v>EPA
United States EPA/600/R-16/203 | February 2017
Environmental Protection , ,
Agency www.epa.gov/ord
Three-dimensional Modeling of
Water Quality and Ecology in Narragansett Bay
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5/30/09
6/29/09
7/29/09
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9/27/09
10/27/09
Office of Research and Development
National Health and Environmental Effects Research Laboratory
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EPA/600/R-16/203
February 2017
www.epa.gov/ord
Three-dimensional Modeling of
Water Quality and Ecology in Narragansett Bay
by
Mohamed A. Abdelrhman
Atlantic Ecology Division
National Health and Environmental Effects Research Laboratory
National Health and Environmental Effects Research Laboratory
Office of Research and Development
US 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.
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PREFACE
The report represents the fourth in a series of modeling activities for Narragansett Bay, RI,
created by Dr. Mohamed Abdelrhman. The other three reports in the series are:
Three-Dimensional Modeling of Hydrodynamic and Transport in Narragansett Bay.
Report # EPA/600/R-15/152. June 2015.
Modeling Total Suspended Solids (TSS) Concentrations in Narragansett Bay.
Report # EPA/600/R-16/195. August 2016.
Modeling Benthic Sediment Processes to Predict Water Quality and Ecology in
Narragansett Bay. Report # EPA/600/R-16/202. September 2016.
Unfortunately, Dr. Abdelrhman passed away before completing the final version of this fourth
report. While most of the internal reviewers' comments have been addressed, there are some
comments that required Mohamed's input. For example, some of the figure titles could not be
corrected because the computer file with the original figure could not be located. In addition,
documentation for the rationale for some of the model parameter values could not be added. An
attempt was made to accurately represent Mohamed's original work. Drs. Daniel Campbell,
Jason Grear, Henry Walker and Glen Thursby provided reviews that assisted in completing the
final version.
There are several items to which we wish to draw attention. During the period 2001 through
2009, 2009 was the year with the most extreme hypoxia observed in Narragansett Bay—and is
the year in which this report is focused. This also was a somewhat unusual year, in that it was
extremely wet in July, more so than "typical" wet years in June (e.g., 2003, 2006, 2013). The
original intent was for this effort to move into a second phase within which model validation
would involve using the current calibration model in other years, such as more typical wet years
(e.g., 2006) and dry years (e.g., 2007).
Mohamed's results in Table 7 (page 53), summarized briefly on page 59, suggest that nitrogen
load reductions from WWTPs are expected to significantly reduce, but not completely eliminate
hypoxia in upper Narragansett Bay—in the context of the unusually wet 2009 year. These results
should be of interest to water quality managers; however, because the model has not been
validated using other years, these results should be considered preliminary. Also, Mohamed's
intent was to provide a "proof-of-concept", demonstrating that the modeling framework he
developed could generate reasonable and ecologically plausible results. He originally intended to
continue refining parameter choices and the relationship between the modeling components he
integrated and the development and application of those components by others in the research
community.
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CONTENTS
DISCLAIMER ii
PREFACE iii
FIGURES vi
TABLES viii
ABBREVIATIONS AND ACRONYMS ix
ACKNOWLEDGMENTS x
1. Introduction 1
1.1. Background 1
1.2. Objectives 1
1.3. Approach 2
1.4. Water Quality Setting 2
1.5. Data 4
1.5.1. River point source loads 4
1.5.2. WWTP point source loads 5
1.5.3. Non-point source loads 5
1.5.4. Historic observations 6
1.5.5. Photosynthetic active radiation (PAR) 6
2. The Water Quality Model 27
2.1. Algae 28
2.1.1. Production 28
2.1.2. Basal metabolism 31
2.1.3. Predation 31
2.1.4. Settling 31
2.2. Organic Carbon 31
2.2.1. Particulate Organic Carbon 31
2.2.2. Dissolved organic Carbon 32
2.3. Phosphorus 33
2.3.1. Particulate Organic Phosphorus 33
2.3.2. Dissolved Organic Phosphorus 34
2.3.3. Total Phosphate 35
2.4. Nitrogen 36
2.4.1. Particulate Organic Nitrogen 36
2.4.2. Dissolved Organic Nitrogen 37
2.4.3. Ammonium Nitrogen 38
2.4.4. Nitrate Nitrogen 39
2.5. Silica 39
2.5.1. Particulate Biogenic Silica 39
2.5.2. Available Silica 40
2.6. Chemical Oxygen Demand 40
2.7. Dissolved Oxygen 41
2.8. Total Active Metal 42
2.9. Fecal Coliform Bacteria 42
3. Model Configuration 44
3.1. Numerical grid 44
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3.2. Initial and boundary conditions 44
3.3. Point-source loadings 45
3.4. Time step and run duration 45
3.5. Input files 46
4. Model Calibration and Validation 48
4.1. General behavior of the whole Bay 49
4.1.1. General behavior of DO 49
4.1.2. General behavior of Chl-a 49
4.2. Validation of dissolved oxygen 49
4.3. Validation of Chl-a 50
5. Results 59
5.1. Contemporary DO and hypoxia 59
5.2. Contemporary monthly vertical profiles of DO 59
5.3. Contemporary hourly vertical profiles of DO at station CP on day 240 60
6. Discussion 65
6.1. DO and hypoxia without direct loads from WWTPs 65
6.2. Chl-a with and without WWTPs 65
6.3 Spatial variability 65
6.4 Chlorophyll quenching and phytoplankton vertical migration 65
7. Summary and Conclusion 69
7.1. Future work 70
REFERENCES 69
Appendix A: Point-source loading from WWTPs 74
Appendix B: Dissolved oxygen concentration in riverine inflow 78
Appendix C: Values of water quality parameters used for Narragansett Bay 80
Appendix D: Validation of DO time series 87
Appendix E : Validation of DO Profiles 100
Appendix F: Validation of Chi-a time series 111
Appendix G: Validation of Chi-a profiles 118
Appendix H: Sample of model result 128
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FIGURES
Figure 1. Map of Narragansett Bay showing main point sources from WWTPs and major rivers together
with locations of observation stations for hydrodynamics 12
Figure 2. Time series of total phosphate (P04t) loads from rivers 13
Figure 3. Time series of dissolved organic nitrogen (DON) loads from rivers 13
Figure 4. Time series of NH4 loads from rivers 14
Figure 5. Time series ofN03+N02 loads from rivers 14
Figure 6. Time series of available silica (SA) loads from rivers 15
Figure 7. Time series of DO loads from rivers 15
Figure 8. Total point-source loads from rivers and riparian area to Narragansett Bay 16
Figure 9. Time series of dissolved organic phosphorus (DOP) loads from WWTPs 16
Figure 10. Time series of total phosphate (P04t) loads from WWTPs 17
Figure 11. Time series of dissolved organic nitrogen (DON) loads from WWTPs 17
Figure 12. Time series ofNFU loads from WWTPs 18
Figure 13. Time series ofN03+N02 loads from WWTPs 18
Figure 14. Time series of chemical oxygen demand (COD) loads from WWTPs 19
Figure 15. Time series of fecal coliform bacteria (FCB) loads from WWTPs 19
Figure 16. Time series of simulated benthic fluxes of phosphate at the twelve buoy locations
(see section 1.5.3) 20
Figure 17. Time series of simulated benthic fluxes of ammonium at the twelve buoy locations
(see section 1.5.3) 20
Figure 18. Time series of simulated benthic fluxes of nitrate at the twelve buoy locations
(see section 1.5.3) 21
Figure 19. Time series of simulated benthic fluxes of silica at the twelve buoy locations
(see section 1.5.3) 21
Figure 20. Time series of simulated benthic fluxes of chemical oxygen demand at the twelve buoy
locations (see section 1.5.3) 22
Figure 21. Time series of simulated benthic fluxes of sediment oxygen demand at the twelve buoy
locations (see section 1.5.3) 22
Figure 22. Time series of monthly seaward open boundary concentrations. (A) Concentration of DO and
phytoplankton carbon for all groups from NBC 2004-2010 data at station GD, (B) Concentration of
NH4, NO2+NO3, PO4L and available silica from 1972-1973 data reported by Kremer and Nixon
(1978) at their station 10 & 11 23
Figure 23. Observed Chl-a vertical profiles at some buoy locations during the summer of 2009 24
Figure 24. Observed DO vertical profiles at some buoy locations during the summer of 2009 25
Figure 25. Shortwave solar radiation incident on the earth's surface at the airport station TFG 26
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Figure 26. Schematic presentation of state variables simulated in the EFDC water quality model 43
Figure 27. The numerical grid and locations of stations and point source loads. (A) Numerical grid and
locations of water quality monitoring stations for Narragansett Bay, (B) Locations of freshwater
inflows, (C) Locations ofWWTPs discharges 47
Figure 28. Example of water quality parameters that were investigated during each calibration run 54
Figure 29 Periods and gaps of Chl-a observations at each station location. Station numbers on the vertical
axis correspond to their order in the legend 55
Figure 30. Stations and associated areas to calculate area-weighted Chl-a and DO concentrations 56
Figure 31. Comparison between observed and predicted behavior of DO for the whole Bay. (A) Observed
surface DO concentrations from NBC with profile surface values from Brown University data,
(B) Observed bottom DO concentrations from NBC, (C) comparison between weighted average
predictions and NBC observations for the whole bay 57
Figure 32. Behavior of Chl-a over the whole Bay. (A) Station records and profile surface value, (B) area
weighted Bay average, (C) comparison between predictions and observations for the whole bay 58
Figure 33. Observed surface DO concentration and predicted DO concentration at all layers exhibiting
dawn-dusk-dawn variation at station NPI during 12 -22 July 2009—layer 1 is the bottom layer 61
Figure 34. Relation between predicted and observed bottom concentrations of DO at station CP 62
Figure 35. Predicted and observed durations and occurrences of contemporary hypoxic events at station
CP in 2009 62
Figure 36. Example of contemporary monthly vertical profiles of DO at station CP during 2009—
layer 1 is the bottom layer 63
Figure 37. Example of contemporary bihourly vertical profiles of DO at station CP on day 240 in
2009—layer 1 is the bottom layer 64
Figure 38. Effect of removing direct loads from WWTPs on Chl-a concentration. (A) with WWTPs,
(B) without WWTPs. Note vertical scale difference 67
Figure 39. Daily variation of Chl-a surface concentration at station NPI during July 2009 68
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TABLES
Table 1. Freshwater flow from major rivers and riparian area 7
Table 2. WWTPs with direct discharge into Narragansett Bay 8
Table 3. Initial and boundary concentrations and loading rates of water quality variables 9
Table 4. Stations and locations used for historical water quality data collected by
NBC-RIDEM 11
Table 5. Main kinetic coefficients used for Narragansett Bay 51
Table 6. Station area weights for calculation of Bay wide overall weighted averages for DO
and Chi-a 52
Table 7. Comparison of predicted and observed chronic and acute periods of bottom DO
concentrations with and without WWTPs showing percent improvement in brackets 53
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ABBREVIATIONS AND ACRONYMS
Many water quality variables and parameters were abbreviated and mentioned with their
definitions where they appeared the first time. The following list includes the very general
acronyms.
DMR
Data Monitoring Report
EFDC
Environmental Fluid Dynamics Code
GIS
Global Information System
ICIS
Integrated Compliance Information System
NB
Narragansett Bay
NBC
Narragansett Bay Commission
NPDES
National Pollutant Discharge Elimination System
NSRDB
National Solar Radiation Data Base
PAR
Photosynthetically Active Radiation
RIDEM
Rhode Island Department of Environmental Management
ROMS
Regional Ocean Model System
SSWR
Safe and Sustainable Water Resources
URI-GSO
University of Rhode Island-Graduate School of Oceanography
USEPA
United States Environmental Protection Agency
USGS
United States Geological Survey
WASP
Water Quality Analysis Simulation Program
WWTP
Wastewater treatment plant
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ACKNOWLEDGMENTS
The author appreciates the effort by the late Dr. John Hamrick (Tetra Tech, Inc.) for providing
the executables for EFDC and the templates for water quality input files. Dr. Charlestra Lucner
(USEPA-AED-Post Doc) calculated river loads with the LOADEST model. The in-house
reviewers of this report included Drs. Dan Campbell, Jason Grear, Henry Walker, Brenda
Rashleigh, and Glen Thursby (USEPA-AED).
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1. Introduction
This report presents the methodology to apply, calibrate, and validate the built-in three-
dimensional (3-D) water quality model provided with the Environmental Fluid Dynamics Code
(EFDC). The advection and dispersion mechanisms required by the water quality and ecological
models were generated simultaneously by the hydrodynamic model. The methodology, setup,
and results from the hydrodynamic model are presented in Abdelrhman (2015). The
methodology for water quality is applied to the Narragansett Bay (NB, Bay, or system) in Rhode
Island (RI) to generate sample predictions of transport patterns for 20 water quality state
variables for the year 2009. A companion report presents sediment processes which generate
benthic fluxes of water quality loads (Abdelrhman 2016a).
The organization of this report includes six sections with relevant tables and figures at the end of
each. Section 1 presents an introduction giving the background, objectives, approach, physical
setting, and available data. Section 2 presents the water quality model with information about
the model equations. Section 3 covers model configuration for NB (numerical grid, forcing
functions, initial conditions, time step, and input files). Section 4 presents model calibration and
validation for water quality variables. Section 5 presents a sample of the results for various
constituent concentrations. Section 6 presents the summary and conclusion with a brief
discussion of the use of the water quality model results and some suggestions for future work to
improve predictions and examine effects from anticipated climate changes and global warming.
More data and results are presented in appendices A-H.
1.1. Background
The Environmental Protection Agency's (EPA's), Safe and Sustainable Water Resources
(SSWR) program seeks to provide the science to ensure that clean, adequate, and equitable
supplies of water are available to support the well-being of humans and aquatic ecosystems. The
EPA requires the development of numeric nutrient criteria (i.e., allowable concentrations of
nutrients) for estuarine and coastal waters to reduce undesirable impacts to beneficial uses.
Changes in nutrient concentrations have to be predicted in both space and time. Critical
relationships between nutrient concentrations and biological responses have to be evaluated
through the application of hydrodynamic, water quality, and ecological models.
The work presented in Abdelrhman (2015) addresses the specific needs of hydrodynamic
information required by tasks within the two SSWR projects: SSWR 2.3.A (Nutrient
management for sustainability of upland and coastal ecosystems: Building a locally applicable
management tool box for application across the US); and SSWR 6.1 (Narragansett Bay and
Watershed Sustainability Demonstration Project). The generated hydrodynamic information is
used here to predict spatial and temporal changes in the concentration of various water quality
constituents, from which impacts on the biology and ecology of the Bay also are predicted.
1.2. Objectives
The main objective of this work is to predict the transport and concentration of constituents and
properties which control the water quality and ecology of Narragansett Bay as a prototype for
future implementation to other systems.
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1.3. Approach
Some other hydrodynamic models can simulate water quality with the same spatial and temporal
resolutions used by this hydrodynamic model. However, this approach becomes prohibitively
time consuming when large regions and long simulations are needed. To overcome this
difficulty, Kremer et al. (2010) used a computational scheme that implemented the Regional
Ocean Model System (ROMS) (Haidvogel et al., 2000; Shchepetkin and McWilliams, 2005) to
generate the fine-scale hydrodynamics in NB with a spatial resolution of 50 m and a time step of
8 s (personal communication, Dave Ullman, Graduate School of Oceanography, University of
Rhode Island). Using computer simulations of dye experiments, Kremer et al. aggregated the
dense spatial and temporal information into a set of matrices to identify daily exchanges between
the coarser water quality segments throughout a full year. This approach required extensive
hydrodynamic runs to cover all the possible exchanges between the water quality segments (with
their nested hydrodynamic cells). Such runs have to be repeated with every change in the
hydrodynamic setting, e.g., to accommodate future scenarios of global warming, climate change,
sea-level rise, and river inflow.
The approach presented here attempts to structure the model's horizontal and vertical grid
resolution to resolve the hydrodynamic, water quality, and ecological needs without any spatial
or temporal aggregation. Thus, the spatial resolution should adequately resolve the
hydrodynamics; meanwhile, it should be reasonably coarse to accommodate water quality and
ecological variations. In addition to insuring the stability of the hydrodynamic model, the
temporal resolution should resolve sub-daily variations to adequately address water quality
needs, e.g., for temperature, light, oxygen, and phytoplankton growth. Two approaches were
used to predict water quality in NB. The first approach implements the EFDC's water quality
modules which are based on the US Army Corps of Engineers Model (CE-QUAL-ICM) (Cerco
and Cole, 1995). This approach was used to study the effect of nutrient load reduction and
eutrophication in Chesapeake Bay (Cerco and Cole, 1993; Cerco, 1995). This first approach is
presented in this report. The second approach uses EFDC-generated hydrodynamics with the
water quality modules in EPA's Water Quality Analysis Simulation Program (WASP). The
application of this second approach to NB is presented elsewhere (Dettmann and Charlestra,
2015). Wool et al. (2002) applied the same approach using EFDC and WASP to study
hydrodynamics and water quality in the Neuse River Estuary, NC. The following sections
include a description of the water quality model in EFDC, and its application to the NB system.
