henry Walker. (USEPA/ORD/CEMM/
ACESD). Dr. Glen Thursby (USEPA/ORD/NHEERL/AED, retired) gave much useful assistance
concerning phytoplankton physiology and general support. Tim Wool (USEPA, Region 4)
modified the model to accommodate our large model grid and provided general support and
training in the use of WASP. Robert B. Ambrose, Jr. (USEPA, retired) provided WASP training,
and assistance with interpretation of results. Jane Copeland (USEPA/ORD/CEMM/ACESD)
provided graphics support. Patricia DeCastro (General Dynamics Information Technology, Inc.)
formatted the report.
viii | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Abbreviations and Acronyms
AEM Advanced Eutrophication Module
AED Atlantic Ecology Division
C Carbon
CBOD5 Five-Day Carbonaceous Biochemical Oxygen Demand
CBODu Ultimate Carbonaceous Biochemical Oxygen Demand
Chi a Chlorophyll a
[Chi a] Chlorophyll a Concentration
CHRP Coastal Hypoxia Research Program (NOAA)
DIN Dissolved Inorganic Nitrogen
DIP Dissolved Inorganic Phosphorus
DISi Dissolved Inorganic Silica
DMR US EPA's Discharge Monitoring Report
DO Dissolved Oxygen
DON Dissolved Organic Nitrogen
DOP Dissolved Organic Phosphorus
DOSi Dissolved Organic Silica
DW Dry Weight
EFDC Environmental Fluid Dynamics Code
FSMN Fixed-Site Monitoring Network
GSO Graduate School of Oceanography (University of Rhode Island)
ICIS Integrated Compliance Information System (USEPA)
LLF Light Limitation Factor
MA Massachusetts
N Nitrogen
NB Narragansett Bay
NBC Narragansett Bay Commission
NH3-N Ammonia-Nitrogen
NHEERL National Health and Environmental Effects Research Laboratory
NLF Nutrient Limitation Factor
NO2-N Nitrite-Nitrogen
Abbreviations and Acronyms | ix
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N03-N
Nitrate-Nitrogen
NO A A
National Oceanic and Atmospheric Administration
NPDES
National Pollutant Discharge Elimination System
NPQ
Nonphotochemical Quenching (of chlorophyll fluorescence)
NSRDB
National Solar Radiation Data Base
[O2]
Oxygen Concentration
ORD
Office of Research and Development
P
Phosphorus
PAR
Photosynthetically Available (or Active) Radiation
PON
Particulate Organic Nitrogen
POP
Particulate Organic Phosphorus
QA/QC
Quality Assurance/Quality Control
RI
Rhode Island
RIDEM
Rhode Island Department of Environmental Management
SOD
Sediment Oxygen Demand
TDN
Total Dissolved Nitrogen
TKN
Total Kjeldahl Nitrogen
TN
Total Nitrogen
TP
Total Phosphorus
TSS
Total Suspended Solids
URI
University of Rhode Island
USEPA
United States Environmental Protection Agency
USGS
United States Geological Survey
WASP
Water Quality Analysis Simulation Program
WWTF
Wastewater Treatment Facility
x | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Executive Summary
This report documents results of a study using Version 7.52 of the U.S. Environmental
Protection Agency's Water Quality Analysis Simulation Program (WASP) to analyze effects of
nutrient loading and factors such as light, freshwater inflow, and temperature on seasonal trends,
diel (over 24-hour day-night cycles) variability, and spatial relationships of phytoplankton and
oxygen concentrations in surface waters of Narragansett Bay (the Bay).
The WASP model has frequently been used to assess relationships between nutrient loads
and water quality in freshwater, marine, and estuarine waters. In the past, the model has been
used to investigate phytoplankton, oxygen, and nutrient dynamics at time scales of weeks or
months to seasons. However, Rhode Island Dissolved Oxygen Criteria cite oxygen
concentrations at time scales as short as one hour at low concentrations. Since we have access to
dissolved oxygen and chlorophyll a (Chi a) concentrations measured in the Bay at 15-minute
intervals, we are able to test model behavior at a range of time scales from the diel cycle to
seasons or longer.
Initial simulations showed that while the model performs well at simulating seasonal patterns
of oxygen and phytoplankton concentrations in the Bay, it substantially underestimates diel
variability. We therefore investigated the spatial distribution and diel dynamics of observed and
simulated oxygen and phytoplankton concentrations at five monitoring stations along a 17-km
north-south longitudinal transect from the upper to mid Bay over the June 1-October 25, 2009
monitoring period. Because of the importance of photosynthetic oxygen production and air-sea
exchange of oxygen, we limit the scope of this investigation to near-surface waters to focus on
the effects of these processes on diel dynamics and spatial relationships of observed and
simulated oxygen and phytoplankton Chi a concentrations.
Findings:
• The March-December pattern of simulated near-surface oxygen concentrations in the
Bay appears largely constrained by oxygen solubility, which is a function of salinity and
temperature, and is overlain by diel and intermediate-period (i.e., longer than diel but
shorter than seasonal) fluctuations.
• Modeled daily average concentrations of oxygen follow observed June-October seasonal
trends, but their diel variations are substantially smaller than those observed. The best
correspondence between simulated and observed short-term variations is in the mid-Bay.
• Simulated rates of photosynthetic oxygen production are nutrient-limited, and much
smaller than required to produce measured ranges of diel oxygen concentrations in the
Bay. Model kinetic parameters governing phytoplankton growth and oxygen production,
mineralization of organic nutrients, and nutrient uptake were varied over ranges
supported by literature values during model calibration. Some of these changes in values
of kinetic parameters yielded incremental increases in phytoplankton oxygen production,
but none large enough to approximate observed June-September diel ranges in oxygen
concentration.
• Simulated phytoplankton Chi a concentrations between March and December reflect
seasonal patterns of solar radiation and water temperature. This pattern is overlain by diel
and intermediate-period fluctuations.
Executive Summary | xi
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• Simulated Chi a follows observed seasonal trends from June 1 through mid- to late
August, but then declines more slowly than observed values through October 25.
• Observed daily average concentrations of Chi a show peaks with durations from days to
approximately three weeks. There is general correspondence in timing and magnitudes of
intermediate-period peaks between observed and simulated values from June 1 through
mid- to late August in the mid Bay. This correspondence becomes progressively weaker
for more northerly stations.
• Diel ranges of observed oxygen and Chi a concentrations substantially exceed those of
model values from June 1 through late August, then decline to values at or smaller than
diel model ranges by late October. However, the diel ranges of actual in-Bay Chi a
concentrations are difficult to quantify because of frequent mid-day declines in measured
Chi a caused by nonphotochemical quenching of Chi a fluorescence. This measurement
artifact leads to underestimation of mid-day Chi a, artificially increasing observed diel
ranges.
• Modeled and observed Chi a, averaged over the period June 1-August 31, agree well at
individual stations and decline more than threefold along the longitudinal transect,
reflecting a gradient in available nutrients. Modeled and measured oxygen
concentrations, averaged over the monitoring period, agree well and show only small
differences among stations, consistent with small spatial variations in oxygen solubility.
• Sensitivity analysis shows that while near-surface simulated Chi a is highly responsive to
large reductions in solar radiation and large changes in external nutrient inputs, simulated
oxygen responds only weakly.
General agreement between seasonal trends in simulated oxygen concentrations and oxygen
solubility and the small effects of assuming greatly reduced solar radiation or large changes in
nutrient inputs on modeled near-surface concentrations of oxygen indicate that the dominant
factors governing simulated oxygen concentrations are physical, namely air-sea exchange as
constrained by oxygen solubility (a function of salinity and temperature).
While some differences between modeled and observed oxygen and Chi a values could be
attributable to uncertainties and temporal sparseness of input data or details of model calibration,
the inability of the model to simulate large observed diel ranges of water-column oxygen and
reported Chi a concentrations appears to be attributable to one or more other factors, possibly
omission from the model of one or more physiological processes in phytoplankton important to
producing the diel cycle. Such omitted processes could include release of organic compounds
such as carbohydrates, uptake of organic compounds of nutrients, and temporal changes in
preferences for specific components of DIN. In addition, some intermediate- and longer-term
differences between observed and simulated chlorophyll a values could in part be attributable to
the model's use of a single user-specified value of the carbon to chlorophyll a ratio for each
phytoplankton group in the model, since the value of this parameter is known to be variable,
depending on light and nutrient conditions.
While WASP is often used to successfully simulate monthly and seasonal variations and
sensitivity of Chi a and oxygen concentrations to nutrient loading, the model underestimates
observed diel ranges of oxygen and reported Chi a.
xii | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Introduction
Background
Elevated eutrophication of estuaries is a widespread problem in the U.S. Symptoms include
excess abundance of phytoplankton, which may include toxic species, blooms of periphyton and
macroalgae, hypoxia or anoxia, loss of beneficial submerged aquatic vegetation, and loss (even
massive kills) of shellfish and finfish. The usual cause is elevated loading of nutrients, leading to
an increase in the rates of phytoplankton, periphyton, and macroalgal production. The National
Estuarine Eutrophi cation Assessment of estuaries of the Atlantic, Gulf of Mexico, and Pacific
coasts of the contiguous 48 states by the National Ocean and Atmospheric Administration
(NOAA) found widespread instances of elevated eutrophi cation in these systems. Data sufficient
to perform an assessment were present for 99 of the 141 estuaries reviewed (Bricker et al. 2007).
A majority (65%) of the assessed estuaries exhibited symptoms of eutrophi cation. Twenty-nine
of these assessed estuaries (29%) had moderately high to high eutrophic condition, meaning that
they were "characterized by symptoms that are extensive (covering 50% or more of the system)
and/or are periodic or persistent." An additional thirty-five systems (35%) had moderate
eutrophic condition ratings, that is, they were "characterized by symptoms that are periodic and
occur over a moderate portion of the estuary."
Phytoplankton and dissolved oxygen concentrations in water bodies are affected by multiple
external drivers, including nutrient and freshwater inputs, temperature, weather-induced
variations in solar radiation, wind patterns, and over periods of years to decades, climate change.
In estuaries, tidal forcing, the presence of freshwater and saline water masses, and input of water
across the ocean boundary further complicate matters. Interactions among these factors are
complex, and managers require tools that can take all these influencing factors into account to
aid in understanding their relative importance in creating estuarine water quality, and in
estimating the likely response of the estuary to remedial actions. Simulation models are
frequently used to assess the effects of these factors on water quality in aquatic systems.
Purpose of This Study
The purpose of this report is to document results of a study using Version 7.52 of the U.S.
Environmental Protection Agency's Water Quality Analysis Simulation Program (WASP) to
analyze effects of nutrient loading on diel (over 24-hour day-night cycles) dynamics and spatial
relationships of phytoplankton and oxygen concentrations in surface waters of Narragansett Bay.
The WASP model has frequently been used to assess relationships between nutrient loads
and water quality in freshwater, marine, and estuarine waters. In the past, the model has been
used to investigate phytoplankton, oxygen, and nutrient dynamics at time scales of weeks or
months to seasons (e.g. Wang et al. 1999; Wool et al. 2003). However, Rhode Island saltwater
dissolved oxygen criteria cite oxygen concentrations at time scales as short as one hour at
concentrations below 1.4 mg/L (Table 1). Since we have access to dissolved oxygen and
chlorophyll a (Chi a) concentrations measured at 15-minute intervals, we are able to test model
behavior at a range of time scales from the diel cycle to seasons or longer.
Initial simulations showed that while the model performs well at simulating seasonal patterns
of oxygen and phytoplankton concentrations in the Bay, it substantially underestimates diel
variability. We therefore investigated the spatial distribution and diel dynamics of observed and
Introduction | 1
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simulated oxygen and phytoplankton concentrations at five monitoring stations along a 17-km
north-south longitudinal transect from the upper to mid Bay over the June 1-October 25, 2009
monitoring period. Because of the importance of photosynthetic oxygen production and air-sea
exchange of oxygen, we limit the scope of this investigation to near-surface waters to focus on
their effects on diel dynamics of observed and simulated oxygen concentrations.
Table 1. Rhode Island saltwater dissolved oxygen criteria (RIDEM 2010).
For surface waters above
a seasonal pycnocline
Dissolved oxygen shall not be less than an instantaneous
value of 4.8 mg/L more than once every three years,
except as naturally occurs.
For waters below a seasonal
pycnocline, or waters without
a seasonal pycnocline
Waters with a DO concentration above an instantaneous
value of 4.8 mg/L shall be considered protective of
Aquatic Life Uses. When instantaneous DO values fall
below 4.8 mg/L, the waters shall not be:
• Less than 2.9 mg/L for more than 24 consecutive hours
during the recruitment season; nor
• Less than 1.4 mg /L for more than one hour more than
twice during the recruitment season; nor
• Shall they exceed the cumulative DO exposure
presented in Table 3.Aa contained in the Rhode Island
water quality regulations
aTable 3.A in the Rhode Island Saltwater Dissolved Oxygen (DO) Criteria specifies the allowable number
of days at given 24-hour oxygen concentrations between 2.9 and 4.6 mg/L that protects against greater
than 5% cumulative impairment of larval recruitment over a recruitment season.
The Study Site
Narragansett Bay and Its Watershed
The Narragansett Bay watershed has an area of 4,836 square kilometers and is located in the
states of Rhode Island (RI, 40%) and Massachusetts (MA, 60%). The watershed includes
approximately 100 cities and towns, with more than two million residents (Fig. 1). Providence,
RI (population ~ 177,000) and Worcester, MA (population ~ 173,000) are the two largest cities
in the watershed. Approximately 14% of the watershed is in urban land use. The two largest
tributaries of the Bay are the Blackstone and Taunton Rivers. The Seekonk River is the
downstream tidal reach of the Blackstone River, and is part of the estuary. The tidal portion of
the Taunton River is also included in the model domain. The portion of Narragansett Bay
between the mouth of the Seekonk River and Conimicut Point (Fig. 2) is generally referred to as
the Providence River; it is tidal and generally more strongly stratified than portions of the Bay
further to the south.
The area, volume, and mean depth of Narragansett Bay at mid-tide are 379 km2,
3,059 X 106 m3 and 8.07 m, respectively. Ninety-four percent of the estuary is in Rhode Island,
the remainder in Massachusetts. Tides in the Bay are largely standing wave in nature with a
small progressive wave component. Tidal range in the Bay varies from a mean of 1.07 m at the
2 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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seaward boundary, to 1.40 m at the Bay's head, with spring tide ranges of 1.34 m and 1.74 m
respectively at these locations (Hicks 1959).
Three large islands (Aquidneck, Conanicut, and Prudence Islands) divide the Bay into three
main north-south segments, the West Passage, the East Passage and the Sakonnet River (Fig. 2)
The Bay includes two large side-embayments, Greenwich Bay and Mount Hope Bay. The
seaward boundary with Rhode Island Sound is at the southern end of the estuaiy.
iMtOrt^nwicA >
Rhode Island
Legend
• Cities
1:100k NHD
Lakes
State Boundaries
C3 Narragansett Bay Watershed
Boston
Locus Map
Massachusetts
Figure 1. Location of Narragansett Bay and its watershed. The drainage network is
from the National Hydrography Dataset (NHD) at a scale of 1:100,000. (Illustration by
Jane Copeland, USEPA/ORD/NHEERL/AED, Narragansett, RI)
Study Site | 3
-------
Hydrodynamics in the Bay are influenced by dredged navigation channels that are
substantially deeper than adjacent areas of the Bay. The main dredged channel extends
northward up the East Passage from the southern part of Prudence Island, through the Providence
River to Fox Point, and the entire length of the Seekonk River. Mount Hope Bay also has a pair
of deep dredged channels, one of which extends the length of Mount Hope Bay into the mouth of
the Taunton River. These channels have posed challenges to at least one previous attempt to
model hydrodynamics of this system (Swanson et al. 2005).
Vertical transport of oxygen, phytoplankton, and nutrients in a water body depends strongly
on the existence and strength of density stratification. Both the Seekonk and Providence Rivers
(Fig. 2) show vertical salinity stratification year-round, with a seasonal thermal gradient. The
northern portion of the Bay south of Conimicut Point exhibits some density stratification, the
strength of which depends on freshwater input and wind speed and direction; it also depends
upon the tidal range, which influences vertical mixing (Bergondo et al. 2005; Codiga et al.
2009). The existence, strength, and timing of density stratification influences the timing and
severity of hypoxic events in the Bay (Bergondo et al. 2005; Codiga et al. 2009; Codiga 2012).
The freshwater residence time of the Bay varies from approximately 10 days at very high
freshwater inflow rates (-325 m3/s), to about 40 days at very low freshwater inflows (20 m3/s"'),
and 26 days at the long-term mean freshwater inflow of 105 m3/s"', with inflows calculated from
tributary, wastewater treatment facility (WWTF), industrial, and net rainfall inputs (Pilson 1985).
4 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Blackstone River
Providence
Field's
Point er
•i.
V\ferrer»/
Palmer River
'Braytot
Point/
Fall River
Conimicut
Point '
Mt. Hope
Greenwicl
41°
40''
Hunt River
Quonset
Point
Aquidneck
island
Km
Figure 2. The Narragansett Bay estuary. (Illustration by Jane Copeland,
USEPA/ORD/NHEERL/AED, Narragansett. RI)
Nutrients and Dissolved Oxygen in Narragansett Bay
A substantial fraction of dissol ved nitrogen in the Bay is in organic form. The molar ratio of
baywide mean dissolved organic nitrogen (DON) concentration to that of dissolved inorganic
nitrogen (DENT) during four surveys of the Bay (October and November 1985 and April and May
1986) varied over the range 1.0 < (DON/DIN) < 10.5 (Pilson and Hunt 1989); for individual
segments of the Bay, the range was 0.27 < (DON/DIN) < 29.7). Krumholz (2012) found an
average summertime molar ratio of total nitrogen (TN) to DIN of approximately nine for 2006-
2010.
Concentrations of total nitrogen and phosphorus show decreasing gradients along a north-to-
south longitudinal transect in the Bay. The concentration of TN, for example, decreases
Study Site | 5
-------
exponentially with distance from 75 |iM near the Field's Point WWTF, located approximately
4.5 km south of Fox Point, in Providence (Fig. 2), to approximately 10 |iM at the southern end of
the West Passage (Oviatt 2008). Smayda and Borkman (2008) report similar decreasing north-
south gradients of ammonium, nitrate, phosphate, and silica concentrations in the Providence
River and West Passage. Phytoplankton abundance, primary production, and abundances of
many other organisms also are highest in the upper Bay and decrease toward the seaward
boundary (Oviatt 2008).
Summertime concentrations of dissolved oxygen in the lower water column are intermittently
suboxic (< 4.8 mg L"1) or hypoxic (< 2.9 mg/L) in the upper Bay (north of Quonset
Point), including the Providence River, Greenwich Bay, and Mount Hope Bay (Fig. 2), and
intermittently severely hypoxic (< 1.4 mg/L) in portions of all these Bay segments except Mount
Hope Bay (Codiga et al. 2009). The frequency and severity of hypoxia are highly variable from
year to year in each of these areas of the Bay except Greenwich Bay, where summertime hypoxia
is frequent and interannual variability is muted (Codiga et al. 2009). Individual suboxic and
hypoxic events in various sections of the Bay exhibit limited synchronicity, suggesting that
dominant causal processes differ among the various segments (Codiga et al. 2009).
Water Quality and Ecological Concerns in Narragansett Bay
Water quality and ecological concerns related to excess nutrient loading that have been
identified in upper Narragansett Bay include periodic hypoxia or anoxia, loss of eelgrass
(Zostera marina), and excessive growth of macroalgae, largely Ulva lactuca and Gracilaria
tikvahiae in some side-embayments and near-shore areas (Deacutis 2008). Anoxia has resulted in
losses of shellfish, such as a mussel die-off in 2001 (Altieri and Witman 2006) and periodic kills
of finfish, including one in August 2003 that resulted in the death of more than one million fish
(primarily juvenile menhaden) in Greenwich Bay (RIDEM 2003).
Bioassay and mesocosm experiments indicate that nitrogen is the macronutrient most often
limiting to primary production in Narragansett Bay (Smayda 1974; Oviatt et al. 1995). However,
nutrient ratios in some survey data suggest localized seasonal phosphorus limitation (Heffner
2009), and Smayda and Borkman (2013) have suggested that phytoplankton productivity in
Narragansett Bay is limited by phosphorus under some conditions. Molar ratios of inorganic
nitrogen to phosphorus in data collected by the Narragansett Bay Commission suggest
intermittent phosphorus limitation in the Providence River in the summer of 2009 (see discussion
in the "Summary and Discussion" section of this report).
Following the August 2003 anoxia event and large fish kill in Greenwich Bay in 2003, the
Rhode Island Department of Environmental Management (RIDEM) required wastewater
treatment facilities (WWTFs) to reduce May-October concentrations of nitrogen (N) in their
effluents from 16-20 mg N/L to no more than 5 mg N/L (Rashleigh et al. 2015). This resulted in
a May-October reduction of nitrogen inputs from Rhode Island WWTFs discharging to the Bay
of approximately 50% compared to the early 2000s pre-reduction period (RIDEM 2017).
USEPA also required six WWTFs in Massachusetts that discharge to the Bay and its tributaries
to implement similar reductions in nitrogen discharges. In addition, a tunnel that stores combined
sewage and runoff flows that formerly discharged to the Bay and routes them to a WWTF
became operational in 2008, further reducing nutrient loading to the Bay. Between 2013 and
2016, May-October reductions compared to the early 2000s pre-reduction time period ranged
from 62 to 73% (RIDEM 2017).
6 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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This is one of a number of recent modeling studies that have been conducted in Narragansett
Bay in order to investigate factors contributing to anoxia in the Bay, and in part to test the ability
of these models to simulate the Bay's response to the recent reductions in nutrient inputs to the
Bay. A listing and brief overview of other recent studies in Narragansett Bay appears in
Appendix A.
Current Rhode Island saltwater quality criteria are numeric for dissolved oxygen (Table 1)
and narrative for nutrients. A total of 123.3 km2 (33%) of Narragansett Bay are listed as impaired
for dissolved oxygen; of these, 102.3 km2 (27% of the Bay) are also listed by the Rhode Island
Department of Environmental Management (RIDEM) as impaired for nitrogen, based on the
inferred effects of nitrogen on dissolved oxygen (personal communication, RIDEM).
Methods
In this study, we use a hydrodynamic model and a dynamic water quality model to simulate
responses of phytoplankton, dissolved oxygen, nutrient concentrations, and associated state
variables to various drivers, including loading of nutrients and water, and forcing by tides, wind,
and sunlight.
The Hydrodynamic Model
We employ the Environmental Fluid Dynamics Code (EFDC) to provide the water quality
model WASP with hydrodynamic and associated variables for one year (2009). The EFDC
(Hamrick 1992, 1996) is a general-purpose model for simulating three-dimensional flow. It
solves the hydrostatic, free-surface, variable-density, and turbulence-averaged equations of
motion. It also solves dynamically-coupled equations for turbulent kinetic energy, turbulence
length scale, salinity, and temperature.
Water inflow rates from tributaries and other loading sources such as WWTFs and simulated
tidal exchanges across the seaward boundary, as well as advective and diffusive water exchanges
are communicated by EFDC to WASP through a hydrodynamic linkage (hydrolink) file.
Simulated water temperature and salinity, used in performing hydrodynamic simulations, are
also communicated to WASP through the hydrolink file. This permits performance of multiple
water-quality simulations for any given hydrodynamic simulation with EFDC. Calibration of
hydrodynamics and results in EFDC for use by WASP in our study are described by Abdelrhman
(2015).
The Water Quality Model
The Water Quality Analysis Simulation Program (WASP) is a general dynamic mass balance
framework for modeling contaminant fate and transport in surface waters (Di Toro et al. 1983;
Ambrose et al. 1988; Ambrose et al. 2006, Wool et al. 2006). It is capable of simulating time-
variable water quality constituents in one, two, or three dimensions. The model has multiple
modules that permit simulation of the fate and transport of nutrients, dissolved oxygen,
sediments, simple toxicants, organic chemicals, and the carbonate system in aquatic systems.
The WASP model has been used in many modeling applications to eutrophication-related
problems [e.g., Wang et al. (1999); Wool et al. (2003); and Yang et al. (2010)].
The WASP model, as do many eutrophi cation models, treats phytoplankton growth simply as
a temperature-dependent growth rate that is multiplied by two types of limitation factors (for
Methods | 7
-------
light and nutrients) that take on values between 0 (total limitation, i.e., no growth) and 1 (no
growth limitation). The rate of oxygen production is calculated as proportional to the
phytoplankton growth rate. The light limitation factor (LLF) is dependent on incident solar
radiation, with corrections for light extinction through absorption and scattering in the water
column, and includes light saturation and photoinhibition in calculations (Wool et al. 2006). The
nutrient limitation factor (NLF) is assumed to be the minimum of the limitation factors for
inorganic forms of nitrogen, phosphorus, and silica, each calculated using a Michaelis-Menten
formulation (Wool et al. 2006). Silica is assumed not to be limiting in this application. The
nitrogen limitation factor is a function of total dissolved inorganic nitrogen (DIN), i.e., ammonia-
N + nitrite-N + nitrate-N. All model calculations dependent on phytoplankton biomass are based
on phytoplankton carbon content. Chlorophyll a is calculated from phytoplankton carbon using
the constant user-specified carbon to chlorophyll a ratio, and is not used in other model
calculations.
We use the Advanced Eutrophication (AE) Module of WASP version 7.52 that contains the
Multi-Class Phytoplankton Model which is capable of simulating three phytoplankton classes
(e.g. diatoms, greens, and blue-greens) as separate state variables (Wool et al. 2018). Our model
version was modified by Tim Wool (USEPA, Region 4) to enable use of our large model grid,
described below. This version of the AE Module permits simulation of up to 26 state variables
(Table 2). Only the 14 state variables highlighted in Table 2 were used in our simulations.
Table 2. State variables included in the WASP Advanced Eutrophication Module (Wool et al. 2018).
Only the 14 highlighted state variables are used in our simulations.
Ammonia Nitrogen (mg-N L"1)
Detrital Phosphorus (mg-P L"1)
Nitrate Nitrogen (mg-N L"1)*
Detrital Silica (mg-Si L"1)
Dissolved Organic Nitrogen (mg-N L"1)
Total Detritus (mg-DW) L"1)**
Inorganic Phosphate (mg-P L"1)
Salinity (ppt)
Dissolved Organic Phosphorus (mg-P L"1)
Benthic Algae (g-DW m2)**
Inorganic Silica (mg-Si L"1)
Periphyton Cell Quota Nitrogen (mg N g-DW"1)**
Dissolved Organic Silica (mg-Si L"1)
Periphyton Cell Quota Phosphorus (mg P g-DW"1)**
CBOD1 (ultimate) (ing-O: L"1)
Inorganic Solids 1 (mg-DW L"1)**
CBOD2 (ultimate) (ing-O: L"1)
Inorganic Solids 2 (mg-DW L"1)**
CBOD3 (ultimate) (ing-O: L"1)
Inorganic Solids 3 (mg-DW L"1)**
Dissolved Oxygen (mg-Oi L"1)
Phytoplankton 1 (mg C L"1)***
Detrital Carbon (mg-C L"1)
Phytoplankton 2 (mg C L1)***
Detrital Nitrogen (mg-N L"1)
Phytoplankton 3 (mgCL1)***
* This state variable includes nitrate + nitrate nitrogen.
** DW = dry weight;
*** Phytoplankton biomass is often expressed as a chlorophyll a concentration (|ig CM a L"1). This is calculated as
[chl a\ = 1000 (Phytoplankton C) (C:chl where (C:chl a) is the carbon to chlorophyll a ratio
[mg C (mg chl ct)A \.
8 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Modeling Strategy
The Model Grid
All WASP model runs performed in the course of model calibration have used the results of a
single EFDC simulation. This EFDC run uses a terrain-following vertical sigma-stretched grid
formatted to yield transport fields for the Advanced Eutrophi cation Module of WASP. WASP
uses the interfacial flows between grid segments determined by the hydrodynamic simulation to
calculate mass transport among these segments.
The model grid used by both EFDC and WASP is shown in plan view in Fig. 3, which shows
the segmentation used in each of eight water column layers. EFDC uses the entire grid, which
contains 754 segments per layer, or a total of 6032 volume elements in all eight layers. (Di Toro
et al. 1983; Ambrose et al. 1988; Ambrose et al. 2006). Dimensions of volume elements are
variable, but 642 m wide (east-west) and 1218 m long (north-south) are typical (Abdelrhman
2015). The thickness of each layer at any location is one-eighth of the local water column depth,
and varies throughout the tidal cycle. Fig. 3 is color-coded to show estuary depth. The WASP
model uses all but the three southernmost rows of the EFDC grid, and has 661 segments per
layer, a total of 5288 segments (volume elements) in all eight layers.
Model Time Step
The hydrodynamic model was run with a 120 s (2-minute) time step. WASP determines the
optimum time step for water-quality calculations. However, the user has the option of selecting
the fraction of the model-calculated optimum time step that will be used in the simulation to keep
the model stable; we used the default value of 90% of the optimum time step. The minimum time
step was set to 0.0001 day (8.64 s).
Key Assumptions
In the WASP modeling framework, each volume element of the model grid is treated as well-
mixed. The EFDC simulation that produced the hydrolink file was calibrated using salinity as a
surrogate for the transport of water quality constituents. This process was further verified by a
mass conservation check in the WASP model using a modeled conservative constituent as a
tracer.
Because of the sparseness of the data available for most boundary conditions, the linear
interpolation feature of WASP is used to estimate values of boundary conditions between
measurement dates. This procedure may introduce some uncertainty in specification of boundary
conditions, as previous research has shown that the linearity assumption of nutrient
concentrations as a function of flow may not hold in streams (Runkel et al. 2004), but was
deemed sufficient for this exploratory study.
Quality Assurance
All research conducted for this report is covered by an approved EPA Quality Assurance
Plan and followed generally accepted good modeling practices (e.g. Jakeman et al. 2006, Laniak
et al. 2013). None of the analyses conducted for this report involved primary data collection. The
modeling results discussed in this report were all generated using commercial software programs
and freely available, open-source models - Microsoft Excel, EFDC and WASP.
Methods | 9
-------
We use monitoring data that have been collected by other organizations as model input, and
for model calibration. These datasets are described, and their sources identified, elsewhere in this
"Methods" section. As is generally the case for models of large and complex systems, some
model input data are sparse. Examples relevant to our study are nutrient concentrations in
tributaries, and flow and nutrient concentrations in discharges from WWTFs, which were often
measured only biweekly or monthly. The frequency of input data, data gaps, uncertainties in
vertical partitioning of inputs in the water column of the Bay, and treatment of the data to
address such matters are described throughout this "Methods" section and are addressed in the
"Summary and Discussion" section.
We also evaluated monitoring data used in model calibration. This evaluation discovered
challenges in interpretation of monitoring data for daytime concentrations of phytoplankton
chlorophyll a used in calibration. These challenges and their effects on interpretation of model
results are described in the "Results" and the "Summary and Discussion" sections of this report.
10 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Bottom Elevation (m)
Figure 3. Model grid, with color coding of water depth EFDC
employs the entire grid. There are 754 segments per depth layer,
6032 segments for all eight layers. WASP uses the same grid,
minus the three rows nearest the seaward boundary. Figure from
Abdelrhman (2015).