The present work provides a proof of the concept of applying EFDC to simultaneously model
hydrodynamics and water quality in NB. The process of model calibration and validation of
model results did not include any field monitoring programs, i.e., existing historical data were
used. Future work should involve more representative spatial and temporal information to refine
model predictions forNB and other systems under analysis.
1.4. Water Quality Setting
The general physical setting and forcing functions forNB were presented in Abdelrhman (2015).
The hydrodynamic model provided the spatial and temporal predictions for water temperature
and salinity. The setting for water quality is presented here.
The EFDC has built in water quality capacities that can model 22 state variables. This capability
was tested for NB and the model successfully simulated the month of January, 2009
(Abdelrhman, 2015). The full implementation of this capability required proper definition of the
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water quality model parameters, initial and boundary conditions, and loading of the following
state variables:
1) dinoflagellates (Be) (or cyanobacteria in freshwater systems)
2) diatom algae (Bd)
3) green algae (Bg)
4) refractory particulate organic carbon (RPOC)
5) labile particulate organic carbon (LPOC)
6) dissolved carbon (DOC)
7) refractory particulate organic phosphorus (RPOP)
8) labile particulate organic phosphorus (LPOP)
9) dissolved organic phosphorus (DOP)
10) total phosphate (P04t)
11) refractory particulate organic nitrogen (RPON)
12) labile particulate organic nitrogen (LPON)
13) dissolved organic nitrogen (DON)
14) ammonium nitrogen (NH4)
15) nitrate nitrogen (NO3)
16) particulate biogenic silica (SU)
17) dissolved available silica (SA)
18) chemical oxygen demand (COD)
19) dissolved oxygen (DO)
20) total active metal (TAM), not modeled here
21) fecal coliform bacteria (FCB)
22) macro algae (Malg), not modeled here
Although model theory was presented for all the above-mentioned state variables (Section 2),
this work covers the actual modeling of the first 19 state variables as well as fecal coliform
bacteria (FCB, state variable No. 21) from January to December of 2009. Total active metal and
macro algae were not modeled. The multi-group structure of the model for algae prediction was
utilized within the existing data limitations for loading and monitoring. Available data for
chlorophyll-c/ (Chi-a) is assumed to represent the integrated Chi-a in the three groups:
dinoflagellates (Be), diatom algae (Bd), and green algae (Bg)
The water quality model parameters were set according to values published in Park et al (1995).
Most of the parameters were evaluated in detail in Chapter IX of Cerco and Cole (1994) for
Chesapeake Bay. Few parameters were not available in the formulations of Cerco and Cole
(1994) and they were estimated in Park et al (1995). The published parameter values and their
ranges were used in the water quality applications of EFDC to NB. In-situ observations of
various water quality concentrations and loadings were calculated throughout the Bay during the
year 2009 (see Data, Section 1.5).
Except for the four algal groups (dinoflagellates, diatoms, greens, and macro algae-not modeled)
and fecal coliform bacteria, concentration for water quality variables were in mg L"1 and their
loadings were in kg d"1. The concentration and loading for the algal groups were in mg C L"1 and
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kg C d"1, respectively. The concentration and loading for fecal coliform bacteria were in terms of
the Most Probable Number (MPN) per 100 ml and MPN d"1, respectively. The loading
information covered both point and non-point sources as described below.
1.5. Data
Available information and historical data for the year 2009 were used to force, calibrate,
validate, and predict the hydrodynamics in NB (Abdelrhman, 2015). Due to limitations in data
availability, the data were not divided into sets for separating calibration and validation. The
hydrodynamic data described the system's boundary, bottom bathymetry, freshwater inflow,
meteorological and atmospheric parameters, water temperature, water salinity, current speed, and
tide elevation. This section covers the data for the water quality model.
Boundary values for water quality parameters had to be specified throughout the simulation
period at the four boundaries of the Bay: the landward boundary with its adjacent watershed, the
seaward (open) boundary with the RI Sound, the surface boundary with the overlying
atmosphere, and the bottom boundary with the underlying bed sediment. The landward boundary
was defined by the watershed of the NB, which is approximately 4,353 km2 (Pilson, 1985). The
watershed was composed of nine sub-watersheds with eight of them (3,855 km2) draining surface
and ground water through gauged rivers (Table 1). The ninth sub-watershed (498 km2) was un-
gauged. Loading from the upper half of this sub-watershed was divided equally between four
rivers including Pawtuxet, Taunton, Warren, and Hunt. Loads from the lower half of the riparian
area was assumed to enter the lower part Bay at three intermediate locations within the Sakonnet
River and the East and West branches (Abdelrhman 2015). The river's load per unit of its sub-
watershed area was assumed to apply to the added ungauged area. Non-point sources of nitrate,
nitrite, ammonium, total phosphate, silicate and dissolved organic nitrogen enter the Bay with the
freshwater inflow from these rivers. In addition, ten waste water treatment plants (WWTPs)
existed along the shore line and discharged their loads directly into the Bay (Fig. 1, Tables 2 and
3, Appendix A).
1.5.1. River point source loads
Time series of daily loads (kg d"1) for all 8 rivers (Table 1, Fig. 1) were calculated from the
EPA LOADEST tool (personal communications, C. Lucner, USEPA-AED, Narragansett, RI).
Data included nitrate, nitrite, ammonium nitrogen, dissolved organic nitrogen, dissolved
organic phosphorus (orthophosphate), and dissolved available silica. For EFDC application,
nitrate and nitrite were combined as nitrate nitrogen. River load of dissolved oxygen was
calculated from the known river discharge assuming DO concentration was at 70% of its
saturation level, i.e., DO load = 0.7 x F x Q x DOsat); where F is a conversion factor [ 86400
(s/d) x 1000 (L/m3) / 106 (mg/kg) = 86.4] to obtain load in kg d"1, Q is river discharge (m3 s"1),
and DOsat is the saturation concentration for DO, which is a function of water temperature and
pressure (See Appendix B). All loads were prorated to compensate for the ungauged (riparian)
and ground water flows (Table 1), i.e., adjusted river load = proration factor x (measured river
load). Flow rate from Warren/Palmer River was not gauged and it was prorated from the flow
rate in the neighboring Ten Mile River. It was assumed that 50% of the loads from the
riparian area and groundwater entered the Bay as point sources at the locations of the four
rivers: Taunton, Warren, Pawtuxet, and Hunt Rivers; and the other 50% was equally divided
between three centrally located points within the Sakonnet River, East Passage, and West
Passage (Abdelrhman, 2015). Loading from riparian areas was based on the overall average
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load per unit area from the watershed [i.e., riparian area loading rate per m2 = total loads from
all rivers (kg/d)/total watershed area served by all rivers (3,855,461,703 m2)]. Table 1 presents
the numerical locations of all rivers and riparian areas (see Section 3.3).
Table 3 indicates the state variables which had measured time series loads from the rivers
(Figs 2-7 for P04, DON, NH4, NO3+NO2, available silica, and DO, respectively). Figure 8
shows time series of the total point-source loads which enter NB from all rivers. To maintain
the kinetic reactions and interactions, loads for all other state variables were set to a default
value of 0.01 kg day"1. Total active metals and macroalgae were not modeled.
1.5.2. WWTPpoint source loads
There are eleven WWTPs which discharged directly into NB (Fig. 1, Table 2). Values of the
average daily load for each month were available from the EPA Discharge Monitoring Report
(DMR) (http://cfpub.epa. gov/dmr/). Based on the reported constituents the following
parameters were calculated:
DON = TKN - NH4 ~ TN - (NO3 + N02) - NH4
Where
TKN = total kjeldahl nitrogen
TN = total nitrogen
Total phosphorous (TP), from WWTPs was partitioned as 20% DOP and 80% P04 (personal
communication: E. Dettmann, USEPA-AED).
All loads were assumed to be active at the middle of their respective months. First and last
monthly values (i.e., for January and December) were assumed to apply uniformly to the first
and last day of these two months, respectively. Figures 9-15 present time series of the point-
source loads from all WWTPs for the major state variables (Table 3): DOP, P04, DON, NH4,
NO3+NO2, COD, andFCB, respectively.
1.5.3. Non-point source loads
Non-point source loads included direct atmospheric deposition on the water surface and
benthic flux (Table 3). Atmospheric deposition included wet and dry deposition per unit area
of the water surface. The rate of wet deposition was internally calculated by the model from
the multiplication of the observed concentrations (Table 3) by the precipitation rate which was
used for the hydrodynamic model (Abdelrhman, 2015). Concentrations in atmospheric
deposition were based on EFDC modeling application to the nearby Charles River, MA (Tetra
Tech, 2005).
The bed acted as a source/sink for many of the dissolved and suspended water quality materials
in the overlying water column. Benthic fluxes (g m"2 d"1) of P04, NH4, NO3, SA, COD, and
sediment oxygen demand (SOD) were predicted in NB using the EFDC sediment water quality
capability (Abdelrhman, 2016a) (Table 3). The benthic flux model was calibrated based on in-
situ observations of SOD (Fulweiler et al., 2010) and of P04, NH4, and SA by Kremer and
Nixon (1978). The benthic flux loads were obtained from predictions produced after more than
five consecutive runs for the full year of 2009, which nourished the various chemical reservoirs
by setting the end-of-run results as initial conditions for the succeeding run. Figures 16-21
present time series of the range of benthic fluxes at the twelve buoy locations (Fig. 1, Table 4). A
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north-south gradient in benthic fluxes was evident in the Bay which had a mean depth of 8.02 m
(including Sakonnet River, Pilson 1985) with a maximum depth of 46 m in the east passage
(Zhao et al. 2006).
1.5.4. Historic observations
Predicted values of DO and Chi-a were validated using buoy data reported by the Narragansett
Bay Commission (NBC) and the University of Rhode Island-Graduate School of Oceanography
(URI-GSO) at twelve locations (Fig. 1, Table 4). The RIDEM data were collected at 15-minute
intervals throughout the year of 2009 (http://www.dem.ri.gOv/bart/stations.htm#map). The
Narragansett Bay Commission (NBC) presented the daily average values of the RIDEM data
(http://www.narrbav.org/d proiects/buov/buovdata.htm). Buoy data were recorded at 0.5-1.0 m
above bottom and 0.5-1.0 m below water surface. Time series graphs of these data are presented
in the Model Calibration and Validation (Section 4). Station GD (Fig. 1) was used to define the
concentration time series of DO and phytoplankton carbon at the seaward open boundary (Fig.
22 A).
Concentrations of P04t, NH4, N03, and SA were calculated from data reported in Kremer and
Nixon (1978) (Fig. 22B). The seaward open boundary concentrations of DOP and DON were
calculated from data collected by URI-GSO (J. Krumholz, personal communication, E.
Dettmann, USEPA-AED).
Vertical profiles of Chi-a were collected at some buoy locations as presented in Figure 23
(Oviatt et al. submitted) (personal communication: Candace Oviatt and Heather Stoffel URI-
GSO, Narragansett, RI). The profile of average Chl-a concentrations indicates higher values
within the upper 8 m, which is consistent with observed DO profiles as presented below.
Vertical profiles of DO were collected at various bay locations by Brown University (Prell et al.
2015) (Personal communication: Warren Prell, Department of Earth, Environmental, and
Planetary Sciences, Brown University, RI). The data is represented as the Insomniacs-Daytripper
monitoring program at 77 stations in upper Narragansett Bay. Profiles of DO close to buoy
locations are presented in Figure 24 (see also Appendix E). It is worth mentioning that only
station TW showed values at depths greater than 15 m and indicated higher DO concentrations,
which may be attributed to the exchange through the open boundary with Rhode Island Sound.
The profile of average DO concentrations indicates higher values within the upper 8 m, which is
consistent with the observed average Chi-a profile (Fig. 23).
1.5.5. Photosynthetic active radiation (PAR)
Meteorological forcing was assumed to impact the Bay uniformly throughout its surface area,
which is approximately 380 km2 (including the Sakonnet River, Pilson 1985). Solar radiation is
the major meteorological force for algal growth and water quality through moderation of water
temperature and photosynthetic active radiation (PAR). Shortwave solar radiation at the water
surface was obtained from the National Solar Radiation Data Base (NSRDB) records at TFG
airport (Fig. 24). These hourly records were reduced by 80% during calibration of water
temperature in the Bay, as described in Abdelrhman (2015). The PAR was assumed to be 0.43 of
the net incident shortwave solar radiation, similar to the nearby Charles River, MA (Tetra Tech,
2005).
6
-------
Table 1. Freshwater flow from major rivers and riparian area (Abdelrhman 2015).
No.
River
Name
USGS
Station
Lat
Long
Gauged
drainage
area (m2)
Watershed
area (m2)
Calculated
% from
total area
Proration
factor for
river flow
& loads"
Numerical
Locationb
I, J
1
W oonasquatucket
01114500
41° 51' 32"
71° 29' 16"
99,196,545
132,527,601
3
1.3860
10,43
2
Pawtuxet
01116500
41° 45' 03"
71° 26' 44"
517,997,622
600,573,757
14
1.2094
11,38
3
Ten Mile
01109403
41° 49' 51"
71° 21' 06"
137,528,369
144,288,727
3
1.0992
12,45
4
Taunton + Mill +
3 mile
01108000
41° 56' 02"
70° 57'25"
1,006,987,377
1,449,758,567
33
1.4897
46,47
5
Moshassuck
01114000
41° 50' 02"
71° 24' 40"
59,828,725
59,733,689
1
1.0484
11,42
6
Blackstone
01113895
41° 53' 19"
71° 22' 55"
1,227,654,365
1,229,155,892
28
1.0512
12,53
7
Hunt
01117000
41° 38'28"
71° 26' 42"
59,336,628
64,093,655
1
1.1302
5,27
8
Warren/Palmer
N/A
N/A
N/A
N/A
175,329,816
4
1.3249
24,38
TOTAL
3,108,529,630
3,855,461,703
89
9
Riparian area
N/A
N/A
N/A
N/A
498,029,952
11
1.05
11,38;
5,27;
24,38;
46,47;
8,17;
17,17;
32,17
GRAND TOAL
4,353,491,655
100
a Proration factors are used to account for flow and loads from ungauged areas and from groundwater.
b Numerical locations I, J of river flow which is distributed equally between all eight sigma layers, K
7
-------
Table 2. WWTPs with direct discharge into Narragansett Bay. From the EPA's discharge monitoring report (DMR) pollutant
loading tool.
No
Station Name
DMR ID
Address
Latitude
Longitude
Numerical
Location"
I, J
1
Bucklin Point
RIO100072
102 Campbell Ave., E. Providence, RI 02914
41.852621°
-71.368388°
12,48
2
Fields Point
RIO100315
2 Ernest St., Providence, RI 02905
41.795111°
-71.385754°
12,40
3
E. Providence
RIO100048
1 Crest Ave., Riverside, RI 02915
41.775043°
-71.366211°
14,38
4
Warren
RIO100056
427 Water St., Warren, RI 02917
41.726319°
-71.285708°
24,34
5
Bristol
RIO100005
2 Plant Ave. and Wood St., Bristol, RI 02809
41.660024°
-71.268343°
26,28
6
Fall River
MAO 1003 82
1979 Bay St., Fall River, MA 02724
41.675799°
-71.195276°
36,30
7
Newport
RIO100293
250 J.T. Connell Highway, Newport, RI 02840
41.517896°
-71.330495°
18,14
8
Jamestown
RIO100366
44 Southwest Ave., Jamestown, RI 02835
41.509541°
-71.358562°
14,13
9
Quonset Point
RIO100404
95 Cripe St., N. Kingstown, RI 02807
41.588309°
-71.406176°
9,21
10
E. Greenwich
RIO100030
21 Crompton Ave., E. Greenwich, RI 02818
41.658321°
-71.447040°
3,27
11
Somerset
MAO 100676
116 Walker Street, Somerset, MA 02725
41.71816°
-71.16699°
40,33
a Numerical locations I, J are from Abdelrhman (2015). WWTP flows are distributed equally between all eight sigma layers, K.
8
-------
Table 3. Initial and boundary concentrations and loading rates of water quality variables.
Water quality state variable
Name
Initial3
Cone,
(mg L1)
Seawardb
Cone,
(mg L1)
Dryc
Dep.
(g m2 d"1)
Wetc
Dep.