Model Parameterization and Calibration
The WASP Advanced Eutrophication module's parameterization is determined by the
model's state variables (Table 2). Individual state variables can be turned on/off (i.e.
simulated/bypassed) or held constant in the "system screen" of the WASP user interface. While
state variables for two phytoplankton groups were included in a few model runs to explore the
effects on model dynamics, only the 14 model state variables highlighted in Table 2 are included
in the standard (calibrated) model run described in this report. The single phytoplankton group
used in the standard run is parameterized as a flagellate community. It is assumed not to be
limited by silica, and does not fix nitrogen. We did not include macroalgae (as benthic algae),
which are present in some shallow nearshore areas and side embayments such as Greenwich Bay
and Wickford Harbor. They are not considered important contributors to oxygen concentrations
in deeper areas of the Bay such as those occupied by the five stations that we examined, which
Methods | 11
-------
have water depths of 7.5-13.3 m (see section "In-Bay Monitoring and Data Sources" below), but
may be important in shallow areas such as Greenwich Bay.
Values of model kinetic parameters, initial concentrations, atmospheric deposition rates,
sediment oxygen demand (SOD), and benthic nutrient fluxes are tabulated in Appendix B. Initial
conditions of state variables are entered for each model segment. Values of kinetic parameters,
sediment oxygen demand, benthic nutrient fluxes, and atmospheric deposition of nutrients and
carbon are listed as either global constants, or as values at 20°C and associated temperature
correction coefficients. Temperature-dependent values of kinetic parameters are calculated as
k(T) = k(20)9(T"20), where k(T) is the value of the parameter at water temperature T (°C), k(20) is
the value of the parameter at 20°C, and theta (9) is the value of a user-specified temperature
correction coefficient. Boundary conditions for inputs from tributaries, WWTFs, benthic nutrient
fluxes, wind speed, and solar radiation as well as concentrations at the seaward boundary are
specified as time-variable values. Sources, frequency, and treatment of data for boundary
conditions are described below.
Model Inflows, Loads, and Other Forcing Functions
Input data for WASP come from numerous sources. Sources of data entered into EFDC are
described here only if they pertain to data that are passed on to WASP through the hydrolink file.
For a description of other input data for EFDC, see Abdelrhman (2015).
Incoming water and water quality constituents from tributaries, riparian areas, groundwater,
and WWTFs are partitioned equally between receiving segments in the top two layers of the grid.
The rationale for this approach is that with this partitioning EFDC simulations of salinity
produce better agreement with observed salinity distribution in the Bay than assuming complete
initial mixing throughout the water column, suggesting that this strategy better mimics initial
mixing of incoming water from these sources. In addition, inspection of near-field spatial
distributions in the estuary of dye introduced into WWTF effluents indicates a tendency for the
dye to be concentrated in the upper water column (unpublished dye study results obtained from
Angelo Liberti, Rhode Island Department of Environmental Management). This tendency is
likely a result of buoyancy of the freshwater inputs from these sources, and while stronger in
some dye studies than others, on balance supports the use of this approach.
Tributary, Groundwater, and Effluent Inflows Entered into EFDC
Inflow rates from seven of the eight tributaries shown in Fig. 4 (except for the Warren River)
were obtained from U.S. Geological Survey (USGS) gauging stations
(http://waterdata.uses.eov/RI/nwis/current?type=flow). Flow rates to the Bay entered into EFDC
are increased by the ratio between the tributary's total watershed area and the gauged drainage
area to correct for inflows below the gauge. Since flow for the Warren River was not gauged, its
flow is estimated as being equal to the flow of the nearby Ten Mile River, multiplied by the ratio
of their watershed areas. These flow gauging stations, their locations, watershed areas, gauged
drainage areas, flow correction factors for ungauged flows, and coordinates in the model grid are
described in Table 1 of Abdelrhman (2015).
Total flow from the riparian sub-watershed is estimated from its area and the average flow
per unit area from the total gauged watershed area. Based on visual inspection of the spatial
distribution of the riparian area identified in Fig. 4, half of the flow from this area is distributed
equally among the Pawtuxet, Taunton, Hunt, and Warren Rivers, and the remainder assigned to
three centrally located segments in the West Passage, East Passage, and the Sakonnet River
12 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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(Abdelrhman 2015). As described in paragraph 2 of the section "Model inflows, Loads, and
Other Forcing Functions", all inflows from the watershed, including tributaries and riparian
areas, are partitioned equally between receiving segments in the top two grid layers to account
for buoyancy.
IV 1
Blackstone River Basin
1,229,155,892 m'
Hunt River Basin
64.093,655 m!
Moshassuck River Basin
59,733,690 m2
¦¦
Riparian
498.029.952 m2
Pawtuxet River Basin
600.573,757 m2
Taunton River Basin
1,449.758,567 m2
t-1
Ten Mile River Basin
144 288,727 m2
Warren River Basin
175,329,816 m2
Woonasquatucket River Basin
132,527,601 m2
V
10 5 0
Figure 4. Narragansett Bay watershed, showing subwatersheds for major
tributaries and the riparian area. (Illustration by Jane Copeland, USEPA-ORD-
NHEERL-AED, Narragansett. RI.)
Groundwater flow to the Bay has been estimated as being less than 10% of direct freshwater
input (Nowicki and Gold 2008), and is assumed to be implicitly included in the inflows from
tributaries and riparian areas (Abdelrhman 2015).
Methods | 13
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Effluent flow rates for the Bucklin Point and Field's Point WWTFs were obtained as daily
rates from the Narragansett Bay Commission (NBC), flow rates for the other nine WWTFs
(Table 3) were obtained from the USEPA's Integrated Compliance Information System (ICIS)
database.
Boundary Concentrations for Water Quality Constituents in Tributaries
Concentrations of most water quality constituents in river inflows to the Bay used as model
boundary conditions were obtained or derived from values in the NBC database:
http://snapshot.narrabav.com/appAVaterQualitvInitiatives/NutrientMonitoring. NBC has been
measuring concentrations of nitrate nitrogen plus nitrite nitrogen (NO3-N+NO2-N), and
ammonia nitrogen (NH3-N), dissolved inorganic phosphorus (DIP), silica (DISi), total dissolved
nitrogen (TDN), total suspended solids (TSS), as well as temperature biweekly or monthly at the
15 stations shown in Fig. 5. When there were multiple water quality monitoring stations on a
tributary, data from the station farthest downstream were used. Concentrations measured at these
monitoring stations were used as boundary conditions for the grid segments at which the
tributaries enter the Bay. Values for the sum of nitrate nitrogen and nitrite concentrations were
entered for nitrate nitrogen boundary conditions since nitrite nitrogen is not a model state
variable and is quickly oxidized to the nitrate form. The Narragansett Bay Commission's TSS
measurements were found in a cross-laboratory validation study to be biased on the high side by
salt accumulation on the edges of filters used in TSS measurement (personal communication,
Glen Thursby, USEPA, Office of Research and Development, National Health and
Environmental Effects Research laboratory, Atlantic Ecology Division). Corrections to these
biased TSS values had not yet been made at the time of our model runs. Water flow rates across
boundaries (including tributary and WWTF discharges) were provided as boundary conditions to
EFDC and passed to WASP through the hydrolink file. United States Geological Survey
monitoring stations for tributary flows used to determine flow boundary conditions are described
in Table 1 of a report by Abdelrhman (2015).
No data are available for concentrations of particulate organic nitrogen (PON), dissolved
organic phosphorus (DOP), particulate organic phosphorus (POP), dissolved oxygen (O2), and
Chi a at these tributary boundaries. Values are estimated as follows:
• Particulate Organic Nitrogen (PON): assumed to be 0.01 mg/L.
• Dissolved Organic Phosphorus (DOP): assumed to be 0.001 mg/L.
• Particulate Organic Phosphorus (POP): assumed to be 0.001 mg/L.
• Dissolved oxygen (DO): assumed to be at saturation value as calculated from temperature.
• Chlorophyll a (Chi a) : assumed to be 2.9 (J,g/L, from an average of values in other New
England streams.
The low values of 0.01 and 0.001 mg/L specified above for PON, DOP, and POP are intended as
lower bounds, and may underestimate actual concentrations.
14 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Black stone River @ Stateline
Black stone River @ Rte. 116 Bikepath
Black stone River @ Slater Mill
Taunton River
Moshassuck River @Mill St
Ten Mile River at Omega Pond Outlet
Paviuxet River @ Terminal Falls
Lees River
luals 19,730.:
500 21',000 -
42,000
^¦Fee
Figure 5. Narragansett Bay Commission tributary nutrient sampling sites.
Source: http://snapshot.narrabav.com/appAVaterQualitvInitiatives/NutrientMonitoring.
Wastewater Treatment Facility Discharges into Narragansett Bay
Eleven WWTFs discharge directly into Narragansett Bay; nine are in Rhode Island and two
in Massachusetts (Table 3 and Fig. 6). Measured concentrations of nutrients, total suspended
solids (TSS), and ultimate carbonaceous biochemical oxygen demand (CBODu) are used as
boundary conditions for the WASP model and multiplied by the plant effluent discharge rate
(from EFDC) to obtain fluxes into the Bay.
The Bucklin Point and Field's Point WWTFs are operated by the NBC. For these two plants,
24-hour composite samples for nutrient analysis are collected three times weekly (Monday,
Tuesday, and Wednesday). Plant effluent discharge rates (Q), total suspended solids (TSS), and
5-day biochemical oxygen demand (BODs) are measured and reported daily.
For the remaining nine plants, data were downloaded from USEPA's Integrated Compliance
Information System (ICIS) database using USEPA's Discharge Monitoring Report (DMR) tool
Methods | 15
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(USEPA 2012). The ICIS database contains data submitted to the Agency by permitted
dischargers, based on monitoring requirements specified in their National Pollution Discharge
Elimination System (NPDES) discharge permits.
In the context of eutrophication, the state variables in the model that are relevant to WWTF
discharges are NH3-N, NO3-N, DON, dissolved inorganic phosphorus (DIP) dissolved organic
phosphorus (DOP), ultimate carbonaceous oxygen demand (CBODu), and inorganic solids.
Ammonia concentrations were measured in effluents of only seven of the WWTFs. For
plants for which it was not measured (Bristol, East Greenwich, Jamestown, and Quonset),
NH3-N was estimated from measured total Kjeldahl nitrogen (TKN) values. A regression
relationship between NH3-N and TKN was developed for East Providence WWTF effluents and
used to estimate NH3-N concentrations for effluents from these plants. The regression equation
is [NH3-N] = 0.8115[TKN] - 0.851 (R2 = 0.82).
Nitrite-N and nitrate-N are always monitored and their concentrations summed and entered
into the model as nitrate-N, as explained in section "Boundary Concentrations for Water Quality
Constituents in Tributaries."
We estimate dissolved organic N (DON) as TKN - (NH3-N). Since TKN is determined on
unfiltered samples of final effluent, this estimate includes particulate organic nitrogen, but the
particulate fraction is assumed to be small in final effluents that have undergone settling.
Table 3. Wastewater Treatment Facilities discharging directly into Narragansett Bay, and water
quality parameters relevant to this study. Q is the effluent discharge rate.
WWTF Name
Parameters Measured
Parameters Not Measured"
Rhode Island WWTFs:
Bristol
NO2-N, NOs-N, TKN, TN, BOD5, TSS, Q
NH3-N, TP, DISi, DOSi
Bucklin Point
NH3-N, NO2-N, NOs-N, TKN, TN, TP, BOD5, TSS, Q
DISi, DOSi (not measured in 2009)
East Providence
NH3-N, NO2-N, NOs-N, TKN, TN, TP, BOD5, TSS, Q
DISi, DOSi
East Greenwich
NO2-N, NOs-N, TKN, TN, BOD5, TSS, Q
NHs-N, TP, DISi, DOSi
Field's Point
NH3-N, NO2-N, NOs-N, TKN, TN, TP, BOD5, TSS, Q
DISi, DOSi (not measured in 2009)
Jamestownb
NO2-N, NOs-N, TKN, TN, BOD5, TSS, Q
NHs-N, TP, DISi, DOSi
Newportb
NH3-N, NO2-N, NOs-N, TKN, TN, BOD5, TSS, Q
TP, DISi, DOSi
Quonset
NO2-N, NOs-N, TKN, TN, BOD5, TSS, Q
NHs-N, TP, DISi, DOSi
Warren
NH3-N, NO2-N, NOs-N, TKN, TN, BOD5, TSS, Q
TP, DISi, DOSi
Massachusetts WWTFs:
Fall River
NH3-N, NO2-N, NOs-N, TKN, BOD5, TSS, Q
TN, TP, DISi, DOSi
Somerset
NH3-N, NO2-N + NOs-N, TKN, BOD5, TSS, Q
TN, TP, DISi, DOSi
a See text for discussion of how these parameter values were estimated when not directly measured.
b No nutrient concentrations were reported for the Jamestown and Newport, RI WWTFs for the colder
months of January-April 2009 and November-December 2009.
16 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Of the WWTFs that discharge directly to Narragansett Bay, phosphorus concentrations in
effluents are measured and reported only for the Bucklin Point, East Providence, and Field's
Point WWTFs, and are measured only as total phosphorus (TP). For those WWTFs for which
TP is not measured, we assign monthly TP concentrations equal to those for the East Providence
plant.
Dissolved inorganic phosphorus (DIP) occurs virtually exclusively as orthophosphates in
aerobic environments (Valiela 1995). Based on consultation with David Pincumbe (USEPA,
Region 1 Office), both total phosphorus (TP) and orthophosphate (assumed identical to DIP for
our purposes) are required to be measured during winter months in the effluents of some
WWTFs in EPA Region 1 that discharge to freshwater systems. Preliminary analysis of these
data indicates that the ratio of DIP to TP is negatively correlated (weakly) with TSS
concentrations and is generally in the range 0.7 < DIP/TP < 0.9. We assume that DIP
concentrations in WWTF effluents are 80% of TP for all months, and that the remaining 20% of
TP is dissolved organic phosphorus (DOP).
None of the WWTFs that discharge to Narragansett Bay regularly measure silica
concentrations in their effluents. Upon request, the Narragansett Bay Commission (NBC) made
monthly silica measurements in effluents from the Bucklin Point and Field's Point WWTFs for a
year, with measurements for the two facilities conducted in alternate months. This yielded a total
of 13 silica measurements, seven for effluents of the Field's Point WWTF over the period June
2014-June 2015, and six measurements over the period July 2014-May 2015. These
measurements were not made in 2009, the year of our model run, and it is uncertain how
representative these values are for the other WWTFs. For these reasons, and since the general
consensus in the Narragansett Bay water quality community is that silica is not important as a
limiting nutrient during the June-October calibration period of our study, we do not use silica as
a limiting nutrient in our WASP simulations.
Carbonaceous biochemical oxygen demand is measured as 5-day oxygen demand (CBODs)
for all WWTFs. Ultimate carbonaceous biochemical oxygen demand (CBODu) is calculated as
four times BOD5 for all WWTFs. This conversion factor is based on measurements made on
effluents from the Bucklin Point, East Providence, and Field's Point WWTFs in 1989 (see
Doering et al. (1990) and Tables 21 and 28 in Dettmann et al. (1992)).
Effluent volumetric discharge rates are available daily for the WWTFs operated by the NBC
at Bucklin Point and Field's Point. Monthly average values are available for the other seven
WWTFs for Rhode Island communities discharging to the Bay. For the Somerset and Fall River
WWTFs in Massachusetts, plant flow-through rates were reported as rolling averages for the 12-
month period ending in the reporting month. For these two WWTFs, we apply the yearly average
monthly flow reported for December 2009 to each month of the year.
Concentrations at the Seaward Boundary
Nutrient concentrations at the ocean boundary are taken from station #03 (Fig. 7) of the
surveys conducted by the University of Rhode Island's Graduate School of Oceanography (GSO)
and the Narragansett Bay Coastal Hypoxia Research Program (CHRP) by Krumholz (2012).
This is located approximately 1.6 km south of Beavertail, the southern tip of Conanicut Island.
Values of dissolved oxygen and chlorophyll a at the seaward boundary are based on
observations at the Fixed-Site Monitoring Network (FSMN) station at the GSO dock (station GD
in Fig. 6).
Methods | 17
-------
-71°20'
41°
50'"
41°
40''
41°
30'"
B ackstone River
^ Ten Mile River
Providence
1 1
Kl
1
j i
m
Warren/
Palmer River
Jj
FallRiver
\1) y
\vS i
gb'a SFf '
C ^^3reenwiBl5/'
r
Hunt River
Quonset z7
CD O
o JV
pp (r f5 (
ft 4
/
J T 1 © \
; § iff
ri /1 /
5 /f ^
$ \
TW ™
» /
7* ;
^ -W • P j>
p 1 !
V
v/4^!
rJ / Newport r
' v#v
Aquidneck
Island
Mt. Hope
Stations
WWTPs
6 Km
Figure 6. Wastewater treatment facilities with direct discharge into the Estuary and FSMN
stations. Wastewater treatment facilities: 1-Bucklin Point, 2-Field's Point, 3-E. Providence, 4-Warren,
5-Bristol, 6-Fall River, 7-Newport, 8-Jamestown, 9-Quonset Point, 10-E. Greenwich, and 11-Somerset.
FSMN stations: BR-Bullock's Reach, CP-Conimicut Point, GB-Greenwich Bay, GD-URI/GSO dock,
MH-Mount Hope Bay, MV-Mount View, NP-North Prudence Island, PD-Phillipsdale, PP-Poppasquash
Point, QP-Quonset Point, SR-Sally Rock, and TW-T Wliarf. (Illustration by Jane Copeland, USEPA-
ORD-NHEERL-AED, Narragansett, RI). Data for sensor depths and water depths at these stations is
given in Table 4.
Benthic Boundary Fluxes
Benthic boundary fluxes of oxygen, N, and P, are specified as boundary conditions.
Fulweiler et al. (2010) measured benthic boundary fluxes of oxygen (sediment oxygen demand),
nitrite + nitrate, ammonium, and dissolved inorganic phosphate at six stations: two in the
Providence River, one near Poppasquash Point, and three in Greenwich Bay, and they developed
regression relationships between these rates and water temperature. Fields (2013) also made
some mid-Bay benthic flux rate measurements for these same variables. These were
implemented to represent both spatial and temporal (temperature-dependent) variability.
18 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Atmospheric Deposition Rates of N, P, and CBOD
Atmospheric deposition rates of nitrate-N, ammonia N, total P were obtained from the
literature (Bowen and Valiela 2001; Chen et al. 1985; Luo et al. 2002; Nixon et al. 1995; Yang et
al. 1996). Orthophosphate P and organic P deposition rates were estimated as 80% and 20% of
the total P deposition rate, respectively. CBOD deposition rates were obtained from Jurado et al.
(2008). Values of these rates may be found in Appendix B.
Meteorological (Including Solar Radiation) Data
Modeled solar radiation data for station 725079 (Newport, Rhode Island) were obtained from
the National Solar Radiation Database, (Wilcox 2012; Maxwell 1998). They were retrieved from
http://rredc.nrel.eov/solar/old data/nsrdb/1991 -2010/hourly/list by state.html, and entered into
WASP as daily values of total solar radiation (Langleys/d). WASP used total daily solar
radiation and day length to calculate a daily light curve. Air temperature and wind speed data for
the Potter Cove station on Prudence Island were obtained from NOAA's Ports website
http://tidesandcurrents.noaa. eov/ports/index.shtml?port=nb.
In-Bay Monitoring Data and Sources
Many water-quality surveys have been conducted in Narragansett Bay over the years, but
most have been limited in spatial or temporal scope. For 2009, the surveys most relevant for our
purposes are the Fixed-Site Monitoring Network (FSMN), a survey conducted by Krumholz
(2012), and once- or twice-monthly near-surface and near-bottom nutrient measurements at the
Bullock's Reach (BR) and Conimicut Point (CP) stations (Fig. 6) by NBC.
The FSMN, which includes monitoring stations on buoys and shoreline installations -
generally on docks, throughout much of the Bay (Fig. 6, Table 4), is operated jointly by the
Rhode Island Department of Environmental Management's Water Resources Division, The
Narragansett Bay National Estuarine Research Reserve, the NBC, the University of Rhode
Island's (URI) Graduate School of Oceanography (GSO), and Roger Williams University.
Stations of the FSMN have sensors mounted (usually near the surface and near the bottom).
Sensors at the Phillipsdale (PD), Greenwich Bay (GB), and T-Wharf (TW) sites are mounted on
fixed structures such as docks, the remainder on buoy moorings. Between 2005 and 2011, there
have been a minimum of 10 such monitoring stations, and 7-11 in years between 2012 and 2015.
Data are collected every 15 minutes, generally between May or early June through late October,
and year-round at selected stations. Parameters measured include depth of measurement,
temperature, salinity, chlorophyll a and dissolved oxygen concentrations, and pH. Further
information and data can be obtained at http://www.dem.ri.gov/bart.
Krumholz (2012) conducted a survey that monitored near-surface nutrient concentrations at
13 stations (Fig. 7) at approximately monthly intervals as part of the National Oceanographic
and Atmospheric Administration's Coastal Hypoxia Research Program (NOAA CHRP). The
lower water column was not sampled. Nutrient concentrations measured are for the dissolved
inorganic nutrients NO2, NO3, NH3, PO4, and Si04, and for TN and TP. The samples for TN and
TP determinations were not filtered, so included both dissolved and particulate components. Data
from these sources are being used to provide initial conditions for state variables and as
comparison data during calibration. Data (approximately monthly) from station 03 (Fig. 7) of
this survey are being used to specify ocean boundary conditions.
Methods | 19
-------
Table 4. Locations, sensor depths, and total water depths for Fixed-Site Monitoring Network
stations.
Station Name,
Abbreviation
L atitude
(North)
Longitude
(West)
Average Sensor
Depth Below Water
Surface2 (in)
Estimated Average
Total Water Depthb
(m)
Phillipsdale, PD
41.34175°
71.372.2°
0.54 (top)
1.86 (bott.)
2.4
Bullock's Reach, BR
41.740567°
71.374667°
0.85 (top)
6.98 (bott.)
7.5
Conimicut Point, CP
41.7138°
71.3438°
0.80 (top)
8.59 (bott.)
9.1
North Prudence Island, NP
41.6704°
71.354717°
1.14 (top)
12.77 (bott.)
13.3
Greenwich Bay, GB
41.684833°
71.446033°
1.06 (top)
2.78 (bott.)
3.3
Sally Rock, SR
41.675283°
71.4240167°
1.14 (top)
4.37 (bott.)
4.9
Mount View, MV
41.638467°
71.383683°
0.86 (top)
6.99 (bott.)
7.5
Quonset Point, QP
41.587617°
71.380033°
0.85 (top)
7.65 (bott.)
8.1
URI/GSO Dock, GD'
41.49183°
71.4188°
1.73
8.0
Mount Hope Bay, MH
41.681333°
71.215217°
0.78 (top)
5.58 (bott.)
6.1
Poppasquash Point, PP
41.647433°
71.317467°
0.69 (top)
8.08 (bott.)
8.6
T- Wharf, TW
41.57885°
71.32145°
0.80 (top)
6.10 (bott)
6.6
a Average sensor depths below surface are calculated from Fixed-Site Monitoring Network data files.
b Average total water depth is estimated is 0.5 meter more than average bottom sensor depth, except for
the station at the URI/GSO dock (GD), which has only one sensor.
c There is only one sensor at station GD, it is not located 0.5 m above the bottom.
Analysis of Simulation Results
Analysis of simulation results focuses on dynamics and spatial relationships of model-
simulated and monitored near-surface oxygen and Chi a concentrations at five stations (BR, CP,
NP, MV, QP in Fig. 6 and Table 4) along a 17-km north-south longitudinal transect between the
inner Bay (the Providence River) and the West Passage of the mid-Bay.
Data monitoring sondes are deployed at these five stations for various periods between mid-
to late May and late October. Comparisons between observed and simulated values are for the
period June 1-October 25, which includes the period of sonde deployment common to all five
stations. Unless stated otherwise, model results are shown at hourly intervals and observed
results are shown at the 15-minute interval at which they were recorded.
Gaps in observed data that appear in some figures are the result of either sensor failure or
removal of data during quality control because of sensor drift caused by fouling.
We explore the variability of near-surface observed and modeled oxygen and chlorophyll a
concentrations over diel, intermediate, and seasonal time scales, as well as factors that contribute
to variability at these time scales. We also explore the sensitivity of chlorophyll a and oxygen
concentrations to reduced external nutrient inputs and reduced incident solar radiation.
20 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Unless stated otherwise, all simulation results are for a single calibrated model ain, the
"standard run", with a single set of kinetic parameters and boundary conditions. The values of
the model parameters used in this standard run are presented in Appendix B.
Blackstorie River
MA
CT
Providence
Warren/
Palmer River
#11
Brayton
Fall River
#09
Mt. Hope
\E3ay
Greenwicl
ABay
#07
#14
40'
Hunt River
#08
Quonset
Point <
#16
#06
(Gould
Island
Aquidneck
Island
'#01 •
( CU "O
c c
O OJ
O _W 1
30'
,#04
#02
Newport r
6 Km
#03
Figure 7. Locations of sampling stations for the NOAA CHRP surveys are shown as
numbered filled circles (Krumholz 2012). (Illustration by Jane Copeland.
USEPA/ORD/NHEERL/AED, Narragansett, RI).
Methods | 21
-------
Results
Near-Surface Oxygen Concentrations
Annual Distribution of Simulated Near-Surface Oxygen Concentrations
Figures 8-12 show time series for simulated oxygen and water temperature for the period
March 1-December 31, 2009 and for oxygen solubility (saturation concentration) calculated
from observed temperature and salinity over the June 1-October 25 sensor deployment (Benson
and Krause 1984), for the five stations along the longitudinal transect in mid- and upper- Bay.
This permits comparison of simulated oxygen concentrations with oxygen solubility under actual
conditions. Station Bullock's Reach (BR) is in the Providence River, Conimicut Point (CP) is in
the transition zone between the Providence River and the remainder of the upper Bay, North
Prudence Island (NP) is at the border between the upper Bay and the West Passage, Mount View
(MV) and Quonset Point (QP) are in the West Passage of the mid-Bay (see Fig. 6). Values are
not shown for January and February because this is the model spin-up period, when simulated
values of state variables are relatively strongly affected by often-approximated initial conditions.
Seasonal patterns for time series of simulated oxygen concentrations, and temperature are
consistent among these five stations. At each of these stations, oxygen concentrations decline
from 12-13.2 mg/L in early March to concentrations in the range 3.7-6.5 mg/L in late August
and then increase to 11-12.5 mg/L in late December. Timing of simulated minimum dissolved
oxygen concentrations is coincident with, or within approximately three days of, oxygen
solubility minima and temperature maxima, suggesting that the seasonal pattern of near-surface
oxygen concentration is strongly influenced by temperature and salinity.
14
Oxygen
Oxygen Solubility
Temperature
a.
E
Figure 8. Simulated near-surface oxygen concentration and water temperature at
the Bullock's Reach station, March 1-December 31, 2009, with oxygen solubility
calculated from observed near-surface water temperature and salinity.
22 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
i 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 r~
& ^ <,\* feV* -iV* *¥* voV* Jp JS*
Date
Figure 9. Simulated near-surface oxygen concentration and water temperature at
the Conimicut Point station, March 1-December 31, 2009, with oxygen solubility
calculated from observed near-surface water temperature and salinity.
14
12
10
w>
E
30
Oxygen
Oxygen Solubility
Temperature
& ^ Dp0 ° feV* -ir* vvV* JSP
Date
Figure 10. Simulated near-surface oxygen concentration and water temperature at
the North Prudence Island station, March 1-December 31, 2009, with oxygen
solubility calculated from observed near-surface water temperature and salinity.
Results | 23
-------
—I 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1—
pj- 0
^ ^ JS*
Date
Figure 11. Simulated near-surface oxygen concentration and water temperature at
the Mount View station, March 1-December 31, 2009, with oxygen solubility
calculated from observed near-surface water temperature and salinity.
14
Oxygen
Oxygen Solubility
Temperature
30
& o,S* 6,\*° \* jP
Date
Figure 12. Simulated near-surface oxygen concentration and water temperature at
the Quonset Point station, March 1-December 31, 2009, with oxygen solubility
calculated from observed near-surface water temperature and salinity.
24 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Comparison of Simulated and Observed Near-Surface Oxygen Concentrations
Figures 13-17 present time series of observed and simulated oxygen concentrations ([O2])
for stations along the longitudinal transect between stations BR and QP for the period June 1-
October 25, 2009. Maximum observed oxygen concentrations are greater at the Providence River
stations (BR and CP) than at the other three stations, and high-frequency variability substantially
exceeds that for model results at all stations, particularly at the more northerly stations.
Observed maximum (mid-day) oxygen concentrations at stations BR-QP often substantially
exceed oxygen saturation (solubility) values, which are close to model-calculated values (Figs.
8-12). This is particularly true at stations BR and CP in the Providence River, close to major
nutrient sources, where nutrient concentrations and phytoplankton biomass are higher than at
stations NP, MV, and QP in the West Passage, as demonstrated in section "Comparison of
Simulated and Observed Near-Surface Chlorophyll a Concentrations'' below, leading to higher
oxygen production rates.
Collection and review of data by the FSMN were governed by a detailed and rigorous quality
assurance monitoring plan. Data identified during quality assurance (QA) review as not meeting
measurement performance criteria were rejected or corrected when possible (e.g. to correct for
sensor drift) or were retained and flagged as having limited accuracy. Only data that passed QA
review without rejection or being flagged as corrected or with stipulations about accuracy were
used in this study. This accounts for periods of missing observed data in figures presented in
figures throughout the "Results" section.
20
Observed
Model
0 -I , 1 , 1 , 1 1 1 ,
iY>v
Date
Figure 13. Simulated and observed near-surface oxygen concentrations at the
Bullock's Reach station, June 1-October 25, 2009.
Results | 25
-------
20
18 -
16 -
14 -
—1
—
12 -
CUD
E,
10 -
CM
O
8 -
6 -
4 -
2 -
0 -
«,\V
1\v
1Y*V
Date
Observed
¦ Model
Figure 14. Simulated and observed near-surface oxygen concentrations at the
Conimicut Point station, June 1-October 25, 2009.
«>\v
Observed
- Model
-IVs-
io -
Figure 15. Simulated and observed near-surface oxygen concentrations at the
North Prudence Island station, June 1-October 25, 2009.
26 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Observed
Model
Figure 16. Simulated and observed near-surface oxygen concentrations at the
Mount View station, June 1-October 25, 2009.
Observed
Mode
Figure 17. Simulated and observed near-surface oxygen concentrations at the
Quonset Point station, June 1-October 25, 2009.
Results | 27
-------
Figure 18 presents simulated and observed oxygen concentrations at station Mount View for
the month of July 2009 as an example of observed and simulated diel oxygen cycles for all
stations throughout the summer. Vertical gridlines indicate midnight for each day. The usual diel
pattern is for observed oxygen concentration to decrease during predawn hours, to increase in
magnitude beginning at the onset of daylight, to peak between mid-day to late afternoon, and to
decrease throughout the remainder of the day. Departures from this pattern may be caused by
multiple factors, including short-term changes in incident light and tidal advection of water in the
presence of spatial inhomogeneity in oxygen and nutrient concentrations. The most pronounced
observed daily minima usually occur early in the day, frequently during the predawn period. The
overall pattern for simulated oxygen concentration is similar to that for observed oxygen,
although daily ranges are smaller in magnitude than for measured values.
Observed
Model
Figure 18. Simulated and observed near-surface oxygen concentrations at the Mount
View station, July 1-31, 2009. Vertical gridlines indicate midnight for each day.