(mg L1)
Benthicf'g
Flux
(g m2 d"1)
Riversb
(kg d"1)
VYWIT1'
(kg d-1)
1) dinoflagellates
Be
0.000148s
TSi
0.0000
0.000
NA
0.000
0.000
2) diatom algae
Bd
0.001571®
TSi
0.0000
0.000
NA
0.000
0.000
3) green algae
Bg
0.015930s
TSi
0.0000
0.000
NA
0.000
0.000
4) refractory particulate organic carbon
RPOC
0.030400
0.01
0.000387
0.325
NA
0.000
0.000
5) labile particulate organic carbon
LOPC
0.023300
0.01
0.000387
0.325
NA
0.000
0.000
6) dissolved carbon
DOC
0.100000
0.01
0.000773
0.65
NA
0.000
0.000
7) refractory particulate organic phosphorus
RPOP
0.000556
0.01
0.00001d
0.000
NA
0.000
0.000
8) labile particulate organic phosphorus
LPOP
0.000499
0.01
0.00001d
0.000
NA
0.000
0.000
9) dissolved organic phosphorus
DOP
0.009750
ts7
0.00001d
0.045
NA
0.000
ts2
10) total phosphate
P04t
0.192000
TSe
0.00001d
0.016
BM
ts3
ts2
11) refractory part, organic nitrogen
RPON
0.003660
0.01
0.0002d
0.000
NA
0.000
0.000
12) labile part, organic nitrogen
LPON
0.004160
0.01
0.0002d
0.000
NA
0.000
0.000
13) dissolved organic nitrogen
DON
0.195000
ts7
0.0002d
0.648
NA
ts3
ts2
14) ammonium nitrogen
NH4
0.304000
TSe
0.00057d
0.263
BM
ts3
ts2
15) nitrate nitrogen
N03
0.519000
TS6
0.002d
0.855
BM
ts3
ts2
9
-------
Water quality state variable
Name
Initial3
Cone,
(mg L"1)
Seawardb
Cone,
(mg L"1)
Dryc
Dep.
(g m2 d"1)
Wetc
Dep.
(mg L"1)
Benthicf'g
Flux
(g m2 d"1)
Riversb
(kg d"1)
WWTPb
(kg d"1)
16) particulate biogenic silica
SU
0.000768
0.01
0.0000
0.000
NA
0.000
0.000
17) dissolved available silica
SA
1.350000
TSe
0.000247
0.000
BM
ts3
0.000
18) chemical oxygen demand
COD
0.066300
0.01
0.00064d
0.000
BM
0.000
ts2
19) dissolved oxygen
DO
11.10000
TSi
0.0000
7.000
BM
(SOD)
TSs
0.000
21) fecal coliform bacteria
FCB
1.22E+07
1.0e+07
0.0
0.0
NA
0.000
ts4
a From model predictions at station CP at the end of the one year simulation (i.e., at 24:00 PM on 31 December, 2009)
b TS = Time Series: TSi from NBC observations at station GD using daily-averages during 7years (2004-2010)
TS2 from ICIS-NPDES database, personal communication (Dettmann, USEPA, AED)
TS3 from LOADEST model, personal communication (Lucner, USEPS, AED)
TS4 from DMR tool using ICIS-NPDES database
TS5 calculated
TSe from Kremer and Nixon (1978) data at their station 10&11 for 1972-1973
TS7 from 2009 data collected by Jason Krumholz (URI-GSO), personal communication (Lucner, USEPS, AED)
c From EFDC application to the nearby Charles River, MA (Tetra Tech, 2005), unless otherwise specified.
d From Nixon et al. (1995) after applying equal partitioning between refractory, labile, and dissolved phases.
6 Concentration of all algae groups are in mg C L"1
f BM = Benthic Model predictions
g NA = not applicable
10
-------
Table 4. Stations and locations used for historical water quality data collected by NBC-RIDEM (Abdelrhman 2015).
Sensor
Model Total
Numerical
Station Name
Abbreviation
Latitude
(North)
Longitude
(West)
Height (m)
From MSL
Water
Depth (m)
Location
I,J,Kd
Conimicut Point (CP)
41.7138°
71.3438°
-0.80 (topb)
-8.60 (botb)
-12.3
17,33,6
17,33,1
Greenwich Bay (GB)
41.684833°
71.44603°
N/A (topb)
-2.70 (botb)
-2.7
3,30,4
3,30,1
T-Wharf (TW)
41.57885°
71.32145°
-0.80 (topb)
-6.10 (botb)
-12.0
19,19,8
19,19,4
Phillipsdale (PD)
41.84175°
71.3722°
-0.54 (topb)
-1.86 (botb)
-5.4
12,46,6
12,46,2
Bullock Reach (BR)
41.740567°
71.374667°
-0.85 (topb)
-7.00 (botb)
-7.5
13,36,6
13,36,1
Sally Rock (SR)
41.675283°
71.4240167°
-1.14 (topb)
-4.37 (botb)
-3.4
6,29,5
6,29,1
N. Prudence Island (NPI)
41.6704°
71.354717°
-1.14 (topb)
-12.76 (botb)
-11.2
15,29,6
15,29,1
Poppasquash Point (PP)
41.647433°
71.317467°
-0.69 (topb)
-8.08 (botb)
-9.0
20,27,7
20,27,2
Mount View (MV)
41.638467°
71.383683°
-0.86 (topb)
-7.00 (botb)
-7.1
11,26,7
11,26,1
Quonset Point (QP1)
41.587617°
71.380033°
-0.85 (topb)
-7.63 (botb)
-8.3
12,21,7
12,21,1
Mount Hope Bay (MH)
41.681333°
71.215217°
-0.78 (topb)
-5.58
-6.0
33,30,6
33,30,1
URI-GSO (GD)
41.49183°
71.4188°
-1.5 -2.5
-8.0
6,11,6
11
-------
-71°20' -71°10'
I I
Providence 2*
Warren/
Palmer River
y Apt #'11 Fall River
FR2 A- FR1
Mt. Hope
NPI
MH
40'"
PP
Point
TW A
Aquidneck
Island
( XD
C c
O cc
O w ,
7#
41°
30'
Km
Figure 1. Map of Narragansett Bay showing main point sources from WWTPs and
rivers together with locations of observation stations for hydrodynamics.
12
-------
1
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009 3/13/2010
Date
Blackstone
Ten Mile
1000
P04t from rivers
Moshassuck Taunton
¦ Pawtuxet Hunt
Woonasquatucket
Palmer
Figure 2. Time series of total phosphate (P04t) loads from rivers.
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009 3/13/2010
Date
<:»¦";
Blackstone
Ten Mile
10000
DON from rivers
Moshassuck Taunton
Pawtuxet Hunt
Woonasquatucket
Palmer
Figure 3. Time series of dissolved organic nitrogen (DON) loads from rivers.
13
-------
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009 3/13/2010
Date
1000
Blackstone
Ten Mile
10000
NH4 from rivers
Moshassuck Taunton
Pawtuxet Hunt
Woonasquatucket
¦ Palmer
Figure 4. Time series of NHU loads from rivers.
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009 3/13/2010
Date
] 'j'jo
Blackstone
Ten Mile
10000
N03+N02 from rivers
Moshassuck Taunton
Pawtuxet Hunt
Woonasquatucket
Palmer
Figure 5. Time series of NO3+NO2 loads from rivers.
14
-------
10000
1000
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009 3/13/2010
Date
¦ Blackstone
Ten Mile
100000
SA from rivers
Moshassuck 'Taunton
Pawtuxet Hunt
Woonasquatucket
¦ Palmer
Figure 6. Time series of available silica (SA) loads from rivers.
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009 3/13/2010
Date
10000
10 !¦;
Blackstone
Ten Mile
100000
DO from rivers
Moshassuck Taunton
Pawtuxet Hunt
Woonasquatucket
Palmer
Figure 7. Time series of DO loads from rivers.
15
-------
1nnnnnn
Total Loads from Rivers & Riparian Area
P04t DON NH4 N03+N02 SA DO
XLAJLAJUVJ
1nnnnn
VA/l ILll ,
xuuuuu
~b
OD
1 nnnn
¦ . xuuuu
"D
ro
o
_l
i nnn
1UUU
1 m
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009 3/13/2010
Date
Figure 8. Total point-source loads from rivers and riparian area to Narragansett Bay.
DOP from WWTPs
100.0
zr 10.0
¦b
oo
-a
ro
o
1.0
0.1
-Bristol
¦ Fall R.
- Warren
¦ Bucklin Pt. —•— E, Greenwich —X—E. Providence
Fields Pt. ~ Jamestown —X—QuonsetPt.
¦Newport —*—Somerset
~—•
X—M
i £
6 *
CO
o
rH
O
o
o
o
T—I
oT r\i
<. <
(M tH
Date
Figure 9. Time series of dissolved organic phosphorus (DOP) loads from WWTPs.
16
-------
P04t from WWTPs
•Bristol
Fall R.
•Warren
• Bucklin Pt.
Fields Pt.
• Newport
E. Greenwich
-Jamestown
-Somerset
• E. Providence
•Quonset Pt.
1000
100
so
HI
re
o
10
00
cn
cn
cn
cn
cn
cn
cn
cn
cn
cn
cn
O
o
o
O
O
o
o
o
O
o
o
o
o
o
rH
00
r--
00
r--
r--
to
>
ro*
ro
fN
rH
T—1
rH
rH
rH
Date
Figure 10. Time series of total phosphate (P04t) loads from WWTPs.
DON from WWTPs
•Bristol
Fall R.
•Warren
• Bucklin Pt. —¦— E. Greenwich —x— E. Providence
Fields Pt. ~ Jamestown —x—QuonsetPt.
•Newport —*—Somerset
10000
1000
¦o
ftD
100
re
o
10
00
o
cn
o
cn
O
cn
o
cn
o
cn
o
cn
o
cn
o
ro
ro
-------
NH4 from WWTPs
Figure 12. Time series of NH4 loads from WWTPs.
•Bristol ¦BucklinPt. —¦—E.Greenwich—x—E.Providence
- Fall R. Fields Pt. ~ Jamestown —X—QuonsetPt.
• Warren Newport —*— Somerset
10000.0
1000,0
100.0
Date
N03+N02 from WWTPs
—•—Bristol BucklinPt. M E. Greenwich—*—E.Providence
—1—Fall R. Fields Pt. ~ Jamestown —x—QuonsetPt.
—*—Warren Newport —s*—Somerset
10000.0
00
(J)
cn
cn
cn
cn
cn
cn
cn
cn
00
r^
h-
<£>
t,D
LD
>
rn
rn
rsl
r-1
t—1
rH
rH
t—1
rH
rH
rH
rH
rH
rH
rH
rH
rH
-¦>
\
-S.
*->
\
-s.
-v
-N,
\
rsl
n—1
Csl
m
U-)
U3
r--
00
cn
O
rH
rsl
rH
T—1
rH
rH
rH
Date
Figure 13. Time series of NO3+NO2 loads from WWTPs.
18
-------
* Bristol
¦ Fall R,
-Warren
10000
1000
"O
HD
TJ
ra
o
100
10
00
o
oo*
rH
fN
-------
Phosphate Flux
0.020
0.018
0.016
" 0.014
0.012
E 0.010
^ 0.008
^ 0.006
0.004
0.002
0.000
00
o
en
o
o
Figure 16. Time series of simulated benthic fluxes of phosphate at the twelve buoy locations
(see section 1.5.3).
Amonium Flux
00
O)
O)
0si
o
O
O
o
00
r*»
(£>
CO
T—1
rH
rH
rH
rH
*->
rH
rH
O
rH
rsl
t-H
rH
rH
rH
Figure 17. Time series of simulated benthic fluxes of ammonium at the twelve buoy
locations (see section 1.5.3).
20
-------
Nitrate F ux
-o.oi
-0.01
-0.02
Figure 18. Time series of simulated benthic fluxes of nitrate at the twelve buoy locations
(see section 1.5.3).
Silica Flux
0.90
0.80
_ °-70
0.60
CN
£ 0.50
3 0.40
J 0.30
Ll_
0.20
0.10
0.00
ii m
OOOOOOOOOOOOOrH
UD 00
id Ln
ro m cnj
-------
fllC
COD Flux
0.20
" 0.15
CN
°-10
CtQ
1 0-05
0.00
-0.05
c
c
c
T
r
r
Jd
J
iJ
II
i
I
k
D
H
nI
H
H
o en en c
D o o c
^ \
o o
H rH rH r
\l rH ^ c
Date
H
3
9/14/09
10/14/09
11/13/09
12/13/09
1 /1 1 /1 fl
Figure 20. Time series of simulated benthic fluxes of chemical oxygen demand at the twelve
buoy locations (see section 1.5.3).
Figure 21. Time series of simulated benthic fluxes of sediment oxygen demand at the twelve
buoy locations (see section 1.5.3).
22
-------
Seaward Open Boundary Concentration
DO Phytoplankton
30 60 90 120 150 180 210 240 270 300 330 360
Time (day)
0.6
0.5
0.4
0.3
0.2
0.1
0
390
Seaward Open Boundary Concentration
-NH4
• P04
• N02+N03
0.50
0.40 -
0.30
00
E,
s
CL
X
z
o
c
o
¦*S 0.20
0.10 -
0.00
4.0 -j
Month
(B)
Figure 22. Time series of monthly seaward open boundary concentrations. (A)
Concentration of DO and phytoplankton carbon for all groups from NBC 2004-2010 data
at station GD, (B) Concentration of NH-t, NO2+NO3, PO-it, and available silica from 1972-
1973 data reported by Kreiner and Nixon (1978) at their station 10 & 11.
23
-------
35
2 4 6 8 10 12 14
Depth (m)
BR6/1
CP6/1
NPI6/1
BR6/10
CP6/10
NPI6/10
BR6/25
CP6/25
NPI6/25
BR7/10
CP7/10
NPI7/10
BR7/22
CP7/22
NPI7/22
BR8/3
CP8/3
NPI8/3
BR8/20
CP8/20
NPI8/20
MV6/9
QP16/9
GD6/9
MV6/24
QP16/24
GD6/24
MV7/13
QP17/13
GD7/13
MV7/20
QP7/20
GD7/20
MV8/5
QP8/5
GD8/5
MV8/24
QP18/24
GD8/24
— Ave rage
16
Figure 23. Observed Chl-« vertical profiles at some buoy locations during the summer of
2009.
24
-------
16
MV6/18
MV7/15
MV7/23
MV8/4
MV8/13
MV9/1
QP1G/18
QP17/15
QP17/23
QP18/4
QP18/13
QP19/1
CP6/18
CP7/15
CP7/23
CP8/4
CP8/13
CP9/1
NPI6/18
NPI7/15
NPI7/23
NPI8/4
NPIS/13
NPI9/1
PD6/18
PD7/15
P07/23
PD8/4
PD8/13
— PD9/1
SRG/18
SR7/15
SR7/23
SR8/4
SR8/13
SR9/1
GB6/18
GB7/15
GB7/23
GB8/4
GB9/1
TW6/18
TW7/15
TW7/23
TW8/4
TW8/13
TW9/1
PP6/18
PP7/15
PP7/23
PP8/4
PP8/13
— PP9/1
BR6/18
BR7/15
BR7/23
BR8/4
BR8/13
BR9/1
Average
2 4 6 8 10 12 14 16 18 20 22 24
Depth (m)
Figure 24. Observed DO vertical profiles at some buoy locations during the summer
of 2009.
25
-------
Solar Radiation
-NSRDB
80% NSRDB
1200
1000
:> 800
C
-§ 600
¦o
ns
OS
o
1/1
400
200
0
00
r-
00
cn
O*
rH
(N*
rH
T—1
T—1
rH
rH
Date
Figure 25. Shortwave solar radiation incident on the earth's surface at the airport
station TFG.
26
-------
2. The Water Quality Model
Hamrick (1992, 1996) developed the 3-D hydrodynamic and water quality model, EFDC. This
model was used in many applications and was accepted and adopted by the USEPA. The EFDC
had built in water quality capacities that can model 22 state variables (Fig. 26). The full
implementation of this capability required proper definition of the water quality model
parameters, initial and boundary conditions, and loading of the 22 variables.
The solution techniques for the water quality equations in EFDC were presented in Tetra Tech
(2005). Boundary conditions included material loads from rivers, WWTPs, atmosphere, open
boundary, and bed. Climatological conditions which impacted sink and source processes of
chemical and biological constituents were considered.
The basic theory of the water quality used in the EFDC model was presented in Tetra Tech, Inc.
(2005), which indicated that the kinetic processes included in the EFDC water quality model
were from the CE-QUAL-ICM (Cerco and Cole 1994) and that the detailed descriptions existed
in a report by Park et al. (1995) as presented, with slight modifications, in the following
description.
The generic transport equation can be put in the following simple form
dC d(uC) d(ipC) d(wC) d / dC\ d / dC\ d / dC\
m+~dT + ~dT + ~dr- to(^to) + ^r^) + airza?) + 5c (1)
Where C is the concentration of the water quality variable; Kx, Ky, Kz are the turbulent
diffusivities in the x, y, and z directions; and Sc represents the internal and external sinks and
sources per unit volume. The kinetic sink-source term is decoupled from the rest of the physical
transport terms for advection and diffusion and the decoupled equations are represented by
dC d(uC) d(vC) d(wC) d / dC\ d / dC\ d / dC\
dFP+~dr+~dT+~dr- ^\K'd^)+ d^\K^)+d^\Kzw+Scp (2a)
d C
— = Sck = K.C + R (2b)
oiK
with
dC _ dC dC
dt dtp + dtK ^C^
Where tp and tK represent the physical and kinetic time steps (which may differ), respectively;
Sep and Sck represent the physical and kinetic sinks and sources, respectively; K is a kinetic rate
(per time) for one of the water quality variables; and R is a sink-source term (mass per volume
per time) for that variable. Based on the segment area and water depth, its proper incremental
volume is introduced into the above equations. The kinetic equations for the conservation of
mass for 22 water quality state variables are presented in this section. Ranges of the kinetic rate
coefficients and their units are presented in the following definitions. The default values of these
parameters are presented in Park et al. (1995) (their Tables 3-1 to 3-7) and are reproduced in the
27
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main input file for the water quality model (WQ3DWC.INP). The values used for NB are
presented in Appendix D. Summary of the main kinetic coefficients used for NB are shown in
Table 5.
2.1. Algae
The modeled algae groups include dinoflagellates, c; diatoms, d; green algae, g , and macro
algae, m; denoted by subscript x; where x refers to c, d, g, and m. Macro algae is not currently
modeled in this work. The general equation includes five terms representing growth
(production), basal metabolism, predation, settling, and external loads.
Bx d WBX
ft = {Px- BMX - PRX)BX + — (VKSX. Bx) + (3)
Bx = algal biomass of group x(gC m"3)
t = time (day)
Px = production rate of group x (day"1)
BMX = basal metabolism rate of group x (day"1)
PRX = predation rate of group x (day"1)
WSX = settling velocity of group x (m day"1)
WBX = external loads of group x(gC day"1)
V = cell volume (m3)
2.1.1. Production
For diatoms and green algae (x = d,g)
Px = PMx.f1(N).f20).f3(T) (4)
For cyanobacteria in freshwater systems, otherwise for dinoflagellates (x = c)
pc = PMc.f1mf2oif3(nf4(.s) (5)
For macroalgae (x = m)
Pm = PMm.fi{N).f2{I).f2{T).fs{V).f6{D) (6)
PMX = maximum growth rate under optimal condition for group x (day"1)
PMC = maximum growth rate under optimal condition for dinoflagellates (day"1)
PMm = maximum growth rate under optimal condition for macro algae (day"1)
fi(N) = effect of nutrient concentration (0 < fi < 1)
f2(I) = effect of light intensity (0 < f2 < 1)
f3(T) = effect of temperature (0 < f? < 1)
fi(S) = effect of salinity on freshwater cyanobacteria (0 < U < 1), for dinoflagellates f4 = 1
f>(V) = velocity limitation factor for microalgae (0 < fs < 1)
28
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fe(D) = density-dependent growth rate reduction factor for macroalgae (0 < U <
2.1.1.1. Effect of nutrients
( NH4 + N03 POM \
fiCN) = minimum , (7)
m J \KHNX +NH4 +N03 KHPX +POM/ ^ J
For diatoms
NH4 + N03 POM SAd
/i(iV) = minimum
-------
Keb = background light extinction (m"1)
Keiss = light extinction Coefficient for TSS (m"1 per g m"3)
TSS = total suspended solids concentration (g m"3) provided by the hydrodynamic model
(Abdelrhman 2016b)
Kecw = light extinction Coefficient for Chi-a (m"1 per mg Chi m"3)
CChlx= Carbon to Chi ratio in group x(gC per mg Chi)
0s)x = maximum {Oo)avg-e~Kess^D°pt">x, Os)min} (13)
(Dopt)x = depth of maximum growth for group x (m)
(Io)avg = adjusted surface light intensity (Langley day"1)
Oo)avg = CIa-I0 + Clb-h + CIc.I2 (14)
Ii = daily light intensity 1 day preceding model day (Langley day"1)
h = daily light intensity 2 days preceding model day (Langley day"1)
CIa, Clb, CIc =weighting factors for Io, Ii, h, respectively, (CIa+CIb+CIc=l)
2.1.1.3. Effect of temperature
f3(T) = exp(-KTGlx[T - TM1X]2); T < TM1X (15)
= 1; TM1X < T < TM2X
= exp(-KTG2x[T - TM2X]2); T > TM2X
T = temperature (°C)
TMX = optimal temperature for growth of group x (°C).
TMlx, TM2X = Lower and upper bounds of the optimal range are specified by the user (Table
5, and Appendix D-Card No. CI 1). Maximum growth rate, PMX, persists within the specified
range.
KTGlx = effect of temperature below TMX on growth of group x (°C"2)
KTG2X = effect of temperature above TMX on growth of group x (°C"2)
2.1.1.4. Effect of salinity on growth offreshwater cyanobacteria
STOX2
~ STOX2 + S2 (16)
STOX = salinity at which growth of cyanobacteria is halved (ppt)
S = salinity in water column (ppt) (provided by the hydrodynamic model)
30
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Note: To eliminate the effect of salinity, STOX can be set to a very large value compared to S
(e.g., 105) which produces f4(S) -1.0 and Equations (4) and (5) will be similar.
2.1.2. Basal metabolism
BMX = BMRX. exp(KTBx[T - TRX]) (17)
BMX = basal metabolism rate for group x (day"1)
BMRX = basal metabolism rate at reference temperature for group x (day"1)
KTBX = effect of temperature on metabolism for group x ("C"1)
TRX = reference temperature for basal metabolism for group x (°C)
2.1.3. Predation
PRX = PRRX. exp(KTPx[T - TRX]) (18)
PRX = predation rate for group x (day"1)
PRRX = predation rate at reference temperature for group x (day"1)
KTPX = effect of temperature on predation for group x ("C"1)
2.1.4. Settling
Settling velocities for group x is specified by user.
2.2. Organic Carbon
The modeled organic carbon groups include labile particulate, refractory particulate, and
dissolved.
2.2.1. Particulate Organic Carbon
The general equation includes four terms representing algal predation, dissolution to dissolved
organic carbon, settling, and external loads.
dRPOC ^ d WRPOC
—g^= FCRPx.PRx.Bx-KRPOC.RPOC + — (WSRP.RPOC)+—r- (19)
x=c,d,g,m
dLPOC sr d WLPOC
= 2, FCLPx.PRx.Bx - Klpoc.LPOC + — {WSip.LPOC) + v (20)
dt
x=c,d,g,m
POC = Particulate organic carbon
RPOC = concentration of refractory POC (g C m"3)
LPOC = concentration of labile POC (g C m"3)
FCRPx = fraction of predated carbon produced as RPOC for group x
FCLPx = fraction of predated carbon produced as LPOC for group x
31
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Krpoc = dissolution rate of RPOC (day"1)
Klpoc = dissolution rate of LPOC (day"1)
WSrp = settling velocity of refractory particulate organic matter (m day"1)
WSlp = settling velocity of labile particulate organic matter (m day"1)
WRPOC = external load of RPOC (g C day"1)
WLPOC = external load of LPOC (g C day"1)
2.2.2. Dissolved organic Carbon
The general equation includes five terms representing algal excretion (exudation) and predation,
dissolution from refractory and labile particulate organic carbon, heterotrophic respiration
(decomposition), denitrification, and external loads.
dDOC /f KHR*
(\ KHKx \
= y i^FCDx + (1 - FCDX) RHR +XDQ . BMX + FCDPX. PRX J . Bx
dt Z-i x
x=c,d,g,m
WDOC
+ (Krpoc. RPOC + Klpoc. LPOC) — Khr.DOC — Denit. DOC H —— (21)
DOC = concentration of dissolved organic carbon (g C m"3)
FCDX = fraction of basal metabolism exuded at infinite DO for group x
KHRx = half saturation constant of DO for dissolved organic carbon exertion for group x
(g 02 m"3)
DO = dissolved oxygen concentration (g O2 m"3)
FCDP = fraction of predated carbon produced as dissolved organic carbon
Khr = hetrotrophic respiration rate of dissolved organic carbon (day"1)
Denit = denitrification rate (day"1)
WDOC = external loads of dissolved organic carbon (g C day"1)
DO
Khr ~ KHORdo + DO Kdoc (22)
KHORdo = oxic respiration half saturation constant for DO (g O2 m"3)
Kdoc = heterotrophic respiration rate of DOC at infinite DO concentration (day"1)
I
Kropc — I Krc + KRCaig L Bx J exp(KTHDR[T — TRhdr]) (23)
x=c,d,g f
KlOPC = ( KlC + KLCalg
Bx j exp(KTHDR[T — TRhdr]) (24)
x=c,d,g f
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KdOC ~ ( KDc + ^DCalg I Bx J exp(KTMNL(T -TR
MNL )) (25)
\ x=c,d,g f
Krc = minimum dissolution rate of refractory POC (day"1)
Klc = minimum dissolution rate of labile POC (day"1)
Kdc = minimum respiration rate of DOC (day"1)
KRCaig = constant relating dissolution of refractory POC to algal biomass (day"1 per g C m"3)
KLCaig = constant that relates dissolution of labile POC to algal biomass (day"1 per g C m"3)
Kocaig = constant that relates respiration to algal biomass (day"1 per g C m"3)
KThdr = effect of temperature on hydrolysis of POC ("C"1)
TRhdr = reference temperature for hydrolysis of POC (°C)
KTmnl = effect of temperature on mineratization of DOC ("C"1)
TRmnl = reference temperature for mineralization of DOC (°C)
/ KRORdo \ ( N03
Don if
/ KRUH-dq \ ( NUo \
'«»« - WPO+00) {kHDNk + N03) AAN0X K™ (26)
KRORdo = denitrification half-saturation constant for dissolved oxygen (g O2 m"3)
KHDNn = denitrification half-saturation constant for nitrate (g N m"3)
AANOX = ration of denitrification rate of oxic dissolved organic carbon respiration rate
2.3. Phosphorus
The modeled phosphorus groups include refractory organic particulate phosphorus, labile
organic particulate phosphorus, dissolved organic phosphorus, and inorganic total phosphate.
2.3.1. Particulate Organic Phosphorus
The general equation includes four terms representing algae basal metabolism and predation,
dissolution to dissolved organic phosphorus, settling, and external loads.
dRPOP ^ d
= 2, (FPRx¦ BMX + FPRPX. PRX)APC. Bx - Krpop.RPOP + — (WSrp.RPOP)
x=c,d,g,m
WRPOP
+—r- (27)
dLPOP
= ^ (FPLX.BMX + FPLPX.PRX)APC.BX - Klpop.LPOP + ^(WSlp.LPOP)
dt
x=c,d,g,m
WLPOP
+ —— (28)
RPOP = concentration of refractory particulate organic phosphorus (g P m" )
33
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LPOP = concentration of labile particulate organic phosphorus (g P m"3)
FPRx = fraction of metabolized phosphorus by algal group x produced as refractory
particulate phosphorus
FPLx = fraction of metabolized phosphorus by algal group x produced as labile particulate
phosphorus
FPRPx = fraction of predated phosphorus produced as refractory particulate phosphorus
FPLPx = fraction of predated phosphorus produced as labile particulate phosphorus
APC = mean algal phosphorus to carbon ratio for all algal groups (g P per g C)
Krpop = hydrolysis rate of refractory particulate organic phosphorus (day"1)
Klpop = hydrolysis rate of labile particulate organic phosphorus (day"1)
WRPOP = external loads of refractory particulate organic phosphorus (g P day"1)
WLPOP = external loads of labile particulate organic phosphorus (g P day"1)
APC = CPlprm + CP2prm exp(—CP3prm P04d) (29)
CP1 prm minimum carbon-to-phosphorus ratio (g C per g P)
CP2prm = difference between minimum and maximum carbon-to-phosphorus ratio
(g C per g P)
CP3prm = effect of dissolved phosphate concentration on carbon-to-phosphorus ratio
(per g P m"3)
2.3.2. Dissolved Organic Phosphorus
The general equation includes four terms representing algae basal metabolism and predation,
dissolution from refractory and labile particulate organic phosphorus, mineralization to
phosphate phosphorus, and external loads.
dDOP V"1
= 2, (FPDx¦BM* + FPDP¦ PRx~) APC¦B* + (Krpop.RPOP + KLP0P. LPOP)
x=c,d,g,m
WDOP
~ Kdop.DOP H —— (30)
DOP = concentration of dissolved organic phosphorus (g P m"3)
FPDx = fraction of metabolized phosphorus by algal group x produced as dissolved organic
phosphorus
FPDP = fraction of predated phosphorus produced as dissolved organic phosphorus
Kdop =mineralization rate of dissolved organic phosphorus (day"1)
WDOP = external loads of dissolved organic phosphorus (g P day"1)
34
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2.3.3. Total Phosphate
The general equation includes five terms representing algae basal metabolism, predation, and
uptake; mineralization from dissolved organic phosphorus; settling of sorbed phosphate;
sediment-water exchange of dissolved phosphate; and external loads.
dP04t ST1 d
—— = 2^ (FPIx-BMx + FPIP. PRX - PX)APC. Bx + Kdop .DOP + — (VKST55. P04p)
x=c,d,g,m
BFP04d WPOAt
<3r>
P04t = total phosphate phosphorus (g P m"3) = P04d+P04p
P04d = dissolved phosphate phosphorus (g P m"3)
P04p = particulate (sorbed) phosphate phosphorus (g P m"3)
FPIX = fraction of metabolized phosphorus by algal group x produced as inorganic
phosphorus
FPIP = fraction of predated phosphorus produced as inorganic phosphorus
WStss = settling velocity of suspended solids (m day"1) (Abdelrhman 2016b)
BFP04d = sediment-water exchange flux of phosphorus (g P m"2 day"1) with bottom layer
WP04t = external loads of total phosphorus (g P day"1)
KHP
Krpop — Krp +
KHP+P04d
KHP
Klpop — KLp +
KHP + POM
KHP
Kdop — ^dp +
KRPalg
Bx I exp(KTHDR(T -TR
HDR )) (32)
x=c,d,g f
KLPalg
Bx J exp(KTHDR(T -TR
HDR )) (33)
x=c,d,g f
KDPalg I Bx I exp(KTMNL(T -TR
MNL )) (34)
KHP+P04d
x=c,d,g
Krp = minimum hydrolysis rate of refractory particulate organic phosphorus (day"1)
Klp = minimum hydrolysis rate of labile particulate organic phosphorus (day"1)
Kdp = minimum mineralization rate of dissolved organic phosphorus (day"1)
KRPalg = constant that relates hydrolysis of refractory organic phosphorus to algal biomass
(day"1 per g C m"3)
KLPaig = constant that relates dissolution of labile organic phosphorus to algal biomass
(day"1 per g C m"3)
KDPaig = constant that relates mineralization to algal biomass (day"1 per g C m"3)
35
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KHP = mean half-saturation constant for algal phosphorus uptake (g P m )
KPo4V.TSS
P04p=—£22——-P(Mt (35)
-L "r I*P04p' '
P04d=- ^P04t (36)
1 + KP04p. TSS
Kpo4P = empirical coefficient relating phosphate sorption to total suspended solids (per g m"3)
P04p 1
Kpo4p = POM TSS ^
2.4. Nitrogen
The modeled nitrogen groups include refractory organic particulate nitrogen, labile organic
particulate nitrogen, dissolved organic nitrogen, inorganic ammonium nitrogen, and inorganic
nitrate nitrogen.