Figures 19 and 20 show the diel range (maximum minus minimum) of simulated and
observed oxygen concentrations at stations BR and MV for the period June 1-October 25, 2009.
In general, observed ranges substantially exceed simulated ranges from June 1 to early October
at station BR and June 1 to mid-September at station MV, then decline to values comparable to
or less than modeled values. The average of individual ratios of observed diel oxygen
concentration ranges to simulated individual diel oxygen concentration ranges at BR during the
period June 1-August 31 is 6.0, the maximum ratio is 25.3. For station MV, the average ratio for
the period June 1-September 19 is 2.9 and the maximum ratio is 10.7.
28 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Observed
Mode
Figure 19. Diel range (maximum-minimum) of near-surface simulated and observed
oxygen concentrations at Bullock's Reach station, June 1-October 25, 2009.
Observed
Model
Figure 20. Diel range (maximum-minimum) of near-surface simulated and observed
oxygen concentrations at Mount View station, June 1-October 25, 2009.
Results | 29
-------
Table 5 presents monthly average values of the observed and simulated near-surface diel
oxygen ranges at station MV for June-September 2009, October 1-25, and for the entire period
June 1-October 25. Also shown in the table is the ratio of the observed range to the simulated
range for each of these periods. Average ranges increase June through August, and decline
between August and October. The ratio of the observed to simulated concentration decreases
throughout the period June-October. The maximum and minimum monthly ratios of observed
diel [O2] to modeled [O2] range are 3.42 and 0.80 respectively, and the average ratio over the
period June 1-October 25 is 2.19.
Table 5. Average observed and simulated diel oxygen concentration ranges at station MV and
their ratios for the months of June, July, August, September, October 1-25, 2009, and the period
(June 1-October 25), 2009.
Dates
Simulated average
diel range (mg/L)
Observed average
diel range (mg/L)
Ratio of average ranges:
Ob served/Simulated
6/1-6/30
0.66
2.26
3.42
7/1-7/31
0.85
2.48
2.92
8/1-8/31
1.13
2.92
2.58
9/1-9/30
1.16
2.00
1.72
10/1-10/25
0.86
0.69
0.80
6/1-10/25
0.94
2.06
2.19
Figure 21 shows observed and simulated oxygen concentrations averaged over the period
June 1-October 25 at stations along the transect from BR to QP. These long-term averages show
small variations among stations and that observed and simulated values are in general agreement.
10
BR
CP
QP
NP
MV
t>0
Observed
Model
10
12
! 14 16
Distance South of Fox Point (km)
18
20
22
24
26
Figure 21. Simulated and observed average summer and early fall near-surface
oxygen concentrations at stations along a longitudinal transect in the Providence
River and West Passage. The averaging period is June 1-October 25, 2009.
30 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Comparison of Daily Averaged Simulated and Observed Near-Surface Oxygen
Concentrations
Figures 22-26 show observed and simulated daily-average oxygen concentrations over the
period June 1-October 25, 2009. The shortest-period, high-amplitude variability of observed
values seen in the unaveraged data (Figs. 13-17) is not present in these time series, indicating
that this component of variability in observed unaveraged values is attributable to diel processes.
The total range of observed oxygen concentrations is also less for daily-averaged than for
unaveraged values at each station.
Daily-average simulated oxygen concentrations show less variability than daily-average
observed values for these five stations. Variability of observed oxygen occurs with periods of a
day to a week, and infrequently as long as approximately two weeks. The magnitude of observed
variability is smallest at stations QP and MV and becomes progressively larger for more
northerly stations. The frequency of relatively high peaks in the daily-average observed data is
higher for stations BR and CP than for the other stations.
Observed
Mode
\V>
Figure 22. Simulated and observed daily average near-surface oxygen concentrations
at the Bullock's Reach station, June 1-October 25, 2009.
Results | 31
-------
Observed
Model
Figure 23. Simulated and observed daily average near-surface oxygen concentrations
at the Conimicut Point station, June 1-October 25, 2009.
Observed
Model
Figure 24. Simulated and observed daily average near-surface oxygen concentrations
at the North Prudence Island station, June 1-October 25, 2009.
32 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Model
Figure 25. Simulated and observed daily average near-surface oxygen concentrations
at the Mount View station, June 1-October 25, 2009.
Observed
Model
Figure 26. Simulated and observed daily average near-surface oxygen concentrations
at the Quonset Point station, June 1-October 25, 2009.
Results | 33
-------
Production of Oxygen by Phytoplankton
As described in subsection "The Water Quality Model" of the "Methods" section, rates of
phytoplankton growth and photosynthetic oxygen production by phytoplankton are calculated as
temperature-dependent production rates that are multiplied by a light limitation factor (LLF) and
a nutrient limitation factor (NLF).
Figure 27 shows a representative time series for LLF at station Mount View (MV) for the
month of July, 2009. Tic marks on the abscissa indicate midnight. The LLF increases rapidly
with light intensity from its nighttime value of zero to a value near 1.0 shortly after daybreak. On
days with intense sunlight, there is a mid-day dip in the value of the LLF to represent
photoinhibition, a decrease in the photosynthetic capacity of plants induced by exposure to light
intensity in excess of their light-saturation level (Falkowski and Raven 2007). The size of a mid-
day dip of the LLF is determined by the amount by which the solar radiation at the depth of
calculation exceeds the light-saturation value specified for the phytoplankton group.
ro 0.75
ro 0.5
Figure 27. Simulated near-surface light limitation factor for phytoplankton biomass
growth rate and oxygen production rate at the Mount View station, July 1-31, 2009.
Figure 28 shows simulated hourly NLF and phytoplankton oxygen production rates at MV
for July 2009. Vertical gridlines indicate midnight. The NLF follows a daily cycle, increasing at
night, when nutrient pools are being replenished by respiration and external inputs in the absence
of nutrient uptake because of light limitation, and then generally begins decreasing early to mid-
day because of declining nutrient concentrations caused by nutrient uptake. Oxygen production
rates by phytoplankton at station MV are controlled by the NLF and LLF. Oxygen production
rates rise rapidly beginning at daybreak with the increase in the LLF, and are enhanced by early-
morning high values of the NLF; afternoon production rates decline because of diminishing
values of the NLF and the LLF. Oxygen production rates are particularly high when values of
NLF are elevated. Oxygen production rates often experience a mid-day dip caused by
34 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
photoinhibition. Averaging hourly gross oxygen production gives a mean daily gross oxygen
production rate of 0.48 mg/(L-d) for July and a mean of 0.41 mg/(L-d) for the period June 1-
October 25.
Although details of time series for oxygen production rates and light and nutrient limitation
factors vary among stations and time periods (e.g., diel variability of NLF is greater and
maximum oxygen production rates are higher in the high-nutrient environment of station BR
than at MV), the relationships shown in Figs. 27 and 28 are representative for the purpose of
the discussion in this section.
0.15
M
E
01
4->
to
ce.
c
o
+¦>
u
3
"O
o
0.1
0.05
ft! V."!
¦ Phytoplankton Oxygen
Production Rate
¦ Nutrient Limitation
Factor
0.8
¦ 0.6 £
will
0.4 ro
u_
c
o
h 0.2 "43
ru
4->
E
o
c
0)
V -0.2 -Z.
-0.4
iV*
Date
Figure 28. Simulated near-surface gross oxygen production rate by phytoplankton,
and nutrient limitation factor at the Mount View station, July 1-31, 2009.
Integrating hourly gross oxygen production rates over the day gives daily gross oxygen
production rates between 0.21 and 1.24 mg/(L-d) (Fig. 29) at station MV for the period
June 1-August 31, with an average of 0.47 mg/(L-d), much smaller than the observed diel ranges
in oxygen concentration (Fig. 20).
Near-Surface Chlorophyll a Concentrations
Annual Distribution of Simulated Near-surface Chlorophyll a Concentrations
Figures 30-34 show hourly values of modeled Chi a concentrations [Chi d\ for the period
March 1-December 31, 2009, for stations BR, CP, NP, MV, and QP. Chlorophyll a
concentrations show high-frequency variations for all five stations. For stations BR and CP in the
Providence River, concentrations increase from March 1 through early to mid-May, fluctuate
around relatively constant values from mid-May through mid-August to early October, then
decline through the remainder of the year. These fluctuations have intermediate periods ranging
from a few days to approximately three weeks, with superimposed very high frequency (short-
Results | 35
-------
period) variability. Maximum values of simulated Chi a attained during the summer period
decline monotonically along the transect from stations BR through QP.
Figure 29. Simulated daily gross oxygen production by phytoplankton, integrated
over daylight hours at the Mount View station, June 1-August 31, 2009.
^ ^ *,V*° ^ ^ ^
Figure 30. Simulated near-surface chlorophyll a concentrations at the Bullock's
Reach station, March 1-December 31,2009.
36 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
30
Date
Figure 31. Simulated near-surface chlorophyll a concentrations at the Conimicut Point
station, March 1-December 31, 2009.
25
0 H 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 r
^\V
-------
20 1
18 -
0 H 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 r
& iV*
-------
Effects ofNonphotochemical Quenching on Observed Chlorophyll a
Concentrations
Figures 35 and 36 present observed chlorophyll a concentrations determined at 15-minute
intervals, observed daily average chlorophyll a concentrations, and total incident solar radiation
(displayed at noon) for the month of June 2009 at station MV. All observed chlorophyll a
measurements reported in this report were measured fluorometrically in situ.
On many days, measured Chi a values exhibit a mid-day decline, followed by an increase in
value later in the day (Figs. 35 and 36). The magnitude of this mid-day dip in measured Chi a
varies from day to day, and is often a substantial fraction (sometimes exceeding 50 %) of the diel
range. Such mid-day declines in fluorometrically-measured Chi a values are an indication of
nonphotochemical quenching (NPQ) of Chi a fluorescence, and are not caused by a decline in
Chi a concentrations (Roesler and Barnard 2013); as such, they represent a measurement artifact.
Mechanisms of NPQ are discussed by Falkowski and Raven (2007). Roesler and Barnard (2013)
found decreased quenching on days with reduced insolation. They found strong quenching at a
depth of 2.5 m with photosynthetically available radiation (PAR) in the range 375-600
microEinsteins/m2/s (|iE/m2/s), much weaker quenching with PAR below 200 |iE/m2/s, and some
degree of quenching with any PAR above 80 |iE/m2/s. In a more recent report to the
Massachusetts Water Resources Authority describing measured chlorophyll fluorescence in near-
surface water at an instrument deployment in Massachusetts Bay, Roesler (2018) states that "At
present, it does not appear to be possible to identify a specific irradiance level that coincides with
the onset of NPQ. . . . Therefore, chlorophyll fluorescence observations during all daylight
hours are currently flagged as NPQ impacted and removed from the data stream for both
fluorometers." Evidence of nonphotochemical quenching appears in our study throughout the
June 1-October 25 fluorometer deployment. The values in Figs. 35 and 36 show variable degrees
of quenching, with generally greater mid-day quenching during periods of higher insolation.
Since observed Chi a concentrations presented in this report include this effect, daily variability
in observed chlorophyll a appearing in graphics often overestimate actual variability. Variations
in observed Chi a concentrations also exhibit complicated fine structure within a day that may be
related to factors such as short-term changes in insolation and to tidal transport from nearby
areas with different concentrations.
Results | 39
-------
Obs.Chla • Daily Avg. Obs. Chi a ¦ Solar Radiation
Figure 35. Observed near-surface concentrations of chlorophyll a at 15-minute intervals
and as diel averages, and total daily incident solar radiation for Mount View station,
June 1-15, 2009. Vertical gridlines indicate midnight for each day.
2.
O
40
30 -
20 -
10 -
-Obs. Chi a
• Daily Avg. Obs. Chi a
¦ Solar Radiation
54.9
Figure 36. Observed near-surface concentrations of chlorophyll a at 15-minute intervals
and as diel averages, and total daily incident solar radiation for Mount View station,
June 16-30, 2009. Vertical gridlines indicate midnight for each day.
40 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Comparison of Simulated and Observed Near-Surface Chlorophyll a
Concentrations
Figures 37-41 show simulated and fluorometrically measured values of Chi a for the period
June 1-October 25. Observed values include the effects of nonphotochemical quenching. There
are large gaps in the observed data record for station CP and smaller gaps for other stations.
Measured and simulated values both decline during September and October, the former more
quickly than the latter. As is the case with oxygen concentrations, measured Chi a concentrations
exhibit much more variability than do simulated values during summer months, but this disparity
declines with the reduction in the amplitude of diel variations of observed Chi a during
September and October. Differences between actual (as opposed to measured) and simulated
values of Chi a cannot be well quantified because of the confounding effects of NPQ of Chi a
fluorescence. Simulated and observed concentrations over the period June 1-August 31 both
decline along the transect between stations BR and QP.
Observed and simulated chlorophyll a concentrations averaged at each station over the
June 1-October 25 monitoring period are shown in Fig. 42. Unlike the relatively flat spatial
distribution of oxygen concentrations in Fig. 21, both observed and simulated concentrations of
Chi a decline by a factor of approximately 3.7 along this transect between stations BR and QP.
Model averages exceed observed values at all stations. This is to be expected since simulated
chlorophyll a concentrations exceed most observed values beginning in early September. To
examine average agreement between model and observed values during the period less affected
by this late-season divergence between simulated and observed values, we plot chlorophyll a
averaged over the period June 1-August 31, 2009 in Fig. 43, showing close agreement between
average model and observed values.
Observed
Model
Figure 37. Simulated and observed near-surface chlorophyll a concentrations at the
Bullock's Reach station, June 1-October 25, 2009.
Results | 41
-------
Observed
Model
Figure 38. Simulated and observed near-surface chlorophyll a concentrations at the
Conimicut Point station, June 1-October 25, 2009.
Observed
Model
Figure 39. Simulated and observed near-surface chlorophyll a concentrations at the
North Prudence Island station, June 1-October 25, Figure 2009.
42 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
—I
20 -
W)
16 -
c
.c
u
12 -
1 1
8 -
4 -
0 -
1\* l\*
Date
Observed
-Model
Figure 40. Simulated and observed near-surface chlorophyll a concentrations at the
Mount View station, June 1-October 25, 2009.
30
25 -
20 -
W>
Is
s
u
— 10 -
15 -
&
1\V
n\*
V
A*
Date
Observed
¦Model
Figure 41. Simulated and observed near-surface chlorophyll a concentrations at the
Quonset Point station, June 1-October 25, 2009.
Results | 43
-------
w>
rc
l-
<
30
BR
20
CP
NP
MV
QP
Observed
Model
8 10 12 14 16 18 20 22 24 26
Distance South of Fox Point (km)
Figure 42. Average simulated and observed summer and early fall near-surface
chlorophyll a concentrations at stations along a longitudinal transect in the Providence
River and West Passage. The averaging period is June 1-October 25, 2009.
30
25
00 20
2.
— 15 -
<3
u
a>
2P io
CD
a>
>
< 5
BR
CP
—•— Observed
A Model
MV
NP
QP
10 12 14 16 18 20 22 24
Distance South of Fox Point (km)
26
Figure 43. Average simulated and observed summer near-surface chlorophyll a
concentrations at stations along a longitudinal transect in the Providence River and
West Passage. The averaging period is June 1-August 31, 2009.
44 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Comparison of Daily Averaged Simulated and Observed Near-Surface
Chlorophyll a Concentrations
Figures 44-48 present daily average values of simulated and observed chlorophyll a
concentrations for all five stations. As is the case with oxygen concentrations, using daily
averages eliminates the shortest-period, high-amplitude variability of observed values from these
time series, indicating that these very short-period variations are attributable to processes at the
diel time scale. Agreement in timing and magnitudes of variations is best in the more southerly
stations (MV and QP), particularly from early June to mid- to late August, than in more northerly
stations.