2.4.1. Particulate Organic Nitrogen
The general equation includes four terms representing algae basal metabolism and predation,
dissolution to dissolved organic nitrogen, settling, and external loads.
dRPON v
—— = 2, BMx + FNRP¦ PRx)ANCx. Bx - Krpon. RPON
x=c,d,g,m
d WRPON
+ — (WSrp.RPON)+ (38)
dLPON
= ^ (FNLX. BMX + FNLP. PRX)ANCX. Bx - Klpon.LPON
dt
x=c,d,g,m
d WLPON
+ — (WSlp.LPON)+ y (39)
RPON = concentration of refractory particulate organic nitrogen (g N m"3)
LPON = concentration of labile particulate organic nitrogen (g N m"3)
FNRX = fraction of metabolized nitrogen by algal group x as refractory particulate organic
nitrogen
FNLX = fraction of metabolized nitrogen by algal group x as labile particulate organic
nitrogen
FNRP = fraction of predated nitrogen as refractory particulate organic nitrogen
FNLP = fraction of predated nitrogen as labile particulate organic nitrogen
ANCx = nitrogen-to-carbon ratio in algal group x (g N per g C)
Krpon = hydrolysis rate of refractory particulate organic nitrogen (day"1)
36
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Klpon = hydrolysis rate of labile particulate organic nitrogen (day"1)
WRPON = external loads of refractory particulate organic nitrogen (g N day"1)
WLPON = external loads of labile particulate organic nitrogen (g N day"1)
2.4.2. Dissolved Organic Nitrogen
The general equation includes five terms representing algae basal metabolism and predation,
dissolution from refractory and labile particulate organic nitrogen, mineralization to ammonium,
and external loads.
dDON
= ^ (FNDX. BMX + FN DP. PRX)ANCX. Bx + KRP0N. RPON + KLP0N. LPON
dt
x=c,d,g,m
WD ON
~ KDon-DON H — (40)
DON = concentration of dissolved organic nitrogen (g N m"3)
FNDX= fraction of metabolized nitrogen by algal group x produced as organic nitrogen
FNDP = fraction of predated nitrogen produced as dissolved organic nitrogen
Kdon = mineralization rate of dissolved organic nitrogen (day"1)
WDON external loads of dissolved organic nitrogen (g N day"1)
KHN
KHN + NH4 + N03
KrpoN — I KrN + , \i u a I ^RNalg > Bx \exp(KTHDR[T — TRhdr]) (41)
X
x=c,d,g f
Klpon — (^lw + khn+nh4+no3 ^LNala 2>x=c,d,g Bx) exP(KTHDR[T — TRhdr]) (42)
( KHN ST \
Kdon — I Kdn + + + ^q^ ^DNaig 2_, I exP(KTHDR[T — TRhdr]) (43)
\ x=c,d,g f
Krn = minimum hydrolysis rate of refractory particulate organic nitrogen (day"1)
Kln = minimum hydrolysis rate of labile particulate organic nitrogen (day"1)
Kdn = minimum mineralization rate of dissolved organic nitrogen (day"1)
KRNaig = constant that relates hydrolysis of refractory organic nitrogen to algal biomass
(day"1 per g C m"3)
KLNaig = constant that relates dissolution of labile organic phosphorus to algal biomass
(day"1 per g C m"3)
KDNaig = constant that relates mineralization to algal biomass (day"1 per g C m"3)
KHN = mean half-saturation constant for algal nitrogen uptake (g N m"3)
37
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2.4.3. Ammonium Nitrogen
The general equation includes five terms representing algae basal metabolism, predation, and
uptake; mineralization and dissolved organic nitrogen; nitrification to nitrate, sediment-water
exchange; and external loads.
dNH4 V"1
—— = ) {FN1X. BMX + FN I P. PRX - PNX. PX)ANCX. Bx + KD0N. DON - KNit. NH 4
ut Z—i
x=c,d,g,m
BFNH4 WNH4
+ —Ai— + —K— (44)
FNIX= fraction of metabolized nitrogen by algal group x produced as inorganic nitrogen
FNIP = fraction of predated nitrogen produced as inorganic nitrogen
PNX = preference of ammonium uptake by algal group x (0 < PNx < 1) given below
KNit = nitrification rate (day"1) given below
BFNH4 = sediment-water exchange flux of ammonium (g N m"2 day"1) with bottom layer
WNH4 = external loads of ammonium (g N day"1)
N03
PNy = NHA
*X 1 JV'Ty v 1V11JVX
I KNHX
+ NH 4
-)
x \{KHNX + NH4) ( KHNX + NO3)
") (45)
.(JVtf 4 + NO3) ( KHNX + NO3)
( UO W KHNitN \
KNit = fNit(T) Nitm (46)
J V \KHNitD0 + DOJ \KHNitN + NH4/ mV J
fNit(T) = Temperature function for nitrification (see below)
KHNitDO = Nitrification half-saturation constant for dissolved oxygen (g 02 m"3)
KHNitN = Nitrification half-saturation constant for ammonium (g N m"3)
Nitm = maximum nitrification rate at TNit (g N m"3 day"1)
fNit(T) = exp(-KNitl[T - TNitl]2); T < TNitl (47)
= 1; Tnitl < T < TNit2
= exp(—KNit2[T - TNit2]2); T > TNit2
TNitl = lower optimum temperature for nitrification (°C)
TNit2 = upper optimum temperature for nitrification (°C)
KNitl = effect of temperature below TNitl on nitrification (°C"2) using Gaussian form
KNit2 = effect of temperature above TNit2 on nitrification (°C"2) using Gaussian form
38
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2.4.4. Nitrate Nitrogen
The general equation includes five terms representing algae uptake, nitrification from
ammonium, denitrification to nitrogen gas, sediment-water exchange, and external loads.
dN03 ^ BFN03
—= 2_t C1 ~ PNx)Px¦ ANCx. Bx + Nit. NH4 - ANDC. Denit. DOC +
x=c,d,g,m
WNO 3
+ —— (48)
ANDC = mass of nitrate nitrogen reduced per mass of dissolved organic carbon oxidized
(0.933 g N per g C)
BFN03 = sediment-water exchange flux of nitrate (g N m"2 day"1) with bottom layer
WN03 = external loads of nitrate (g N day"1)
2.5. Silica
The modeled silica groups include particulate biogenic silica and available silica.
2.5.1. Particulate Biogenic Silica
The general equation includes four terms representing diatom basal metabolism and predation,
dissolution to available silica, settling, and external loads.
dSU d WSU
— = (FSPd.BMd + FSPP.PRd)ASCd.Bd - Ksua.SU + — (WSd.SU) + — (49)
SU = concentration of particulate biogenic silica (g Si m"3)
FSPd = fraction of metabolized silica by diatoms produced as particulate biogenic silica
FSPP = fraction of predated diatom silica produced as particulate biogenic silica
ASCd = silica-to-carbon ratio of diatoms (g Si per g C)
Ksua = dissolution rate of particulate biogenic silica (day"1)
WSU = external loads of particulate biogenic silica (g Si day"1)
WSd = settling velocity of particulate biogenic silica (m day"1)
Ksua = Ksu. exp(KTSUA[T-TRSUA]) (50)
Ksu = dissolution rate of particulate biogenic silica at TRsua (day"1)
KTsua = effect of temperature on dissolution of particulate biogenic silica ("C"1)
TRsua = reference temperature for dissolution of particulate biogenic silica (°C)
39
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2.5.2. A vailable Silica
The general equation includes five terms representing diatom basal metabolism, predation, and
uptake; settling of sorbed (particulate) available silica; dissolution from particulate biogenic
silica; sediment-water exchange; and external loads.
dSA d BFSAd
— = (FSId.BMd + FSIP .PRd)ASCd.
Bd + Ksua- SU + te (VK5r55"SAp) + —Az—
WSA
+ — (51)
SA = concentration of available silica (g Si m"3) = SAd+SAp
SAd = dissolved available silica (g Si m"3)
SAp = particulate (sorbed) available silica (g Si m"3)
FSId = fraction of metabolized silica by diatoms produced as available silica
FSIP = fraction of predated diatom silica produced as available silica
BFSAd = sediment-water exchange flux of available silica (g Si m"2 day"1)
WSA = external load of available silica (g Si day"1)
KSAv. TSS
SAp = —^(52)
1 + KsAp-TSS
1
SAd = —SA (53)
1 + KsAp-TSS
Ksap = empirical coefficient relating available silica sorption to total suspended solids (g m"3)
2.6. Chemical Oxygen Demand
The general equation includes three terms representing oxidation, sediment flux, and external
loads of chemical oxygen demand.
dCOD DO BFCOD WCOD
—=-7777 —KCOD.COD+— + ——- (54)
dt KHcod + DO A z V
COD = concentration of chemical oxygen demand (g 02-equivalents m"3)
KHcod = half-saturation constant of dissolved oxygen required for oxidation of chemical
oxygen demand (g 02 m"3)
KCOD = oxidation rate of chemical oxygen demand (day"1)
BFCOD = sediment flux of chemical oxygen demand (g 02-equivalents m"2 day"1)
WCOD = external loads of chemical oxygen demand (g 02-equivalents day"1)
KCOD = KCD.exp(KTC0D[T-TRC0D]) (55)
Kcd = oxidation rate of chemical oxygen demand at TRcod (day"1)
40
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KTcod = effect of temperature on oxidation of chemical oxygen demand ("C"1)
TRcod = reference temperature for oxidation of chemical oxygen demand (°C)
2.7. Dissolved Oxygen
The general equation includes seven terms representing algal photosynthesis (production) and
respiration (basal metabolism), nitrification, hetrotrophic respiration of dissolved organic carbon,
oxidation of chemical oxygen demand, surface reaeration, sediment oxygen demand, and
external loads.
dDO sr1 ( DO \
——= > [ (1.3 — 0.3. PNX)PX — (1 — FCDX) BMx\AOCR.Bx
dt L-l \ V XV X V XV KHR^ + D0 X X
x=c,d,g,m \ '
DO
- AONT. Nit. NH4 - AOCR. KHR.DOC - — — KCOD. COD
Knrnn + DO
SOD WDO
+ Kr{DOs-DO)+ —+ -p- (56)
AONT = mass of dissolved oxygen consumed per unit mass of ammonium nitrogen nitrified
(4.33 g O2 per gN)
AOCR = dissolved oxygen-to-carbon ratio in respiration (2.67 g O2 per g C)
Kr = reaeration coefficient (d"1): the reaeration term is applied to the surface layer only
DOs = saturated concentration of dissolved oxygen (g O2 m"3)
SOD = sediment oxygen demand (g O2 m"2 day"1): applied to the bottom later only
WDO = external load of dissolved oxygen (g O2 day"1)
DOs = 14.5532 - 0.38217.7 + 5.4258 x 10_3.r
-3 j2
- CL. (1.665 x 10-4 - 5.866 x 10-6. T + 9.796 x 10-8. T2) (57)
CL = chloride concentration (mg L"1) = S/l.80655
ro h
U-eq
+ Wrea)^-f7f-20) (58)
Kro = proportionality constant = 3.933 in MKS (meter kilogram second) unit
ueq = weighted water surface velocity over cross-section (m sec"1) =H(it k V k )/ ^ V k , ui< and
Vk are velocity and volume, respectively, of a surface segment on the cross-section as
calculated by the hydrodynamic model (Abdelrhman 2015)
heq = weighted depth over cross-section (m) = Y.(Vk)
B„ = width at the free surface (m)
Wrea = wind-induced reaeration (m day"1)
41
-------
Wrea = 0.7281/°-5 - 0.317Uw + 0.0372U* (59)
Uw = wind speed (m sec"1) at height of 10 m above surface
KTr = constant for temperature adjustment of dissolved oxygen reaeration rate
2.8. Total Active Metal
Total active metal is not currently modeled in this work. The general equation includes three
terms representing anoxic release from benthic sediment, settling of particulate metal, and
external loads.
dTAM KHbmf BFTAM , d WTAM
— = KHbmf I DO —e*^-^+-z(WSs.TAMv)+— (60)
TAM = total active metal concentration (mol m"3) = TAMd + TAMp
TAMd = dissolved total active metal (mol m"3)
TAMp = particulate total active metal (mol m"3)
KHbmf = dissolved oxygen concentration at which total active metal release is half the
anoxic release rate (g O2 m"3)
BFTAM = anoxic release rate of total active metal (mol m"2 day"1)
Ktam = effect of temperature on sediment release of total active metal ("C"1)
Ttam = reference temperature for sediment release of total active metal (°C)
WSs = settling velocity of particulate metal (m day"1)
WTAM = external load of total active metal (mol day"1)
TAMd = minimum{TAMdmx.exp(—Kdotam.DO),TAM} (61)
TAMp = TAM - TAMd (62)
TAMdmx = solubility of total active metal under anoxic conditions (mol m"3)
Kdotam = constant that relates total active metal solubility to dissolved oxygen (per g O2 m" 3^
2.9. Fecal Coliform Bacteria
The general equation for fecal coliform bacteria includes two terms representing die-off and
external loads.
dFCB _ 7n WFCB
—= -KFCB. TFCBt~20. FCB + (63)
FCB = bacteria concentration (MPN per 100 ml)
KFCB = first order die-off rate at 20 °C (day"1)
TFCB = effect of temperature on decay of bacteria ("C"1)
WFCB = external loading of fecal coliform bacteria (MPN per 100 ml m-3 day-1)
42
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"l |c"
-[lpoc }
raspiratlo
• TSS If';."-
mod*)
Figure 26. Schematic presentation of state variables simulated in the EFDC water quality
model.
43
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3. Model Configuration
Model configuration requires establishing the numerical grid, identifying the forcing functions,
setting the initial conditions (including parameter values), choosing the time step and duration,
and preparing the input. All these requirements were developed for the hydrodynamic model
(Abdelrhman 2015). This section covers the same requirements for the water quality model.
3.1. Numerical grid
The use of the same numerical grid to serve both the hydrodynamics and the anticipated water
quality simulations is essential to this work. Thus, the numerical grid should be fine enough to
resolve the geometry; meanwhile, it should be coarse enough to accommodate the dimensionality
limitations of the water quality model (-7,000 cells in WASP7) and the coarseness of the
biological rate measurements, which are typically daily values. After many trials the final grid
included 754 horizontal segments and 8 vertical layers, a total of 6,032 segments. The adequacy
of the grid was confirmed from the hydrodynamic results. Locations for rivers, WWTPs, and
monitoring stations were identified on the numerical grid. Figure 27A shows the generated grid
with the locations of stations that were used for calibration and validation of model results.
3.2. Initial and boundary conditions
Various forces affected the hydrodynamics in NB at times during the simulation period in 2009.
All forcing values were provided at hourly or daily increments. These forces were internally
interpolated to the hydrodynamic time step by the model. These forces included: tide elevation
(m), freshwater inflows from the eight rivers (m3 s"1), salinity concentration (ppt) at seaward
open boundary and for all freshwater inflows (assumed zero for river inflows), temperature (°C)
at all nodes on the seaward open boundary and for all river inflows (assumed similar to air
temperature throughout the year), atmospheric pressure (millibar), air temperature (°C), air
relative humidity, rain fall rate (m s"1), shortwave solar radiation (W m"2), cloud cover (%), wind
speed (m s"1), and wind direction from the North (degree).
The water quality model used the predicted hydrodynamics (water surface elevation, water
velocity, horizontal and vertical diffusivities, water temperature, and water salinity). The water
quality model required information about the distribution of initial concentrations, the temporal
variation of boundary concentrations, the temporal behavior of loading rates of all the modeled
state variables, and numerous biological constants and rate parameters.
Unless otherwise specified, initial conditions in NB were consistent with conditions at 00:00
time on January 1, 2009. The spatial distribution of the initial values was prepared for
temperature and salinity as described in Abdelrhman (2015). The initial spatial distribution of all
water quality state variables were not available, and they were assumed to be vertically and
horizontally constant. Assuming that winter concentrations do not change much between
different years, the starting initial values where set from predictions at station CP at the end of an
exploratory test simulation (i.e., at 24:00 PM on 31 December, 2009) (Table 3). Updating these
initial values was manifested during the calibration of benthic fluxes which required running the
yearly simulation more than five times to nourish the various chemical reservoirs by setting the
end-of-run results as initial conditions for the succeeding run (Abdelrhman 2016a). Nonetheless,
the effect of initial values would be reduced as the simulation proceeds, and the initial value
distributions are updated throughout the year.
44
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Concentrations at the seaward open boundary were assumed to be vertically uniform (Table 3),
except for phytoplankton. These concentrations would continue to moderate respective values
inside the Bay throughout the simulation period; thus, temporal variations of these
concentrations should be considered for more accurate predictions. Due to the proximity of
station GD to the seaward open boundary, concentrations of DO and Chi-a at GD were used to
represent their respective values at the open boundary. The time series of DO was calculated
from the daily average for the years 2004-2010. The Chi-a concentrations were converted to mg
C L"1 using the carbon to Chl-a ratio of 0.060 (mg cellular C per (J,g-chl a) for all algal groups.
The concentration of phytoplankton carbon was partitioned equally between Be, Bd, and Bg
throughout the year. Phytoplankton at the open boundary was assigned to only the surface two
layers (7 and 8). Assuming that yearly behavior of the outside concentrations in the Rhode Island
Sound does not have drastic inter-annual changes, typical monthly values for NH4, N03+N02,
P04t, and SA were calculated from the data reported by Kremer and Nixon (1978) for 1972-
1973. These data were considered to represent rough estimates of the concentration time series at
the open boundary (Fig. 22). Time series of monthly concentrations of DOP and DON were
calculated from data collected by Jason Krumholz (URI-GSO) at his station No.3 (personal
communication: L. Charlestra, USEPA-AED). Unknown concentrations for other state variables
were assumed to have small constant values of 0.01 mg L"1 at the open boundary.
Wet and dry atmospheric depositions were assumed to have constant values similar to those for
the nearby Lower Charles River, MA (Tetra Tech, 2005) (Table 3).
Benthic fluxes were calculated by the EFDC benthic flux modules and they were calibrated
based on mathematical forms presented for NB by Fulweiler et al. (2010) for SOD and by
Kremer and Nixon (1978) forNFU, P04t, and SA (Abdelrhman, 2016a).
3.3. Point-source loadings
Two types of point source loadings exist with direct input into NB. The first type is from river
and riparian discharges (Table 1, Figs. 2-8, and Fig. 27B) and the second type includes
discharges from WWTPs (Table 2, Figs. 9-15, and Fig. 27C). Indirect discharges from other
WWTPs, which exist in the watershed, were implicitly considered in the river loads. The first
type of point source loadings (from rivers) was considered to approximately represent the
baseline scenario, which existed before the establishment of WWTPs on the Bay. The same
scenario could also represent the ultimate mitigation condition when loads from all WWTPs on
the Bay cease. This work does not present any scenarios for indirect loads from WWTPs in the
watershed.
3.4. Time step and run duration
Hydrodynamic and transport simulations were run for the year 2009. The full duration of the
majority of simulations was 365 days (31,536,000 s). The simulation time step for water quality
predictions was 15s. This time step produced stable solutions during the various seasons and
during the spring-neap tidal cycles throughout the full year. All values of loading rates and rate
coefficients with longer time variability were internally interpolated by the model to the
simulation time step.
The full year simulation required a total of 2,102,400 time steps and took ~ 427s of CPU time to
execute one day of simulation time (on the desktop computer DELL-Intel[R] Xeon[R] CPU E5-
45
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2609 0 @ 2.4GHz). The full-year simulation of hydrodynamics with TSS and water quality with
fluxes from benthic sediment took approximately 18 h of CPU time.
3.5. Input files
In addition to the input files for the hydrodynamic model (Abdelrhman, 2015), the water quality
input files used in this work included the three main input files: EFDC.INP with all parameters
for a simulation of combined hydrodynamics and water quality, WQ3DWC.INP with all water
quality parameters (Appendix D), and WQ3DSD.INP with all sediment water quality parameters
(Abdelrhman 2016a). Time series of all point sources of rivers and WWTPs were included in
WQPSL.INP. Moreover, the following time series for each state variable at the seaward open
boundary were also needed:
1) dinoflagellates (Be): cwqsrOl.inp.
2) diatom algae (Bd): cwqsr02.inp.
3) green algae (Bg): cwqsr03.inp.
4) refractory particulate organic carbon (RPOC): cwqsr04.inp.
5) labile particulate organic carbon (LPOC): cwqsr05.inp.
6) dissolved carbon (DOC): cwqsr06.inp.
7) refractory particulate organic phosphorus (RPOP): cwqsr07.inp.
8) labile particulate organic phosphorus (LPOP): cwqsr08.inp.
9) dissolved organic phosphorus (DOP): cwqsr09.inp.
10) total phosphate (P04t): cwqsrlO.inp.
11) refractory particulate organic nitrogen (RPON): cwqsrll.inp.
12) labile particulate organic nitrogen (LPON): cwqsrl2.inp.
13) dissolved organic nitrogen (DON): cwqsrl3.inp.
14) ammonium nitrogen (NH4): cwqsrl4.inp.
15) nitrate nitrogen (N03): cwqsrl5.inp.
16) particulate biogenic silica (SU): cwqsrl6.inp.
17) dissolved available silica (SA): cwqsrl7.inp.
18) chemical oxygen demand (COD): cwqsrl8.inp.
19) dissolved oxygen (DO): cwqsrl9.inp.
21) fecal coliform bacteria (FCB): cwqsr21.inp.
46
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Warr^g/Palmer
Riparian
E. Branch
Riparian
Figure 27. The numerical grid and locations of stations and point source loads. (A) Numerical grid and locations of water
quality monitoring stations for Narragansett Bay, (B) Locations of freshwater inflows, (C) Locations of WWTPs discharges.
Group 2
Group 1
Woonasquatucket
Moshassuck
Blackstone
Ten Mile
Taunton +
Riparian
Hunt +
Riparian
Pawtuxet +
Riparian
Sakohnet
Riparian
V. Branch
iparian
47
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4. Model Calibration and Validation
The calibration and validation of the hydrodynamic model results included predictions of water
surface elevation, temperature, salinity, and velocity during the year 2009. The calibration
parameters include the bottom roughness height, z0, Smagorinsky's coefficient for calculation of
horizontal diffusion, c, and the constant horizontal diffusion/dispersion coefficient, A0. The
calibration values were z0 = 0.01 m, c = 0.005, and A0 = 5 m2 s"1. These values were not changed
for mass transport of the water quality variables. The turbulence closure scheme produced the
vertical diffusion and dispersion coefficients from a set of parameters that were kept at their
default values. The validation of water temperature and salinity were presented in Abdelrhman
(2015). Validation of DO and Chi-a concentrations were presented at all NBC buoy stations, as
discussed below.
In general, calibration of water quality requires a comprehensive and intense field program and
historical data to cover all kinetic processes for the modeled state variables. Such information
was not available for this effort, instead existing historical data (Section 1.5) were used. Many of
the model parameters controlling water quality processes were used successfully during testing
of the Chesapeake Bay Model (Cerco and Cole 1994). These parameters were given in the EFDC
model documentation (Hamrick et al. 1996). During model application and testing for
Narragansett Bay, many of the parameter values were identical to those of the Chesapeake Bay
application with only few changes to produce results that were closer to field observations
throughout NB. Values of the changed parameters fell within ranges used in accepted previous
applications of the model including studies in Christina River Basin (USEPA 2000) and the
nearby Charles River Basin, Massachusetts (Tetra Tech, 2005).
Table 5 presents values for the main parameters that are calibrated and used for Narragansett
Bay. Dissolved oxygen and phytoplankton are the primary constituents used for calibration.
Phytoplankton is the major controlling factor for most of the water quality constituents (Fig. 26).
Over 50 common phytoplankton species exist in Narragansett Bay (Karentz and Smayda, 1984).
It is assumed that the three major phytoplankton groups include nano plankton with sizes < 20
[j,m (Durbin et al., 1975), with an optimum temperature for growth at 23-25 °C, which resemble
greens in the model. Another phytoplankton group includes diatoms with sizes > 20 [j,m and with
optimum growth at 12-15 °C. Diatoms use silica in their structure and they have settling speed
0.25-2.0 m d"1 (Kremer and Nixon, 1978). The last group includes dinoflagellates with sizes >20
[j,m and it has optimum growth at 18-22 °C (Personal communication: Dan Campbell, USEPA-
AED). The three phytoplankton groups are assumed to have a carbon to Chl-a ratio of 60 and
-1.9 doublings per day during the summer blooms (Durbin et al. 1975). Growth rates for the
three groups are considered to be calibration parameters.
Benthic fluxes were calibrated based on mathematical forms presented for NB by Fulweiler et al.
(2010) for SOD and by Kremer and Nixon (1978) forNH4, P04, and Si (Abdelrhman, 2016a).
Suspended sediment concentrations affect water clarity, which impacts irradiance levels and
phytoplankton growth through the water column. Total suspended particles include both mineral
particles (i.e., cohesive sediments) and phytoplankton. Cohesive sediments were modeled in NB
during 2009 (Abdelrhman 2016b).
Each calibration run for NB covered hydrodynamics (including temperature and salinity),
benthic processes and flux (including diagenesis), and TSS for the full year of 2009, which ran
overnight (-18 CPU hours). Visual observation of results were conducted for various water
48
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quality variables including phytoplankton, DO, and benthic sediment flux (Fig. 28). One of the
most important calibration variables was POC, which originated from settling of phytoplankton
particles and it controlled coupling between benthic fluxes, DO, and phytoplankton. Processes
controlling POC were calibrated to insure that POC mass had a quasi-steady behavior with end
of year values similar to their initial values at the beginning of the year. The quasi-steady
behavior was established for all benthic sediment state variables and fluxes (Abdelrhman 2016a).
Model performance was established holistically by examining the overall behavior of the whole
Bay as well as by comparing predicted and observed time series and vertical profiles at the
locations of the twelve buoy stations (Fig. 27 A). Similarly, validation of model predictions was
established by visually inspecting the temporal behavior of all the state variables throughout the
full year of 2009.
4.1. General behavior of the whole Bay
The available Chi-a and DO historical data from RIDEM and NBC concentrated on the period
June-October for all stations, except stations GB and GD which covered the full year (Fig. 29).
Each station represents a specific area (Fig. 30) (GIS Thiessen polygons, personal
communication: J. Copland USEPA-AED). Station area is used to weigh its contribution to the
overall average for the whole bay (i.e., the weighted average for the Bay = station area / overall
area x observation) (Table 6). The same station weights were applied to model predictions at the
station locations to produce consistent and compatible predictions for the Bay. The accuracy of
these weights will largely depend on mixing at each station, which is not included in the
weighting scheme.
4.1.1. General behavior of DO
Daily average observations of surface and bottom DO concentrations are presented by NBC
(Figs. 31A and 3 IB, respectively). Comparison between observed and predicted area-weighted
average DO concentrations for the whole Bay are shown in Fig. 31C. The model captured the
overall general trend and behavior of DO at the bottom and surface within 1-2 jag L"1.
4.1.2. General behavior of Chl-a
Actual observations of surface Chl-a concentrations at all stations are presented by RIDEM at
15-minute intervals. Data were based on Chl-a fluorescence. Chlorophyll quenching affected all
daytime observations. Quenching effects were avoided by using night time measurements (Fig.
32A). The area-weighted observed average of Chl-a concentration for the whole Bay is shown in
Fig. 32B. There are approximately four different peaks in Chl-a concentration showing in middle
of June, July, August, and the beginning of September. The maximum overall concentration (~
18 jag L"1) appeared on August 8th, 2009. Comparison with model predictions are presented in
Fig. 32C. The model captured the times of all the blooms and their values during the summer.
The difference between predicted and observed peaks was < 4 jag L"1, which may be attributed to
inconsistency in the relation between phytoplankton and Chl-a (see Discussion).
4.2. Validation of dissolved oxygen
Predictions of surface and bottom DO concentrations were compared with observations at the
twelve buoy stations (Appendix D). Visual inspection indicated that predictions agreed
reasonably with observations with some stations better than others, which suggest spatial
49
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variability due to local conditions (see Discussion). More discussion on hypoxia is presented
later.
Comparison between predicted and observed profiles of DO are presented in Appendix E.
Effects of vertical stratification are evident in both observations and predictions. The upper ~ 4-6
meters of the water column showed higher DO concentrations than the rest of the water column
at various locations and times during the summer season. Predicted profiles for the same
locations and times resembled the observed vertical structures within -1-2 mg L"1.
4.3. Validation of Chl-a
Predictions of surface Chl-a concentrations were compared with observations at eleven buoy
stations (Appendix F) (Station TW had no records of Chl-a). For most stations, predictions and
observations of Chl-a had the same range of values. Predictions were noticeably lower than
observations at stations PD, MH, and GD, which may be attributed to effects of spatial
variability (see Discussion). The observations indicated a spring bloom at station GB.
Unfortunately, field observations were not reported during this period in 2009 at the other
stations. Model predictions did not show any spring blooms in the Bay.
Comparison between predicted and observed profiles of Chl-a are presented in Appendix G.
Effects of vertical stratification are evident in both observations and predictions. The upper ~ 4-6
meters of the water column showed higher Chl-a concentrations than the rest of the water
column at various locations and times during the summer season. With few exceptions, most of
the predicted Chl-a profiles resembled the observed vertical structures for the same locations and
times. Observed Chl-a structures at station BR indicated values higher than predictions, which
may be attributed to loading of freshwater phytoplankton from the nearby rivers. Such loads are
not modeled in this work.
50
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Table 5. Main kinetic coefficients used for Narragansett Bay (Appendix D).
Coefficient
Value
Card number1*
Maximum algal growth rate (d"1)
3.2, 2.8, 3.0a
45
Optimum temperature for algal growth (°C)
18/22, 12/15, 23/25a'b
11
Effect of temperature on algal growth below
optimum temperature (°C"2)
0.008, 0.008, 0.008a
12
Effect of temperature on algal growth above
optimum temperature (°C"2)
0.008, 0.008, 0.008a
12
Algal basal metabolism rate at 20°C (d"1)
0.14, 0.14, 0.14a
45
Half-saturation constant for:
Nitrogen uptake of algae (g N m"3)
Phosphorous uptake of algae (g P m"3)
Silica uptake of diatoms (g Si m"3)
0.02, 0.02, 0.02a
0.001, 0.001, 0.001a
0.035
8
Algal predation rate at 20°C (d"1)
0.035, 0.035, 0.03a
45
Algal settling rate (m d"1)
0.5, 0.5, 0.15a
46
Carbon to chlorophyll ratio (mg C [(jg-chl]"1)
0.06, 0.06, 0.06a
9
Decay rate of:
Organic carbon dissolution at 20°C (d"1)
Organic phosphorous hydrolysis at 20°C (d"1)
Organic nitrogen hydrolysis at 20°C (d"1)
0.005, 0.05, 0.070°
0.005, 04, 0.050°
0.002, 0.040, 0.050°
16
21
26
Dissolution rate of particulate silica at 20°C (d"1)
0.05
27
a For dinoflagellates, diatom, and green algae, respectively
b Lower optimum temperature/upper optimum temperature for persisting maximum growth rate
c For refractory particulate, labile particulate, and dissolved organic matter, respectively
d Card number in Appendix C
51
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Table 6. Station area weights for calculation of Bay-wide overall weighted averages for DO
and Chl-a.
Station
Ch
-a
DO
Area (m2)
Weight
Area (m2)
Weight
PP
32204392
0.137988
32204392
0.117622
MH
34239205
0.146707
34239205
0.125054
SR
12027197
0.051534
12027197
0.043928
CP
22017467
0.094339
22017467
0.080416
PD
5888185
0.025229
5888185
0.021506
QP1
46482351
0.199166
46482351
0.169771
GD
17471410
0.074861
17471410
0.063812
MV
26646653
0.114174
26646653
0.097324
NPI
18369277
0.078708
18369277
0.067091
BR
15652605
0.067068
15652605
0.057169
GB
2386795
0.010227
2386795
0.008717
TW
N/A
N/A
40409011
0.147589
Total
233385535
1
273794546
1
52
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Table 7. Comparison of predicted and observed chronic and acute periods of bottom DO
concentrations with and without WWTPs showing percent improvement in brackets.
Station
Observed
Chronic
(h)
Observed
Acute
(h)
Predicted
Chronic
WAYWTPs
(h)
Predicted
Acute
WAYWTPs
(h)
Predicted
Chronic
No
WWTPs'
(h)
Predicted
Acute
No
WWTPs1'
(h)
PD
1803.5
580.25
1121
6
375 (67%)
0
CP
1737.75
256.75
1596
120
1136(26%)
0
GB
1813.75
770.25
2132
879
1966 (8%)
476 (46%)
SR
1607.25
731.75
534
1
261 (51%)
0
BR
1177.5
199.25
1894
198
1110(41%)
0
NPI
1419.5
423.25
702
0
251 (64%)
0
PP
1253.75
57.5
23
0
0 (100%)
0
MV
1115
290
0
0
0
0
QP1
539.25
3.25
0
0
0
0
TW
333.75
0
0
0
0
0
MH
1066.75
131
275
0
65 (76%)
0
Total (h)
13867.75
3443.25
8277
1204
5164 (38%)
476 (60%)
Total (d)
578
143
345
50
215 (38%)
20 (60%)
a Percent improvement =100 [(Prediction w/WWTPs - Prediction w/o WWTPs) / Prediction
w/WWTPs]
53
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CR 41
N^SuiKtCH*
IfSI'lJItlitlS I ! 5 ! ! I I I ! ! i t I
§S5»BS>xiSS5§5 5SS»»S*SSS*2«
(Sy^
°| I ! ! I ! I |T I I I i S i * 5 1 * I 5 S S 5 * 1 1 S 'iilllijjlJltil
s s H : I h : s : i : : IslStfslssjssI ssssssSsssjsis
m (Mf » • »¦ ~ LM*
NPISgcfKcOO
(Mm 00 AmK . . . W' ,. . . » ' " ,
M
8 ' f I m /
II I I I H I I II " ^ f
SOD Flu* AmeMum Rw
Ph&i&Nat* flu» Site* Flu* KX
-
'i
!! I!! 111!
HIM 1 II 11II II11111 ~!
illilllli1'!