70
60
I I Observed
I I Model
>^MfrvVVV\
0 -I 1 1 1 1 1 1 1 1 r
<»\V
Date
Figure 44. Simulated and observed daily average near-surface chlorophyll a
concentrations at the Bullock's Reach station, June 1-October 25, 2009.
Results | 45
-------
Model
Observed
Figure 45. Simulated and observed daily average near-surface chlorophyll a
concentrations at the Conimicut Point station, June 1-October 25, 2009.
Observed
Model
Date
Figure 46. Simulated and observed daily average near-surface chlorophyll a
concentrations at the North Prudence Island station, June 1-October 25, 2009.
46 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Model
Observed
Figure 47. Simulated and observed daily average near-surface chlorophyll a concentrations
at the Mount View station, June 1-October 25, 2009.
Observed
Model
Figure 48. Simulated and observed daily average near-surface chlorophyll a concentrations
at the Quonset Point station, June 1-October 25, 2009.
Results | 47
-------
Responses of Simulated Near-Surface Oxygen and Chlorophyll a Concentrations to
Changes in Incident Light and Nutrient Inputs
Simulations in addition to the standard model ran (used to produce all results described earlier
in this report) were performed to determine the independent effects of changes in solar radiation
and nutrient inputs on Chi a and oxygen concentrations. One run reduced the solar radiation used
in the standard run to zero, keeping all model kinetic parameters and other forcing functions the
same as in the standard run. Two additional runs decreased or increased assumed external inputs
to the Bay from WWTFs, tributaries, atmospheric deposition, and across the seaward boundary by
a factor of two. This was done by decreasing or doubling the atmospheric deposition rates
specified in the "Globals" subscreen of the "Constants" input screen, and by resetting the scale
factors for nutrients in the "Boundaries" input screen from 1.0 to either 0.5 or 2.0.
Figures 49 and 50 show the effects on Chi a and oxygen concentrations at station MV of
reducing solar radiation input assumed in the model to zero. The average near-surface Chi a
concentration over the period June 1-October 25 declines by 98% from 9.44 |ig/L with observed
solar radiation to 0.21 |ig/L in the absence of sunlight (Fig. 49), with the small residual Chi a
concentration most likely attributable to import across the seaward boundary. The average
dissolved oxygen concentration over the period June 1-October 25 declines by 7.4% from 7.14
mg/L for full sunlight to 6.61 mg/L in the absence of solar radiation (Fig. 50).
18
u 1 1 1 — i i I I I i i
Date
Figure 49. Near-surface modeled chlorophyll a concentrations for 2009 at Mount View,
with full incident light (standard run) and with incident light reduced to zero.
48 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
2
& <*\* vo\* v\V*
Date
Figure 50. Near-surface modeled oxygen concentrations for 2009 at Mount View,
with full incident light (standard run) and with incident light reduced to zero.
Figures 51-53 show the effects on Chi a and oxygen concentrations at station MV of halving
and doubling external inputs of nitrogen and phosphorus. Average simulated Chi a
concentrations over the period June 1-October 25 decline by 49% from 9.44 |ig/L to 4.77 |ig/L
when nutrient inputs are halved and increase by 103% to 19.19 |ig/L when nutrient inputs are
doubled (Fig. 51). Dissolved oxygen concentrations decline by 3.5% from 7.14 mg/L to
6.89 mg/L when nutrient inputs are halved and increase by 7.1% to 7.65 mg/L when nutrient
inputs are doubled (Figs. 52 and 53).
Figure 54 and Table 6 compare the diel ranges of observed and modeled diel oxygen
concentrations at Mount View for the standard run and the run with doubled external nutrient
inputs for the period June 1-October 25. The average diel range of observed oxygen
concentrations for the period June 1-October 25 is 2.06 mg/L. During this period, the average
diel ranges for the runs with standard and doubled nutrient inputs are 46% and 60% of the
average observed diel range, respectively. There are, however, substantial changes in diel
variability of observed oxygen concentrations during this period, with ranges declining and
substantially lower after September 15 than earlier. Average modeled diel oxygen ranges for the
runs with both standard and doubled nutrient inputs increase June 1 through early to mid-
September and decrease thereafter. Average modeled diel oxygen ranges for the period June 1-
September 15 increase by 30% when nutrient inputs are doubled; they are 39% of the average
range of observed concentrations for standard nutrient inputs and 51% when nutrients are
doubled.
Results | 49
-------
-Double Nutrients
-Standard Nutrients
- Half Nutrients
M 20
& ^ o\* ^ ^ jfP
Date
Figure 51. Near-surface modeled chlorophyll a concentrations for 2009 at Mount
View, with standard nutrient input rates (standard run) and with halved and
doubled nutrient input rates from WWTFs, tributaries, atmospheric deposition,
and the seaward boundary.
14
Half Nutrients
Standard Nutrients
2 -
0 -I 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 r
& ^ jfp
Date
Figure 52. Near-surface modeled oxygen concentrations for 2009 at Mount View, with
standard and halved nutrient input rates from WWTFs, tributaries, atmospheric
deposition, and the seaward boundary.
50 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
16
Double Nutrients
14
Standard Nutrients
12
—i 10
W>
E 8
6
4
2
0
Date
Figure 53. Near-surface modeled oxygen concentrations for 2009 at Mount View, with
standard and doubled nutrient input rates from WWTFs, tributaries, atmospheric
deposition, and the seaward boundary.
8
7
Observed
' Model - Standard Nutrients
Model - Double Nutrients
;vw
Figure 54. Diel ranges (maximum-minimum) at Mount View of near-surface observed
oxygen concentrations and of simulated diel ranges for observed (standard) and doubled
nutrient input rates from WWTFs, tributaries, atmospheric deposition, and the seaward
boundary.
Results | 51
-------
Table 6. Average observed and simulated diel ranges of oxygen concentrations at Mount View for
the periods June 1-October 25, 2009 and the subperiod June 1-September 15. Averages for model
results do not include dates with no observed data. Modeled diel ranges are for observed (standard) and
doubled nutrient inputs.
Time Period
Average observed
diel range
(mg O2/L)
Average modeled
diel range for
standard nutrients
(mg O2/L)
Average modeled
diel range for
double nutrients
(mg O2/L)
June 1-October 25
2.06
0.95
1.23
June 1-September 15
2.51
0.98
1.27
Summary and Discussion
Preliminary simulations early in this study showed that while simulated oxygen and Chi a
concentrations gave close approximations of observed seasonal trends, the model substantially
underestimated observed variability over the diel light-dark cycle in near-surface waters of
Narragansett Bay, highlighting simulation of oxygen and Chi a at short time scales as a topic
requiring further investigation. The primary purpose of our study has been to calibrate the model
to minimize this difference between the diel ranges of simulated and observed values of oxygen
and Chi a concentration in near-surface waters.
Model values of oxygen and Chi a concentrations are compared with measurements made at
15-minute intervals at five stations along a 17-km north-south longitudinal transect from the
upper to the mid-Bay over the June 1-October 25 monitoring period. Calibration of the model
included consideration of oxygen, Chi a, and nutrient dynamics in both surface and bottom
waters. Nutrient concentrations were generally available only on a monthly interval (twice
monthly in the Providence River), and only in surface water for most stations. While these
nutrient data were used in model calibration to evaluate general simulated concentrations, they
are not useful for calibrating or evaluating diel or weekly nutrient dynamics. Because our
primary purpose is to explore diel dynamics, we limit our description of oxygen and Chi a
dynamics to near-surface waters since this is the portion of the water column where
phytoplankton production, the main factor driving diel variations in oxygen and Chi a variations,
is most important.
Simulated oxygen concentrations follow observed seasonal trends and are strongly
influenced by oxygen solubility, as calculated from measured water temperature and salinity, at
all stations along the longitudinal transect. However, they substantially underestimate observed
diel variability for the period June 1 through early to mid-September, after which diel variability
of observed values declines through late October, becoming comparable to simulated ranges in
October. At station BR, in the nutrient-rich Providence River, the mean and maximum ratios
between observed and simulated diel oxygen range over the period June 1-October 25 are 4.5
and 25.3. At station MV, in the mid-estuary and further removed from large nutrient sources, the
mean and maximum ratios are 2.5 and 10.7. Observed ranges in oxygen concentrations decline in
September and October, becoming comparable to model-calculated ranges in October.
52 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
Average June 1-October 25 simulated and measured oxygen concentrations are similar and
show only small variations among the five stations analyzed, reflecting small differences in
oxygen solubility along the longitudinal transect.
Chlorophyll a concentrations were measured in situ using fluorometry. Chi a data show
frequent mid-day dips caused by nonphotochemical quenching of Chi a fluorescence. This
measurement artifact often extends the daily minimum of reported Chi a values downward,
thereby artificially increasing the diel range, precluding precise quantification of diel ranges of
actual Chi a values. It might be useful in future to calibrate Chi a using only night-time in-situ
fluorometric measurements, which would not be influenced by nonphotochemical quenching.
Simulated Chi a concentrations follow observed seasonal trends from June 1 through early
September, but decline more slowly than observed values from early September through October
25. Magnitudes of high-frequency (diel) cycles of measured Chi a concentrations during June
through early September are substantially larger than for model values, although variability in
observed values declines through September and October. These declines in diel variability of
observed Chi a and oxygen concentrations in September and October occur during a period of
seasonally declining solar radiation and water temperature.
The divergence between observed and simulated long-term trends in Chi a during September
and October may be a consequence of a shift in the species composition of the phytoplankton
community during this period of declining solar radiation and water temperature. We did not
attempt to simulate such a shift in community composition by including multiple phytoplankton
groups in our standard model configuration since test runs with two modeled phytoplankton
groups showed that this would not substantively affect simulated diel variability of Chi a or
oxygen, particularly during the June-August period, when the differences between diel
variability of observed and simulated values are largest. In addition, simulation results for
diatoms as a second phytoplankton group would have been speculative, given the general lack of
data for silica concentrations in WWTF effluents (Table 3).
Based on nitrogen and phosphorus limitation factors, simulated production rates of
phytoplankton biomass and oxygen at Quonset Point and Mount View are limited by nitrogen
during the entire simulation period, but at North Prudence Island, primary production is co-
limited by nitrogen and phosphorus from early May to mid-October, and by nitrogen alone for
the rest of the year. At Conimicut Point (CP) and Bullock's Reach (BR), phosphorus limitation
dominates from early May through early October, and nitrogen for the remainder of the year.
Four of ten measurements of DIN and DIP by the Narragansett Bay Commission on distinct
dates at Bullock's Reach over the period May 20-October 14, 2009 have molar ratios of DIN to
DIP between >22.2 and >94.5 (i.e. >22.2, >35.7, 43.7, >94.5), substantially greater than the
value 16 often used as a criterion indicating onset of phosphorus limitation
(http://snapshot.narrabay.com/WaterQualityInitiatiyes/NutrientMonitorina). The inequalities in
some of these molar DIN/DIP values are a result of a measured NH3-N or DIP value at or below
the detection limit. In such cases, an NH3-N value was assumed to zero, thus underestimating
DIN, and/or a DIP value at or below the detection limit was assumed to be at the detection limit
so that the calculated molar DIN/DIP value was a lower bound. Three of eight measurements of
DIN and DIP (distinct dates) by Krumholz (2012) over this period give molar DIN/DIP ratios
between 17 and 25 near this station. These results suggest frequent phosphorus limitation at this
location in the Providence River.
Summary & Discussion | 53
-------
The flow-weighted average of the molar DIN to DIP ratio in tributaries (Blackstone,
Moshassuck, Pawtuxet, Ten Mile, and Woonasquatucket Rivers) and WWTFs (Bucklin Point,
East Providence, and Fields Point) that discharge to the Providence River for the year 2009 is
98.7 (106 for tributaries and 17 for WWTFs), well above the value of 16 often used as the value
indicating onset of phosphorus limitation.
Given the low frequency (biweekly) of nutrient concentration measurements and the absence
of measurements of tributary DOP concentrations, which may be rapidly mineralized to DIP, and
the uncertainties in DIP concentration values in WWTF effluents, it is possible that our
simulation of nearly continuous phosphorus limitation of primary production in the Providence
River stations (BR and CP) is in part a result of underestimation of actual phosphorus loading to
the Providence River, where approximately 40% of measured DIN/DIP values during the period
of peak phytoplankton production suggest phosphorus limitation in the upper water column.
Diel ranges of observed Chi a values decrease from north to south along the longitudinal
transect. Modeled and observed Chi a averaged over the period June 1-August 31 at individual
stations agree well and decline by a factor of more than three between stations BR and QP.
In model sensitivity analyses, responses of simulated oxygen and Chi a concentrations to
large assumed changes in solar radiation and external nutrient inputs differ markedly. The
average near-surface Chi a concentration over the period June 1-October 25 declines by 98%
from 9.44 |ig/L with observed solar radiation to 0.21 |ig/L in the absence of sunlight, with the
small residual Chi a concentration most likely attributable to import of phytoplankton across the
seaward boundary, which was not suppressed for this scenario. The average dissolved oxygen
concentration over the same period declines by only 7.4% from 7.14 mg/L for observed sunlight
to 6.61 mg/L in its absence. Average simulated Chi a concentrations over the period June 1-
October 25 decline by 49% from 9.44 |ig/L to 4.77 |ig/L when nitrogen and phosphorus inputs
are halved and increase by 103% to 19.19 |ig/L when nutrient inputs are doubled. Dissolved
oxygen concentrations decline by 3.5% from 7.14 mg/L to 6.89 mg/L when nutrient inputs are
halved and increase by 7.1% to 7.65 mg/L when nutrient inputs are doubled. These differences
between the responses of Chi a and oxygen to these model manipulations are attributable to the
importance of light and nutrients to phytoplankton production, in contrast to air-sea exchange of
oxygen, as constrained by oxygen solubility, and the low rates of phytoplankton oxygen
production calculated by the model.
Model-calculated production rates of oxygen are insufficient to support the observed diel
ranges of oxygen concentrations. Since model calculations of the rates of oxygen and biomass
production by phytoplankton are proportional, this explains the model's underestimation of the
diel ranges in the standing stock of both. Phytoplankton production is limited in the model by
nutrient availability. Nutrient concentrations increase at night as nutrient pools are replenished
by respiration and external inputs with no uptake, and decrease after daybreak as production
rises, depleting nutrients. Oxygen and Chi a production rates are zero during the night, followed
by a rapid increase after daybreak, followed later in the day by a decrease in production because
of the decrease in nutrients during the daylight period, then the loss of light.
The general agreement between simulated seasonal trends of oxygen concentrations and
oxygen solubility indicates that the dominant factors governing model calculation of oxygen
concentrations are physical, namely air-sea exchange and oxygen solubility. The latter is
54 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
determined by temperature and salinity. Imbalance between primary production and community
respiration can shift observed oxygen concentrations away from saturation (solubility-controlled)
values. However, the effects of short-term shifts in the balance between production and
respiration on oxygen concentrations will be transient because of air-sea exchange. Agreement
between seasonal trends of simulated oxygen and oxygen solubility is poorest before early
August, when simulated concentrations somewhat exceed solubility. This is consistent with the
difference between simulated oxygen concentrations with full and zero solar radiation (Fig. 50),
which is the modeled contribution of photosynthetically produced oxygen. In that figure, the
excess of oxygen concentration with full sunlight over that with no sunlight is greatest before
August.
The decline of simulated (and observed) chlorophyll a concentrations between monitoring
stations BR and QP, averaged over the period June 1-August 31, is consistent with a decline in
nutrient concentrations along the longitudinal transect. The small variations in average (June 1-
October 25) observed and simulated oxygen concentrations along this same transect are
consistent with the small variations in solubility among these stations.
Model kinetic parameters governing phytoplankton growth and oxygen production,
mineralization of organic nutrients, and nutrient uptake were varied over ranges supported by
literature values during model calibration. Some of these changes in values of kinetic parameters
yielded incremental increases in phytoplankton oxygen production, but none large enough to
approximate observed June-September diel ranges in oxygen concentration.
Some differences between model results and observed values could be attributable to
uncertainties in input data. Nutrient loads from the watershed and WWTFs are calculated as the
product of water inflow and nutrient concentration. Flow data for tributaries and two large
WWTFs are based on daily monitoring, but flow data for the other seven Rhode Island WWTFs
are monthly averages, and for the two WWTFs in Massachusetts are annual averages. For details
see section " Tributary, Groundwater, and Effluent Inflow Entered into EFDC\ Nutrient
concentration data for tributaries are based on measurements generally made twice per month.
Nutrient concentrations for two large WWTFs are based on measurements made three
consecutive days per week, while values for the remaining WWTFs are based on once- or twice-
monthly measurements. In addition, ammonia-N concentrations were not directly measured at
four of the eleven WWTFs and were estimated from total Kjeldahl-N measurements at the
affected stations. Phosphorus concentrations were measured only as total phosphorus (TP).
These TP concentrations were measured at only three WWTFs, and had to be estimated for the
other eight WWTFs. In addition, dissolved organic phosphorus and dissolved inorganic
phosphorus were not measured separately in WWTF effluents, but were estimated as constant
fractions of measured TP. For details, see Sections "Boundary Concentrations for Water Quality
Constituents in Tributaries'' and " Wastewater Treatment Facility Discharges into Narragansett
Bay". While the sparseness of many of these data introduces some uncertainty into nitrogen and
phosphorus loading rates from tributaries and WWTFs, it is unlikely this explains the model's
inability to reproduce observed diel oxygen ranges, since even a doubling of nutrient loading
rates from these sources and atmospheric deposition fails to bring diel ranges of oxygen
concentrations close to observed ranges.
Another potential cause of some degree of difference between observed and simulated
concentrations of water quality constituents is the vertical thickness of a model grid cell, which
discretizes the modeled concentration values. Because of variation in the thickness of grid layers
over the tidal cycle (always one-eighth of the total local water depth), the monitoring sonde may
Summary & Discussion | 55
-------
reside in different grid layers during different tide stages, while simulated results at a given
station are presented for a single layer.
Inputs of water and dissolved and suspended materials into the Bay from tributaries, overland
flow from riparian areas, groundwater, and WWTFs are equally partitioned between receiving
segments in the top two layers of the model grid. The decision to partition inputs vertically in
this way is based on calibration of EFDC simulations of salinity distributions in the Bay and on
review of near-field spatial distributions in the Bay of dye introduced into WWTF effluents. For
further details, see Section "Model Inflows, Loads, and Other Forcing Functions" and
Abdelrhman (2015). While this procedure cannot account for temporal changes in vertical
partitioning of nutrients, it leads to higher nutrient inputs into, and higher primary production
rates in, the two near-surface grid layers than would uniform distribution throughout the water
column, and therefore does not lead to a decrease in primary production in near-surface waters.
None of the above-mentioned factors appear to account for the large discrepancies between
the observed and simulated diel variability in oxygen and Chi a concentrations. Such effects may
possibly be caused by processes important at the diel time scale that are not included in the
model.
As described in subsection "The Water Quality Model" of the "Methods" section, WASP:
• takes into account day-to-day and diel variations in solar radiation,
• calculates nutrient limitation as a reduction of phytoplankton production by the most-
limiting nutrient (dissolved inorganic nitrogen = ammonia-N + nitrate-N + nitrite-N or
dissolved inorganic phosphorus, or dissolved inorganic silica), with silica not included in
this model application,
• calculates oxygen production by phytoplankton as proportional to production of
phytoplankton biomass, making all oxygen production subject to nutrient limitation, and
• uses phytoplankton biomass as carbon (C) to calculate dynamics of phytoplankton and
their interactions with other state variables, e.g. through nutrient uptake. Chi a is
calculated from phytoplankton C using a constant user-specified carbon-to-Chl a ratio for
each phytoplankton group and does not enter into any other model calculations of
phytoplankton dynamics.
Details of diel phytoplankton growth are more complicated than this, however, and include
factors such as temporal variability in the carbon to chlorophyll a ratio, dependence of
photosynthesis rates on chlorophyll concentrations, storage and release of dissolved organic
matter, uptake of organic forms of nutrients, and temporal changes in preferences for specific
components of DIN (Antia et al 1991; Falkowski et al. 1985; Falkowski and Raven 2007; Glibert
et al. 1991; Thornton 2014; Xu et al. 2012). None of these processes are explicitly included in
the model. Oxygen production by phytoplankton is modeled in WASP as proportional to and
simultaneous with biomass production, whereas photosynthetic production of oxygen and
carbohydrates actually precede incorporation of these carbohydrates and nutrients into other
components of algal biomass, including chlorophyll.
Uptake of organic nutrients is a potentially important source of nutrients to phytoplankton
that is not included in the WASP model. Concentrations of organic nutrients in aquatic systems
often substantially exceed concentrations of inorganic nutrients, particularly during periods of
56 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
-------
drawdown of inorganic nutrients by high phytoplankton growth rates. A series of Bay-wide
water quality surveys in Narragansett Bay in October and November 1985 and in April and May
1986 found that Bay-wide molar ratios of DON to DIN ranged from 1.0 to 10.5, and that ranges
of DON/DIN in individual Bay segments ranged from 0.27 to 29.7 (Pilson and Hunt 1989). The
DON pool in aquatic systems may consist of a variety of chemical forms, some of which are
available to phytoplankton (Antia et al. 1991). Uptake of urea and dissolved free amino acids
have received particular attention (Antia et al. 1991; Bradley et al. 2010a and 2010b; Glibert et
al. 1991; Xu et al. 2012). The lack of a mechanism for uptake of organic nutrients in the model is
addressed in this study by calibrating DON and DOP mineralization parameters to increase
availability of these nutrients as DIN and DIP. Including state variables for labile and refractory
organic nutrient pools in the model might enhance simulation of DON and DOP mineralization.
Phytoplankton release of organic compounds, including carbohydrates, that do not contain
nitrogen or phosphorus (Bj0rnsen 1988; Lignell 1990; Myklestad 1995; Thornton 2014) may
also be important to a full representation of phytoplankton growth and oxygen production. For
instance, explicit inclusion of carbohydrate production and excretion may be useful in improving
the model's simulation of the full range of oxygen and chlorophyll a concentrations observed in
the diel cycle. Daily oxygen production is limited by nutrient availability in WASP, but
carbohydrates may be produced by photosynthesis without nutrient uptake, enhancing oxygen
production rates beyond those permitted in this model version. Carbohydrates excreted by
phytoplankton (Thornton 2014) could also represent an important substrate for growth of
bacteria (Lignell 1990), which contribute to community respiration.
While temporal changes in phytoplankton carbon to Chi a ratios may not be an important
factor in diel oxygen and Chi a dynamics, they can be important over longer time scales.
Variable carbon to Chi a ratios are modeled by Laws and Chalup (1990); Chapra (1997); and
Sadeghian et al. (2018). Falkowski et al. (1985) present relationships between phytoplankton
growth rates and influencing factors.
In summary the WASP model is generally used to simulate monthly, seasonal, or longer-term
variations of Chi a and oxygen concentrations. In our study, Version 7.52 of WASP substantially
underestimates the observed diel range of oxygen concentrations. WASP also appears to
underestimate the diel range of observed Chi a concentrations, although the degree of
underestimation is difficult to determine in this study because field measurements of Chi a were
made fluorometrically in situ, and were subject to nonphotochemical quenching of Chi a
fluorescence. It may in future be advisable to use only night-time fluorometric measurements,
which are not susceptible to nonphotochemical quenching (see Roesler 2018), in calibrating the
model.
This application of WASP has been to Narragansett Bay, a hydrodynamically and
structurally complex estuary with large nutrient inputs at its northern (inner) end. It would be
useful to apply the newest version of WASP to other systems with appropriate diel observational
data to test the generality of our results at this time scale.
The WASP model is periodically updated. A new version of WASP (Version 8.0) was
released in 2016, well into the period of this study. Modifications incorporated into Version 8
Summary & Discussion | 57
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include dynamic allocation of grid cells to permit use of larger numbers of grid cells than
previously possible, changes to the handling of light data to permit specification of light data in
multiple wavelength bands, and the ability to simulate macroalgae. We do not expect that these
changes to the model will affect the calculations of diel oxygen and Chi a dynamics produced in
our study. If further studies indicate that model changes would improve simulation of diel
oxygen and chlorophyll dynamics, they can be incorporated into future model versions.
Continued modeling of nutrient, phytoplankton, and oxygen dynamics in Narragansett Bay using
WASP8 is ongoing at our laboratory. Further information on WASP8.0 and subsequent releases,
including documentation, tutorials on WASP8, and other water quality models and WASP8
download information may be found at https://www.epa.gov/ceam/water~quality~analysis~
simulation-program-wasp.
58 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Appendix A - Other Recent Modeling Studies on
Narragansett Bay
The evaluation of the USEPA's WASP model described in the main body of this report is
one of a number of recent modeling studies conducted in Narragansett Bay. Other recent
modeling studies conducted in Narragansett Bay (the Bay) are listed and briefly described below.
The context for these studies is a nutrient reduction program conducted over the years 2005-
2012, following a large fish kill (approximately 1 million fish) resulting from an episode of
anoxia in Greenwich Bay in 2003 (RIDEM 2003), a side-embayment of Narragansett Bay
(Fig. 2). In addition, a tunnel that stores combined sewage and runoff flows that formerly
discharged to the Bay and now routes them to a WWTF became operational in 2008, further
reducing nutrient inputs to the Bay. For further information concerning the nutrient reduction
program, see section "Water Quality and Ecological Concerns in Narragansett Bay". The
modeling studies described here were conducted in part to test the ability of these models to
simulate the Bay's responses to these nutrient reductions.
The studies summarized below have been facilitated by data collected near the surface and
near the bottom of the water column at up to 12 sites in Narragansett Bay from 2005 to present at
15-minute intervals by the Narragansett Bay Fixed-Site Network, a network of sensors mounted
on buoys and fixed structures throughout the Bay (see locations of monitoring stations in Fig. 6).
Parameters measured are concentrations of oxygen and chlorophyll a, and water temperature,
salinity, and pH.
Information on Narragansett Bay and its watershed, including nutrient loading, may be found
in a compilation of articles edited by Desbonnet and Costa-Pierce (2008) and in a report by the
Narragansett Bay Estuary Program (NBEP 2017).
A modeling study conducted in parallel to that described in the main body of this report
included improvements to the simulation of dispersion in the Environmental Fluid Dynamics
Code (EFDC), a hydrodynamic model, and simulation of water quality using a water quality
module included in EFDC (Hamrick 1992, 1996). Results of this study are described in a series
of reports.
• Development of the model grid for the Bay and calibration of the model is described by
Abdelrhman (2015), including comparison of model simulations and observed values of
water surface elevation, current speed and direction, as well as water salinity and
freshwater and estuarine water flushing times in the estuary.
• Simulated concentrations of total suspended solids and sediment deposition in the Bay,
and their relationship to factors such as river discharge rate, and the effect of spring-neap
tide cycles on resuspension are described by Abdelrhman (2016a).
• Sediment processes, including deposition of organic matter, and processing of particulate
organic matter including nutrients and sulfur in sediments, calculation of sediment
oxygen demand, and fluxes of nutrients, sulfide, and methane from sediments to the
overlying water column are described by Abdelrhman (2016b).
• Dynamics of oxygen, chlorophyll a, and nutrients are modeled by Abdelrhman (2017)
using the water quality module included in EFDC.
Appendix A | 65
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Other models, such as a bio-optical model (Thursby et al. 2015) and other related studies
conducted at the Atlantic Ecology Division of the National Health and Environmental Effects
Research Laboratory of USEPA's Office of Research and Development are summarized by
Rashleigh et al. (2015).
The National Oceanic and Atmospheric Administration's (NOAA) Coastal Hypoxia
Research Program (CHRP) has supported a monitoring and modeling program in the Bay. One
of the models developed in CHRP is the EcoGEM model, which segments Narragansett Bay into
15 two-layer segments (30 volume elements) and simulates six state variables: concentrations of
oxygen, phytoplankton biomass (as carbon), dissolved inorganic nitrogen, dissolved inorganic
phosphorus, and salt as well as benthic carbon (mass of carbon delivered to the benthos from the
water column, minus benthic metabolism). Dissolved organic nitrogen and dissolved organic
phosphorus are not included in the model. Ecological simulations within each volume element
are based on empirically-derived formulations from the literature and integrated over a day
(Vaudrey 2016). Physical transport among volume elements over each full day is calculated with
a much finer grid and with a time step of 10 seconds (Kremer et al. 2010) using the Regional
Ocean Model System (ROMS) (Haidvogel et al. 2000; Warner et al. 2005), and stored in an
array - the Gross Exchange Matrix (GEM). Ecological changes through the day in each volume
element are combined with the exchange data from all other volume elements once per day using
the GEM, giving the model an effective time step of one day.
A related model is the EcoOBM model, which employs the ecological model of EcoGEM,
but calculates transfers using a box model that determines daily transfer coefficients using salt
balance (Officer 1980). The model and applications are described by Brush (2016). EcoOBM
requires daily input data for freshwater inflows to the Bay and salinity in each model volume
element and at the seaward boundary. The EcoGEM and EcoOBM models both have a daily time
step, and cannot calculate diel variability of oxygen concentrations, but Brush has developed a
statistical method for estimating minimum oxygen concentrations from model output (Vaudrey
2016). A variant of the EcoOBM model that includes macroalgae has been applied to Greenwich
Bay, a sub-embayment of Narragansett Bay (Brush and Nixon 2010, 2017).
An updated version (SNB-ROMS) of the Regional Ocean Model (ROMS) has been
developed for use in the Seekonk River-Narragansett Bay system (Kincaid 2018). The model
includes a high-resolution grid for the Seekonk River up to the head of tide at Slater Dam, and a
coupled simple ecosystem model, referred to as an NPZD model, that includes state variables for
nitrogen (N), phytoplankton (P), zooplankton (Z), and detritus (D) (Franks et al. 1986; Franks
2002). The model does not simulate oxygen dynamics. The SNB-ROMS model has been used to
test the effects on phytoplankton concentrations of the spatial resolution of the model grid and of
reductions of nitrogen in WWTF effluents from 15 mg/L to 5 mg/L, from 5 mg/L to 3 mg/L, and
from 3 mg/L to 0 mg/L.
66 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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References for Appendix A
Abdelrhman, M.A. 2015. Three-Dimensional Modeling of Hydrodynamics and Transport in
NarragansettBay. EPA/600/R-15/152. U.S. Environmental Protection Agency, Narragansett, RI.
Abdelrhman, M.A. 2016a. Modeling Total Suspended Solids (TSS) Concentrations in Narragansett
Bay. EPA/600/R-16/195. U.S. Environmental Protection Agency, Narragansett, RI.
Abdelrhman, M.A. 2016b. Modeling Benthic Sediment Processes to Predict Water Quality and
Ecology in Narragansett Bay. EPA/600/R-16/202. U.S. Environmental Protection Agency,
Narragansett, RI.
Abdelrhman, M.A. 2017. Three-dimensional Modeling of Water Quality and Ecology in
Narragansett Bay. EPA/600/R-16/203. U.S. Environmental Protection Agency, Office of
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Brush, M.J. and S.W. Nixon. 2010. Modeling the role of macroalgae in a shallow sub-estuary of
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Desbonnet, A. and B.A. Costa-Pierce (eds.). 2008. Science for Ecosystem-based Management:
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Shchepetkin. 2000. Model evaluation experiments in the North Atlantic Basin: Simulations in
nonlinear terrain-following coordinates. Dynamics of Atmospheres and Oceans 32:239-281.