8
1
Figure 28. Example of water quality parameters that were investigated during each
calibration run (these data are from run 41). From top left: chl-a (from diatoms,
dinoflagellates, and greens) at all stations, Bay weighted average chl-or, total chl-a at station NPI,
Chl-a (from diatoms, dinoflagellates, and greens) at station NPI, surface DO at station NPI,
bottom DO at station NPI, 10-day surface DO at station NPI, DO vertical profiles (on 6/25, 7/10,
8/3 of 2009, respectively), benthic fluxes (of SOD, NFU, P04, Si, respectively), and POC.
54
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Data Gaps
• CP • GB #TW »PD • BR »SR «NPI • PP • MV «QP1 • MH • GD
00
co
co
fN
rH
T—I
rH
rH
rH
Date
Figure 29 Periods and gaps of Chl-« observations at each station location.
Station numbers on the vertical axis correspond to their order in the legend.
55
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-71°20'
-7no'
% \ Blackstone River
\\ IpD *
CD
Ten Mile River
Providence
Warren/
Palmer River
Brayton
Fall River
^Greenwich
Bay
Mt. Hope
Stations
Hunt River
Quonset
Point
Aquidneck
Island
O JO
Newport
Figure 30. Stations and associated areas to calculate area-weighted Chl-« and
DO concentrations.
56
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Observed DO at surface
8 8
1 a
S :>
(A)
Observed DO at bottom
-BR
-MH
-PP
- Ror Average
-CP
-MV
-QP
GB
NPI
SR
GO
-PD
- rw
*/vT
I
%
for1
(B)
- Pred Bot Avg -
Average DO for the whole Bay
- Pred Surf Avg Obs Surf weighted avg Obs Bot weighted avg
(C)
Figure 31. Comparison between observed and predicted behavior of DO for the whole Bay.
(A) Observed surface DO concentrations from NBC with profile surface values from
Brown University data, (B) Observed bottom DO concentrations from NBC,
(C) Comparison between weighted average predictions and NBC observations for the
whole bay.
57
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Observed surface Chl-a
BR NPI
GD • Profile
(A)
Weighted Average Observed Chl-a
Z* 18
_i
60 16
=L
- 14
•2 12
ro
£ 10
c
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5. Results
Predictions from two extreme scenarios are presented: one to illustrate the contemporary current
conditions with loading from WWTPs (Appendix A) and the other without loading from
WWTPs. The latter scenario bounds the maximum change that can be achieved by eliminating
such loadings. Example of model predictions are presented for DO and Chi-a to illustrate
anticipated maximum improvement in hypoxia at all buoy locations.
In addition to the time series results for DO and Chi-a that are presented for validation at the
buoy locations (Appendices D-G)' this section provides more results about the temporal
variation of all the modeled state variables. The model generated data for the state variables are
very extensive in both space and time. The concentration predictions are presented for the
modeled 20 state variables in the water column at all stations during the full year of 2009
(Appendix H).
5.1. Contemporary DO and hypoxia
Loadings from all rivers and the eleven WWTPs were included in the simulation and the model
was rerun to predict water quality values for contemporary conditions. Appendix D presented
time series of surface and bottom DO concentration including the hypoxic events in the bottom
waters and their durations at the eleven buoy locations (Table 7). Example of daily variation is
presented in Fig. 33 which shows predicted and observed near surface DO concentration at
station NPI during 10 days in July, 2009. The dawn-dusk-dawn variation was predicted within
-1.0 jag L"1. The scatter plot in Fig. 34 shows the linear relation (r2 = 0.78) between model
predictions and observations of bottom DO concentrations at station CP.
The chronic and acute DO criteria values are assumed to be 4.8 mg L"1 and 2.3 mg L"1,
respectively, as indicated by the horizontal lines in the figures (Appendix D). The observed and
predicted DO concentrations exceeded these two criteria values at the various locations at
various times during the year and persisted for various durations (Table 7). Adding all
consecutive hours when the criteria was exceeded produced the duration for each event of
criteria exceedance. The overall total number of hypoxic hours during 2009 was also presented
in Table 7. The same procedure was applied to both observed and predicted DO concentrations
in the bottom layer (Layer 1). In general, predicted and observed hypoxic periods were close
both in their durations and when they occurred. For example, at station CP, the observed and
predicted periods of chronic criteria (4.8 mg L"1) expanded the three months from mid-June to
mid-September. Short breaks in predicted hypoxia (that may be attributed to vertical mixing due
to wind forces) broke this extended period into three shorter periods approximately 22d, 25d, and
19d (Fig 35). The observed hypoxic events showed more breaks in the hypoxic period, which
added up to values close to predictions (12.4d, 19d, and 17d, respectively). Such long hypoxic
events could be detrimental to aquatic life at this location.
5.2. Contemporary monthly vertical profiles of DO
Examples of vertical profiles of the DO concentration are presented at station CP approximately
every month during 2009 (at 30-d increments) (Fig. 36). The above-mentioned criteria value
(4.8 mg L"1) is marked by the vertical lines on the figure, which indicated that various parts of
the water column (i.e., lower part) might violate the criteria while other parts (i.e., higher part)
59
-------
may not violate it during various months of the year at the various locations (e.g., July and
August, 2009).
5.3. Contemporary hourly vertical profiles of DO at station CP on day 240
Vertical profiles of the DO concentration were presented at station CP every 2h during day 240
in the year 2009 (Fig. 37). The criteria values were marked by the vertical lines on the figures,
which indicated that various parts of the water column (i.e., lower part) might violate the criteria
while other parts (i.e., higher part) may not violate it during various hours on the same day.
60
-------
NPI Surface DO Layer 8
NPI Surface DO Layer 7
E "
c 3
3 j
§ i
- Pred Surf DO Gbs Surf DO Chronic DO Acute DO
- Pred Surf DO Obs Surf DO Chronic DO Acute DO
i g
gggggggg
2^«iQi3t3 23 22rjlJ33
N N K N h N N K N ^
Date
NPI Surface DO Layer 6
- Pre d Surf DO Obs Surf DO Chronic DO Acute DO
8 8
ri «>
8 S
§ &
r. r-
Date
8 8 8 S
I 8 I 1
E 4
£ 3
NPI Surface DO Layer 5
-Pred Surf DO Obs Surf DO Chronic DO Acute DO
g g g g
21 2 3 *3
g g
00 CTr
g g
s 5
gggggggg
•? y IS h» M <7>
8 r3
NPI Surface DO Layer 4
.2 6
i S
E 4
(LI H
c 3
<3 2
§ »
-Pred Surf 00 Obs Surf DO Chronic DO Acute DO
8 8 8 8 8 8
5 «) « m « n
§ 5. <. 5i
8 |! 8 8 8
00* A o' M r?
^ ^ Ci ^ ^
.2 6
E 5
c A
-------
CP Bottom DO
_ 1.20E+01
i—I
m 1.00E+01
£
0 8.00E+00
1 6.00E+00
01
o 4.00E+00
O
Q
¦a
2.00E+00
=5 O.OOE+OO
OJ
V = 1.0416X
R2 = 0.8317
2 4 6
Observed DO Concentration (mg L1)
10
Figure 34. Relation between predicted and observed bottom concentrations of DO
at station CP.
CP Hypoxia
¦Pred period Obs Period
700
600
500
Q-
300
x
0
g; 200
1
100
0
±\
Ili
J J
ti
CO
o
of
r-H
OJ*
rH
rsl
00
rH
m
rH
r-*
rH
LO
ID
rH
T—I
o*
-------
CP DO Monthly Profiles
Jan
Feb
Mar
Apr
May
Jun
Criteria
DO Concentration (mg LJ)
CP DO Monthly Profiles
8
7
6
i 5
1—
01
i
3
2
!
'(
V\
r
T
f I
/
Jul
'
IT
Aug
if
/
7
ft:
Sep
V
/
T
i
Oct
I '
L
/
II •
Dec
i
ff i
Criteria
0 1 2 3 4 5 6 7 8 9 10 11 12 13
DO Concentration (mg L1)
Figure 36. Example of contemporary monthly vertical profiles of DO at station CP during
2009—layer 1 is the bottom layer.
63
-------
CP DO Bihourly Profiles on Day 240
£ 4
¦ 2h
¦ 4h
6h
¦ 8h
• lOh
12h
Criteria
2 3 4 5 6 7
DO Concentration (mg L-l)
Q
CP DO Bihourly Profiles on Day 240
7
i
/
a
I
14h
D
O 5
16h
2 J
1—
01
>¦ A
vf\
18h
_i
Q
2 Oh
D
o
7 !
22h
z
1
;
24h
Criteria
01234567!
DO Concentration (mg L1)
Figure 37. Example of contemporary bihourly vertical profiles of DO at station CP on day
240 in 2009—layer 1 is the bottom layer.
64
-------
6. Discussion
6.1. DO and hypoxia without direct loads from WWTPs
This section covers the impact of the extreme scenario of assuming zero loads from the eleven
WWTPs (Table 2) on the predicted behavior of hypoxia in the Bay. The above-mentioned
chronic and acute DO criteria are represented by the horizontal lines in the figures (Appendix D).
The predicted DO concentrations were below the chronic and acute DO criteria at the various
locations at various times during the year and persisted for various durations (Table 7).
According to model predictions, the effect of removing all loadings from WWTPs would
improve hypoxia, but would not eliminate presumably because the model includes the persistent
loadings from the other point and non-point sources (e.g., rivers, atmosphere, and benthic
sediment).
6.2. Chl-a with and without WWTPs
In addition to direct loadings from WWTPs, phytoplankton growth responds to loads from other
sources, for example, loadings from other point sources (i.e., rivers) and non-point sources
(i.e., atmospheric deposition and benthic flux). Figure 38 highlights predicted Chl-a
concentrations with and without WWTPs at all buoy locations during the year 2009. It is clear
that the impact of WWTPs, which directly discharge into the Bay, reduced predictions of Chl-a
concentrations by -25%.
6.3 Spatial variability
All model predictions presented in this work assume spatially uniform distributions of model
coefficients and parameters for all state variables in the water column and benthic sediments.
In-situ observations at the buoy locations indicate spatial variability in the monitored water
column values for DO (Appendices D and E) and Chl-a (Appendix F). Future modeling efforts
will require adequate field efforts to identify and provide enough information about the spatial
variability of water quality coefficients and parameters to properly mimic the spatial variability
within the Bay.
6.4 Chlorophyll quenching and phytoplankton vertical migration
Physiology of phytoplankton cells can change based on the light level (Roesler 2014). When
light intensity is high, laboratory experiments indicate that concentration of Chl-a drops due to
non-photochemical quenching. Similar quenching behavior is expected in field measurements.
Figure 39 shows an example of Chl-a quenching at station NPI. During mid-day when light
intensity is high, Chl-a concentrations drop sharply to a minimum of 2-3 jag L"1 then they jump
sharply to their maximum values during the day in the early afternoon hours. However,
phytoplankton biomass does not change when Chl-a quenching takes place (Roesler 2014).
To avoid such superfluous effect of Chl-a measurements on actual phytoplankton biomass, the
average of the reported night time values of Chl-a (every 15 minutes during the period from 9pm
to 5am on the following day, Fig. 39) are used to represent the actual Chl-a concentration
throughout the year (Appendix F). Figure 39 shows the relation between Chl-a measurements
during the day and their average values during the night hours.
In addition to the effect of Chl-a quenching on in-situ measurements of phytoplankton, the
vertical migration of phytoplankton cells by certain species capable of active movement during
65
-------
the day time may also impact the in-situ measurements. Phytoplankton migration is triggered by
irradiance in the PAR range (Gerbersdorf and Schubert 2011). This downward migration of the
cells is a precaution against possible damage by excessive light. In return, upward migration of
the cells may take place during the night time, which can increase phytoplankton biomass there.
This phenomenon has not been considered in this modeling effort and it may have contributed to
the underestimation of predicted peaks of Chi-a concentrations (e.g., Fig. 31C).
66
-------
Dinofl age Hates Diatoms Greens All
50
45
zr 40
35
c~ 30
o
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time {day)
Dinoflagellates Diatoms Greens All
^ : .
30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
Figure 38. Effect of removing direct loads from WWTPs on Chl-« concentration.
(A) With WWTPs, (B) Without WWTPs. Note vertical scale difference.
67
-------
NPI
• Chl-a
- Night Average Chl-a
¦ Day Avg Chl-a
40
35
rH
rsl
m
LD
i£»
r-
CO
cn
o
H
-
r-
r>-
r*-
r*-
h-
r**
r-
r-
r>-
r*-
r-
Date and time (day)
Figure 39. Daily variation of Chl-fl surface concentration at station NPI during July 2009.
68
-------
7. Summary and Conclusion
This work fulfilled the stated main objective (section 1.2) by predicting the 3-D transport and
concentration of the following 20 water quality state variables in NB1:
1) dinoflagellate algae
2) diatom algae
3) green algae
4) refractory particulate organic carbon
5) labile particulate organic carbon
6) dissolved carbon
7) refractory part, organic phosphorus
8) labile particulate organic phosphorus
9) dissolved organic phosphorus
10) total phosphate
11) refractory part, organic nitrogen
12) labile part, organic nitrogen
13) dissolved organic nitrogen
14) ammonium nitrogen
15) nitrate nitrogen
16) particulate biogenic silica
17) dissolved available silica
18) chemical oxygen demand
19) dissolved oxygen
21) fecal coliform bacteria
The same coarse grid was used to predict both hydrodynamics (water surface elevation and
velocity) and the transport of the water quality state variables. This report presented model
predictions with the horizontal and vertical behavior of DO and Chi-a to illustrate hypoxia in the
Bay. Available data were used to force, calibrate, and validate the model. The results indicated
that the predicted concentrations were compatible with expected behavior and observations. The
information and parameterization of the model were such that the impact of WWTPs, which
directly discharge into the Bay, on Chl-a concentration was significant. The model showed the
impact of point-source loadings from WWTPs on hypoxia and indicated that hypoxic events
were reduced, but they could still appear without such direct loads. Observations of Chl-a in
1 The reader is reminded that Mohamed's original intent was to provide a proof of the concept of applying EFDC to
simultaneously model hydrodynamics and water quality in Narragansett Bay. In spite of the fact that Mohamed
was not able to complete his goal of further refinement and validation of the modeling effort, this report shows
that ecologically plausible results can be achieved with EFDC.
69
-------
Greenwich Bay indicated the importance of considering spatial variability of water quality
parameters within some regions in NB.
7.1. Future work
Many improvements would be included in this work to consider the following:
• More calibration and refining of all model parameters would be necessary to support
model predictions for future decision making.
• The impact of defining accurate time series of concentrations at the open boundary
should not be underestimated.
• More refining of non-point source loads (i.e., dry and wet atmospheric deposition) would
be important for better predictions.
• Include macro-algae and total active metals in future simulations
• The impact of future changes to population demography and density could affect loadings
from the watershed.
• Impact of global warming might be considered as it would increase water temperature at
the seaward open boundary and the temperatures of all river inflows (assumed similar to
air temperature) throughout the year.
• Impact from sea-level rise on water quality parameters would affect water depth, water
volume, constituent concentrations, and light penetration.
70
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73
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Appendix A: Point-source loading from WWTPs
74
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Appendix A presents time series graphs of point-source loadings from the ten WWTPs into NB.
Nitrogen components (NO2, NO3, NH3, and DON) were measured only during May-October,
2009 at Fields Pt. In this work, NO3+NO2 are referred to as NO3.
N03+N02
-Bristol
Fields Pt.
1000
900
800
700
% 600
BO
=1 500
¦c
§ 400
300
200
100
0
12/18/2008
-BucklinPt. —A- E.Greenwich )< E. Providence X Fall R.
Jamestown —— QuonsetPt. — Warren —Newport
3/18/2009 6/16/2009 9/14/2009 12/13/2009
Date
Figure Al. Non-point source loadings for NO3 + NO2.
¦Bristol
Fields Pt.
-Bucklin Pt.
Jamestown
NH3
E. Greenwich
QuonsetPt.
-E. Providence -
Warren
Fall R.
Newport
2500
2000
1500
¦c
§ 1000
500
12/18/2008
3/18/2009
6/16/2009
9/14/2009
12/13/2009
Date
Figure A2. Non-point source loadings for NH3.
75
-------
DON
~ Bristol —¦— Bucklin Pt. —A- E. Greenwich —X—E. Providence —Fall R.
—Fields Pt. —i- Jamestown —— QuonsetPt. — Warren —~- Newport
800
700
600
3 300
200
100
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009
Date
Figure A3. Non-point source loadings for dissolved organic nitrogen.
TP
Bristol ¦ Bucklin Pt. -A- E. Greenwich >( E. Providence x Fall R.
Fields Pt. —i- Jamestown —- QuonsetPt. — Warren —Newport
350
300
250
200
aa
150
100
50
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009
Date
Figure A4. Non-point source loadings for total phosphorus.