Hamrick, J.M. 1992. A Three-Dimensional Fluid Dynamics Computer Code: Theoretical and
Computational Aspects. Special Report 317. The College of William and Mary, Virginia
Institute of Marine Science, Gloucester Point, VA.
Hamrick, J.M. 1996. User's Manual for the Environmental Fluid Dynamics Computer Code.
Special Reports in Applied Marine Science and Ocean Oceaneering No. 331. Virginia Institute
of Marine Science, College of William and Mary, Gloucester Point, VA.
Appendix A | 67
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Kincaid, C. 2018. A Seekonk-Narragansett Bay (SNB) ROMS Model Applied to Coupled
Circulation-Ecosystem Processes: A 2010 Seasonal Study. Report to the Narragansett Bay
Commission by Chris Kinkaid, Graduate School of Oceanography, University of Rhode Island,
Narragansett.
Kremer, J.N., J.M.P. Vaudrey, D.S. Ullman, D.L. Bergondo, N. LaSota, C. Kincaid, D.L.
Codiga, and M.J. Brush. 2010. Simulating property exchange in estuarine ecosystem models at
ecologically appropriate scales. Ecological Modelling 221:1080-1088.
NBEP (Narragansett Bay Estuary Program). 2017. State of Narragansett Bay and Its Watershed.
Technical Report. Providence, RI. http://nbep.ore/the-statc-of-our-watcrshed/technicalreport/
Officer, C.B. 1980. Box models revisited. In: Estuarine and Wetland Processes. Hamilton, P.
and K.B. MacDonald (eds.), Plenum., NY, pp. 65-114.
Rashleigh, B., H. Walker, T. Gleason, M. Abdelrhman, L. Charlestra, E. Dettmann, P. Pelletier,
S. Hale, G. Thursby, N. Detenbeck, D. Keith, S. Rego, S. Robinson, J. Grear, S. Ayvazian, and
M. Mazzotta. 2015. Quantitative Models Describing Past and Current Nutrient Fluxes and
Associated Ecosystem Level Responses in the Narragansett Bay Ecosystem. EPA/600/R-
15/174. U.S. Environmental Protection Agency, Narragansett, RI.
RIDEM (Rhode Island Department of Environmental Management). 2003. The Greenwich Bay Fish
Kill - August 2003: Causes, Impacts, and Responses, http://www.dem.ri.eov/pubs/fishkill.pdf.
Thursby, G., S. Rego, and D. Keith. 2015. Data Report for Calibration of a Bio-Optical Model
for Narragansett Bay. EPA/600/R-15/211. U.S. Environmental Protection Agency,
Narragansett, RI.
Vaudrey, J. 2016. Pp. 47-64 in CHRP: Observations and Modeling of Narragansett Bay
Hypoxia and Its Response to Nutrient Management. Final project report to NOAA by the
Graduate School of Oceanography, University of Rhode Island, Narragansett, RI.
Warner, J.C., W.R. Geyer, J. A. Lerczak, 2005. Numerical modeling of an estuary: A
comprehensive skill assessment. Journal of Geophysical Research 110, C05001,
doi: 10.1029/2004JC002691.
68 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Appendix B. Data Input Values for State Variables, Atmospheric Deposition Rates,
and Model Parameters Used in the Standard Run of the WASP Model
Tables B.1-B.7 list values for user-specified kinetic and control parameters, boundary fluxes, and initial conditions for state variables
that were used for the model standard run that produced most simulation results described in this report. Also shown are some
parameters for which values are passed to WASP by the Environmental Fluid Dynamics Code through the hydrolink file. Control
parameters listed in the tables specify the algorithms to be used by the model to perform certain calculations.
The screens and subscreens referred to in table headings refer to data input screens in the WASP input file used to run the model. The
"Range" column lists ranges of values found in WASP documentation, the literature or other sources listed in the "Data Sources"
column. The parameter values used in the standard run are listed in the "Values Used" column.
Table B.l. Values listed in the Segments input screen. Only WASP parameters that we have specified or are passed to WASP by EFDC
through the hydrolink file are shown here.
Screens and Parameters
Range
Value Used
Data Sources
Segments Screen
Segment Subscreen
Volume (m3)
Segment-dependent
Values are specified by EFDC3
Velocity Multiplier (unitless)
Segment-dependent
Values are specified by EFDC"
Depth Multiplier (unitless)
Segment-dependent
Values are specified by EFDC3
Parameters Subscreen
Water Velocity (m/sec)
Segment-dependent
Values are specified by EFDC3
Temperature (°C)
Segment-dependent
Values are specified by EFDC3
Benthic Ammonia Flux (mg/m2/d)
7.78
Fields (2013)
Benthic Phosphate Flux (mg/m2/d)
2.4
Fields (2013)
Sediment Oxygen Demand (SOD) at 20°Cb (g/m2/d)
0.71-1.12
1.12
Fulweiler et al. (2010); Fields (2013)
Settling Rate for Phytoplankton Group 1 (m/d)
0.2
Kremer and Nixon (1978)
a These values are specified individually for each model segment by the EFDC model and are transferred to WASP in the hydrolink file.
b SOD temperature coefficient is given in Table B.6.
Appendix B | 69
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Table B.2. Initial values for state variables used in the standard run of the WASP model. These are specified in the
Segments input screen.
Screens and Parameters
Values Used
Data Sources
Segments Screen
Subscreen Initial Concentrations
Ammonia N (mg L"1)
(0.011 -0.058)3
Krumholz (2012). Values are averages for groups of segments aggregated according to
Krumholz station locations in model grid.
Nitrate N (mg L"1)
(0.031 -0.21 l)a
See above
Dissolved Organic N (mg L_1)
(0.034-0.064)a
See above
Inorganic Phosphate (mg L1)
(0.027 -
390.045)a
See above
Dissolved Organic Phosphorus (mg L1)
0.
No values available. Depend on model spin-up.
CBODul (mg L1)
0.
No values available. Depend on model spin-up.
Dissolved Oxygen (mg L"1)
Various values
used3
Based on calculated saturation values.
Detrital Carbon (mg C L"1)
14 X 10"3
Based on average of benthic and phytoplankton ratio (i.e. mg DW/mg C = 3)
Detrital N (mg N L"1)
34 X 10"4
USEPA (2009)
Detrital P (mg PL-1)
79 X 10"5
USEPA (2009)
Total Detritus (mg DW L_1)b
44 X 10"3
Kremer and Nixon; (1978); Vadeboncoeur et al. (2010); Abdelrhman and Cicchetti
(2012)
Phytoplankton 1 (|ug Chi a L_1)
0.3
Estimated from data on
Value used is segment-dependent.
b "DW" denotes "Dry Weight".
70 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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The following state variables were not used in this model application, so the associated kinetic constants were not used.
Alkalinity Inorganic Solids 2
Benthic Algae Inorganic Solids 3
CBOD2 Periphyton Cell Quota for N
CBOD3 Periphyton Cell Quota for P
Detrital Si pH
Dissolved Organic Si Phytoplankton Group 2
Inorganic Si Phytoplankton Group 3
Table B.3. Atmospheric deposition rates used in the standard run of the WASP model. These are specified in the Constants input screen.
Screens and Parameters
Range
Value Used
Data Sources
Constants Screen
Subscreen Globals
Waterbody Type Used for Wind Driven Reacration Rate
Control parameter (unitless)
o, 1
0
Control parameter. (0 = flowing, 1 = quiescent), Wool et al. (2006)
Atmospheric Deposition of Nitrate (mg/m2/d)
1.55 - 2.35
2
Nixon et al. (1995); Luo et al. (2002); Bowen and Valiela (2001)
Atmospheric Deposition of Ammonia (mg/m2/d)
0.38 - 0.77
0.57
Nixon et al. (1995); Luo et al. (2002); Bowen and Valiela (2001)
Atmospheric Deposition of Orthophosphate (mg/m2/d)
0.01-0.04
(total P)
0.02 (i.e. 80 %
of the total
P mean)
Yang et al. (1996); Nixon et al. (1995); Chen et al. (1985)
Atmospheric Deposition of CBOD1 (mg/m2/d)
0.64
Jurado et al. (2008)
Atmospheric Deposition of Organic N (mg/m2/d)
0.54-0.60
0.57
Nixon et al. (1995); Luo et al. (2002)
Atmospheric Deposition of Organic P (mg/m2/d)
0.01-0.04
(total P)
0.006 (as 20 %
of the total
P mean ~ 0.03)
Yang ci al. (1996); Nixon et al. (1995); Chen et al. (1985)
Appendix B | 71
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Table B.4. Kinetic parameters for inorganic nutrients used in the standard run of the WASP model. These parameters are listed in the
Constants input screen.
Screens and Parameters
Range
Value Used
Data Sources
Constants Screen
Inorganic Nutrient Kinetics Subscreen
Nitrification Rate Constant at 20°C (d1)
0
1
o
0.1
Ambrose and Wool (2010); CEAM (undated); USEPA (2009);
Wang et al. (1999)
Nitrification Temperature Coefficient
1.02-1.1
1.07
Ambrose and Wool (2010); Wang et al. (1999)
Half Saturation Constant for Nitrification Oxygen Limit
(mg 02 L"1)
0-5
2
Ambrose and Wool (2010); Wang et al. (1999)
Minimum Temperature for Nitrification Reaction (°C)
4
Berounsky and Nixon (1990)
Denitrification Rate Constant at 20°C (d1)
0
1
o
0.09
Ambrose and Wool (2010); Wang et al. (1999)
Denitrification Temperature Coefficient (unitless)
1.02-1. 1
1.04
Ambrose and Wool (2010); Wang et al. (1999)
Half Saturation Constant for Denitrification Oxygen Limit
(mg 02 L"1)
0-5
0.1
Ambrose and Wool (2010); Wang et al. (1999)
72 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Table B.5. Kinetic parameters for inorganic nutrient partitioning and for organic nutrients used in the standard run of
the WASP model. These parameters are listed in the Constants input screen.
Screens and Parameters
Range
Value Used
Data Sources
Constants Screen
Subscreen Inorganic Nutrient Partitioning
Ammonia Partition Coefficient to Water Column Solids (L kg"1)
0-200
100
Ambrose and Wool (2010)
Orthophosphate Partition Coefficient to Water Column Solids (L kg"1)
0-200
100
Ambrose and Wool (2010)
Subscreen Organic Nutrients
Detritus Dissolution Rate 20°C (d"1)
0.01-0.2
0.1
Ambrose and Wool (2010)
Temperature Correction Coefficient for Detritus Dissolution (unitless)
1.04-1.1
1.07
Ambrose and Wool (2010)
DON Mineralization Rate Constant at 20°C (d"1)
0.1
Limno-Tech (1992)
DON Mineralization Temperature Coefficient (unitless)
1.07
CEAM (undated)
DOP Mineralization Rate Constant at 20°C (d-1)
0.25
CEAM (undated)
DOP Mineralization Temperature Coefficient (unitless)
1.07
CEAM (undated)
Phytoplankton Half Saturation Constant for
Mineralization Rrate (mg phytoplankton C L"1)
0.8
Ambrose and Wool (2010)
Appendix B | 73
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Table B.6. Kinetic parameters for ultimate carbonaceous biological oxygen demand, dissolved oxygen, and light used in the
standard run of the WASP model. These parameters are listed in the Constants input screen.
Screens and Parameters
Range
Value Used
Data Sources
Constants Screen
Subscreen CBOD
CBOD (1) Decay Rate Constant at 20°C (d_1)
0.02-5.6
0.18
Wang et al. (1999)
CBOD (1) Decay Rate Temperature Coefficient (unitless)
1.02-1.15
1.05
Wang et al. (1999)
CBOD (1) Half Saturation Oxygen Limit (mg O2L"1)
0.5
Wang et al. (1999)
Fraction of Detritus Dissolution to CBOD (1) (unitless)
1
Calibration
Subscreen Dissolved Oxygen
Oxygen to Carbon Stoichiometric Ratio (0:C)
2.67
Wang et al. (1999)
Global Reaeration Rate Constant at 20°C (d_1)
1.0
Calibration; Limno-Tech (1992)
Reaeration Temperature Correction Coefficient (unitless)
1.03
Bowie et al. (1985)
SOD Temperature Correction Coefficient (unitless)
(The rate parameter for SOD at 20°C is entered in the
Parameters Subscreen described in Table B. 1.)
1.08
Fulweiler et al. (2010)
Subscreen Light
Light Option3 (1) & (2) (control parameter, unitless)
1,2
2 (i.e. calculated diel)
Control parameter - no source needed
Background Light Extinction Coefficient (m_1)
0.05-0.5
0.34
Kremer and Nixon (1978); Ambrose (2010a)
Detritus & Solids Light Extinction Multiplier (m2/g)
0.05-0.4
0.2
Ambrose (2010a)
Dissolved Organic Carbon Light Extinction Multiplier (m2/g)
0.05-0.4
0.2
Ambrose (2010a)
a Option 1 - use input diel light; Option 2 - calculate diel light from input total daily light.
74 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Table B.7. Kinetic parameters for Phytoplankton Group 1 used in the standard run of the WASP model. These parameters are listed
in the Constants input screen.
Screen and Parameters
Range
Value Used
Data Sources
Constants Screen
Subscreen Phytoplankton 1
Phytoplankton Detritus to Carbon Ratio (mg DW/mg C)a
2-5
3.5
Ambrose (2010b); Kremer (1990)
Phytoplankton Nitrogen to Carbon Ratio (mg N/mg C)
0.15-0.25
0.16
Ambrose (2010b); CEAM (undated);
Kremer (1990)
Phytoplankton Phosphorus to Carbon Ratio (mg P/mg C)
0.01-0.05
0.03
Ambrose (2010b); CEAM (undated);
Kremer (1990)
Phytoplankton Carbon to Chlorophyll Ratio (mg C/mg Chi a)
25-125
55
Ambrose (2010b); Kremer (1990);
Kremer and Nixon (1978)
Phytoplankton Maximum Growth Rate Constant at 20°C (d_1)
I
l/">
o
2.5
Ambrose (2010b)
Phytoplankton Growth Temperature Coefficient (unitless)
1.05-1.1
1.07
Ambrose (2010b)
Phytoplankton Optimum Temperature for Growth (°C)
10-27
23
Ambrose (2010b)
Phytoplankton Respiration Rate Constant at 20°C (d_1)
0.05-0.25
0.1
Ambrose (2010b)
Phytoplankton Respiration Rate Temperature Coefficient (unitless)
1.05-1.08
1.045
Ambrose (2010b)
Phytoplankton Death Rate Constant (Non-Zoo. Predation) (d_1)
0.003 -0.1
0.02
Ambrose (2010b)
Phytoplankton Zooplankton Grazing Rate Constant (d_1)
o
1
o
o
0.1
Ambrose (2010b)
Phytoplankton Half Saturation Constant for N (mg N L"1)
0.001 -0.40
0.05
Ambrose (2010b); CEAM (undated)
Phytoplankton Half Saturation Constant for P (mg P L"1)
0.001-0.08
0.001
Ambrose (2010b); CEAM (undated)
Phytoplankton Optimal Light Saturation (Langleys d"1)
100-500
250
Ambrose (2010b)
Fraction of Phytoplankton Death Recycled to Organic N (unitless)
0.85
Calibration
Fraction of Phytoplankton Death Recycled to Organic P (unitless)
0.85
Calibration
a DW = Dry weight
Appendix B | 75
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References for Appendix B
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Equations Implemented in WASP7 Eutrophication Module. A PowerPoint™ tutorial made
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Ambrose, R.B., Jr. 2010a. The WASP7 Solar Radiation Processes: Processes and Equations
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Ambrose, R.B., Jr. 2010b. The WASP7 AdvancedPhytoplankton Processes: Processes and
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76 | Seasonal and Diel Oxygen and Phytoplankton Dynamics in an Estuarine Water Quality Model
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Kremer, J.N. and S.W. Nixon. 1978. A Coastal Marine Ecosystem: Simulation and Analysis.
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Appendix B | 77
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