76
-------
0
12/18/2008 3/18/2009 6/16/2009 9/14/2009 12/13/2009
Date
CBOD
Bristol
Fields Pt.
Bucklin Pt.
Jamestown
E. Greenwich
QuonsetPt.
E. Providence
Warren
Fall R.
Newport
6000
5000
„ 4000
¦b
ae
3000
03
o
"¦ 2000
1000
Figure A5. Non-point source loadings for chemical oxygen demand.
FCB
1.00E+12
1.00E+11
2 1.00E+10
•o 1.00E+09
ns
o
1.00E+08
1.00E+07
- Bristol
-Fall R.
-Warren
¦Bucklin Pt.
¦ Fields Pt.
-Newport
-E. Greenwich •
-Jamestown ¦
-Somerset
- E. Providence
-Quonset Pt.
f
J
—1
CTl
O
Date
Figure A6. Non-point source loadings for fecal coliform bacteria.
77
-------
Appendix B: Dissolved oxygen concentration in riverine inflow
78
-------
Concentration of dissolved oxygen in freshwater inflow through the eight rivers and the riparian
area (Table 1) is set at 70% of its saturation concentration, which depends on water temperature
and atmospheric pressure. Freshwater temperature was set equal to air temperature, as
represented by a sin-wave (Abdelrhman, 2015). The following procedure was used to calculate
the concentration of dissolved oxygen in freshwater (APHA, 1985).
d n* d r^-0^01
UP ~ U r [ (i-pw)(i-0) J
Where
Op = equilibrium oxygen concentration (mg L"1) at any pressure,
P = pressure (atm) and is within 0.000 to 2.000 atm
0 = 0.000975 - (1.426 x lO-5*;) + (6.436 x lO-8*;2) , where t = temperature (°C)
Pwv = partial pressure of water vapor (atm) calculated from:
PWV = exp [11.8571 - pSS2) - where
T = temperature (°K), where T = t + 273.15 and t within 0.0 to 40.0°C.
O* = equilibrium oxygen concentration (mg L"1) at a pressure of 1.000 atm, calculated from:
O* = exp
/1.575701 x 105\ /6.642308 x 107\ /1.2438 x 101QN
-139.3441 + - +
T I \ T2 / \ T3
'8.621949 X 1011N
79
-------
Appendix C: Values of water quality parameters used for
Narragansett Bay
80
-------
Values are grouped in card-image format for FORTRAN input file (WQ3DWC.inp) to EFDC
model. Card images are separated by "C " which is followed by another card with the
number of the card, e.g., "C08". Values of parameters are reported in Tables 3-1 to 3-7 in Cerco
and Cole (1994) and presented by Park et al. (1995). The text in each title card (e.g. C08) states
the table number in the mentioned references for the parameters that follow. Some parameters
are set at a value of 0.0 until their values become available.
Value
Parameter Description CR28
C08 constant parameters for ALGAE (see Table 3-1)
KHNc nitrogen half-saturation for dinoflagellates (mg/L) 0.02
KHNd nitrogen half-saturation for algae diatoms (mg/L) 0.02
KHNg nitrogen half-saturation for algae greens algae (mg/L) 0.02
KHNm nitrogen half-saturation for macroalgae (mg/L) 0.01
KHP phosphorus half-saturation for dinoflagellates (mg/L) 0.001
KHPd phosphorus half-saturation for algae diatoms (mg/L) 0.001
KHPg phosphorus half-saturation for algae greens algae (mg/L) 0.001
KHPm phosphorus half-saturation for macroalgae (mg/L) 0.001
KHS silica half-saturation for algae diatoms (mg/L) 0.035
STOX salinity at which microsystis growth is halved for cyanobacteria N/A
C09 constant parameters for ALGAE (see Table 3-1)
KeTSS light extinction for total suspended solids (1/m per g/m3) 0.4
KeCHL light extinction for total suspended chlorophyll (1/m per g/m3) -0.29
CChlc carbon-to-chlorophyll ratio for dinoflagellates (mg / ug Chi) 0.06
CChld carbon-to-chlorophyll ratio for algae diatoms (mg / ug Chi) 0.06
CChlg carbon-to-chlorophyll ratio for algae greens (mg / ug Chi) 0.04
CChlm carbon-to-chlorophyll ratio for macroalgae (mg / ug Chi) 0.06
DOPTc optimal depth (m) for dinoflagellates growth 1
DOPTd optimal depth (m) for algae diatoms growth 1
DOPTg optimal depth (m) for algae greens growth 1
DOPTm optimal depth (m) for macroalgae growth 1
C10 constant parameters for ALGAE (see Table 3-1)
10 initial solar radiation (Langley/day) at water surface 280
IsMIN minimum optimum solar radiation (Langley/day) 40
FD fraction of day that is daylight 0.5
Cla weighting factor for solar radiation at current day 0.7
Clb weighting factor for solar radiation at (-1) days 0.2
CIc weighting factor for solar radiation at (-2) days 0.1
CIm not used 0.7
Rea global reaeration adjustment factor (NOT USED) 0.8
PARadj solar radiation multiplied by this factor to get the PAR 0.43
Cll constant parameters for ALGAE (see Table 3-1)
TMcl lower optimal temperature for dinoflagellates growth (C) 18
81
-------
Value
Parameter
Description
CR28
TMc2
upper optimal temperature for dinoflagellates growth (C)
22
TMdl
lower optimal temperature for algae diatoms growth (C)
12
TMd2
upper optimal temperature for algae diatoms growth (C)
15
TMgl
lower optimal temperature for algae greens growth (C)
23
TMg2
upper optimal temperature for algae greens growth (C)
25
TMml
lower optimal temperature for macroalgae growth (C)
20
TMm2
upper optimal temperature for macroalgae growth (C)
22
TMpl
lower optimal temperature for diatom predation (C)
8
TMp2
upper optimal temperature for diatom predation (C)
20
C12 constant parameters for ALGAE (see Table 3-1)
KTG1
suboptimal temperature effect coef. for dinoflagellates growth
0.008
KTG2
superoptimal temperature effect coef. for dinoflagellates growth
0.008
KTGld
suboptimal temperature effect coef. for algae diatoms growth
0.008
KTG2d
superoptimal temperature effect coef. for algae diatoms growth
0.008
KTGlg
suboptimal temperature effect coef. for algae greens growth
0.008
KTG2g
superoptimal temperature effect coef. for algae greens growth
0.008
KTGlm
suboptimal temperature effect coef. for macroalgae growth
0.001
KTG2m
superoptimal temperature effect coef. for macroalgae growth
0.001
KTGlp
suboptimal temperature effect coef. for diatom predation growth
0.0001
KTG2p
superoptimal temperature effect coef. for diatom predation growth
0.0001
C13 constant parameters for ALGAE (see Table 3-1)
TRc
reference temperature for dinoflagellates metabolism (C)
20
TRd
reference temperature for algae diatoms metabolism (C)
20
TRg
reference temperature for algae greens metabolism (C)
20
TRm
reference temperature for macroalgae metabolism (C)
20
KTBc
temperature effect coef. for dinoflagellates metabolism
0.069
KTBd
temperature effect coef. for algae diatoms metabolism
0.069
KTBg
temperature effect coef. for algae greens metabolism
0.069
KTBm
temperature effect coef. for macroalgae metabolism
0.069
C14 constant parameters for CARBON (see Table 3-2)
FCRP
carbon distribution coef. for algae predation: refractory POC
0.35
FCLP
carbon distribution coef. for algae predation: labile POC
0.55
FCDP
carbon distribution coef. for algae predation: DOC
0.1
FCDc
carbon distribution coef. for dinoflagellates metabolism
0
FCDd
carbon distribution coef. for algae diatoms metabolism
0
FCDg
carbon distribution coef. for algae greens metabolism
0
KHRc
half-sat. constant (g02/m3) for dinoflagellates DO excretion
0.5
KHRd
half-sat. constant (g02/m3) for algae diatoms DO excretion
0.5
KHRg
half-sat. constant (g02/m3) for algae greens DO excretion
0.5
C15 constant parameters for CARBON (macroalgae)
FCRPm
carbon distribution coef. for macroalgae predation: refractory POC
0.25
82
-------
Value
Parameter Description CR28
FCRPm carbon distribution coef. for macroalgae predation: labile POC 0.25
FCRPm carbon distribution coef. for macroalgae predation: DOC 0.5
FCDm carbon distribution coef. for macroalgae metabolism 0.1
KHRm half-sat. constant (gCh/m3) for macroalgae DO excretion 0.5
C16 constant parameters for CARBON (see Table 3-2)
KRC minimum dissolution rate (1/day) of refractory POC 0.005
KLC minimum dissolution rate (1/day) of labile POC 0.05
KDC minimum dissolution rate (1/day) of DOC 0.07
KRCalg constant relating refractory PO dissolution rate to total chl a 0
KLCalg constant relating labile PO dissolution rate to total chl a 0
KDCalg constant relating DO dissolution rate to total chl a 0
KDCalgm constant relating DO dissolution rate to macroalgae 0
C17 constant parameters for CARBON (see Table 3-2)
TRHDR reference temperature for hydrolysis (C) 20
TRMNL reference temperature for mineralization (C) 20
KTHDR temperature effect constant for hydrolysis 0.069
KTMNL temperature effect constant for mineralization 0.069
KHORDO oxi respiration half-sat. constant for D.O. (g02/m3) 0.5
KHDNN half-sat. constant for denitrification (gN/m3) 0.1
AANOX ratio of denitrification rate to oxi DO respiration rate 0.5
C18 constant parameters for PHOSPHORUS (see Table 3-3)
FPRP phos. distribution coef. for algae predation: refractory POP 0.1
FPLP phos. distribution coef. for algae predation: labile POP 0.2
FPDP phos. distribution coef. for algae predation: DOP 0.5
FPIP phos. distribution coef. for algae predation: Inorganic P 0.2
FPR phos. distribution coef. of RPOP for dinoflagellates metabolism 0
FPRd phos. distribution coef. of RPOP for algae diatoms metabolism 0
FPRg phos. distribution coef. of RPOP for algae greens metabolism 0
FPLc phos. distribution coef. of LPOP for dinoflagellates metabolism 0
FPLd phos. distribution coef. of LPOP for algae diatoms metabolism 0
FPLg phos. distribution coef. of LPOP for algae greens metabolism 0
C19 constant parameters for PHOSPHORUS (macroalgae)
FPRPM phos. distribution coef. for macroalgae predation: RPOP 0.4
FPLPM phos. distribution coef. for macroalgae predation: LPOP 0.4
FPDPM phos. distribution coef. for macroalgae predation: DOP 0.1
FPIPM phos. distribution coef. for macroalgae predation: Inorganic P 0.1
FPRm phos. distribution coef. of RPOP for macroalgae metabolism 0.2
FPLm phos. distribution coef. of LPOP for macroalgae metabolism 0.3
APCM factor to modify AP for macroalgae 0.5
C20 constant parameters for PHOSPHORUS (see Table 3-3)
FPDc phosphorus distribution coef. of DOP for dinoflagellates metabolism 1
83
-------
Value
Parameter Description CR28
FPDd phosphorus distribution coef. of DOP for algae diatoms metabolism 1
FPDg phosphorus distribution coef. of DOP for algae greens metabolism 1
FPDm phosphorus distribution coef. of DOP for macroalgae metabolism 1
FPIc phosphorus distribution coef. of P4T for dinoflagellates metabolism 0
FPId phosphorus distribution coef. of P4T for algae diatoms metabolism 0
FPIg phosphorus distribution coef. of P4T for algae greens metabolism 0
FPIm phosphorus distribution coef. of P4T for macroalgae metabolism 0
KP04p partition coefficient for sorbed/dissolved P04 2
C21 constant parameters for PHOSPHORUS (see Table 3-3)
KRP minimum hydrolysis rate (1/day) of RPOP 0.005
KLP minimum hydrolysis rate (1/day) of LPOP 0.04
KDP minimum hydrolysis rate (1/day) of DOP 0.05
KRPalg constant relating hydrolysis rate of RPOP to algae 0
KLPalg constant relating hydrolysis rate of LPOP to algae 0
KDPalg constant relating hydrolysis rate of DOP to algae 0.2
CPprml constant used in determining algae Phos-to-Carbon ratio 42
CPprm2 constant used in determining algae Phos-to-Carbon ratio 85
CPprm3 constant used in determining algae Phos-to-Carbon ratio 200
C22 constant parameters for NITROGEN (see Table 3-4)
FNRP nitrogen distribution coef. for algae predation: RPON 0.35
FNLP nitrogen distribution coef. for algae predation: LPON 0.55
FNDP nitrogen distribution coef. for algae predation: DON 0.1
FNIP nitrogen distribution coef. for algae predation: Inorganic N 0
FNRc nitrogen distribution coef. of RPON for dinoflagellates metabolism 0
FNRd nitrogen distribution coef. of RPON for algae diatoms metabolism 0
FNRg nitrogen distribution coef. of RPON for algae greens metabolism 0
FNLc nitrogen distribution coef. of LPON for dinoflagellates metabolism 0
FNLd nitrogen distribution coef. of LPON for algae diatoms metabolism 0
FNLg nitrogen distribution coef. of LPON for algae greens metabolism 0
C23 constant parameters for NITROGEN (MACROALGAE)
FNRPM nitrogen distribution coef. for macroalgae predation: RPON 0.4
FNLPM nitrogen distribution coef. for macroalgae predation: LPON 0.5
FNDPM nitrogen distribution coef. for macroalgae predation: DON 0.1
FNIPM nitrogen distribution coef. for macroalgae predation: Inorganic N 0
FNRm nitrogen distribution coef. of RPON for macroalgae metabolism 0.2
FNLm nitrogen distribution coef. of LPON for macroalgae metabolism 0.4
C24 constant parameters for NITROGEN (see Table 3-4)
FNDc nitrogen distribution coef. of DON for dinoflagellates metabolism 1
FNDd nitrogen distribution coef. of DON for algae diatoms metabolism 1
FNDg nitrogen distribution coef. of DON for algae greens metabolism 1
FNDm nitrogen distribution coef. of DON for macroalgae metabolism 1
84
-------
Value
Parameter Description CR28
FNIc nitrogen distribution coef. of DIN for dinoflagellates metabolism 0
FNId nitrogen distribution coef. of DIN for algae diatoms metabolism 0
FNIg nitrogen distribution coef. of DIN for algae greens metabolism 0
FNIm nitrogen distribution coef. of DIN for macroalgae metabolism 0
ANCc nitrogen-to-carbon ratio for dinoflagellates 0.167
ANCd nitrogen-to-carbon ratio for algae diatoms 0.167
ANCg nitrogen-to-carbon ratio for algae greens 0.167
ANCm nitrogen-to-carbon ratio for macroalgae 0.167
C25 constant parameters for NITROGEN (see Table 3-4)
ANDC mass N03 reduces per DO oxidized (gN/gC) 0.933
rNitM maximum nitrification rate (gN/m3/day) 0.05
KHNitDO nitrification half-sat. constant for D.O. 1
KHNitN nitrification half-sat. constant for NH4 1
TNit reference temperature for nitrification (C) 27
KNitl suboptimal temperature effect constant for nitrification 0.0045
Knit2 superoptimal temperature effect constant for nitrification 0.0045
C26 constant parameters for NITROGEN (see Table 3-4)
KRN minimum hydrolysis rate (1/day) of RPON 0.002
KLN minimum hydrolysis rate (1/day) of LPON 0.04
KDN minimum hydrolysis rate (1/day) of DON 0.05
KRNalg constant relating hydrolysis rate of RPON to algae 0
KLNalg constant relating hydrolysis rate of LPON to algae 0
KDNalg constant relating hydrolysis rate of DON to algae 0.05
C27 constant parameters for SILICA (see Table 3-5)
FSPP silica distribution coef. for diatom predation 1
FSIP silica distribution coef. for diatom predation 0
FSPd silica distribution coef. for diatom metabolism 1
FSId silica distribution coef. for diatom metabolism 0
ASCd silica-to-carbon ratio for algae diatoms 0.36
KSAp partition coef. for sorbed/dissolved SA for TSS 0.16
KSU dissolution rate (1/day) of particulate silica (PSi) 0.05
TRSUA reference temperature (C) for PSi dissolution 20
KTSUA temperature effect on PSi dissolution 0.092
C28 constant parameters for COD & DO (see Table 3-6)
AOCR stoichiometry algae oxygen-to-carbon ratio (g02/gC) 2.67
AONT stoichiometry algae oxygen-to-nitrate ratio (g02/gN) 4.33
KRO reaeration constant (3.933 for O'Connor-Dobbins; 5.32 for Owen-Gibbs) 3.933
KTR temperature rate constant for reaeration 1.024
KHCOD oxygen half-saturation constant for COD decay (mg/L O2) 1.5
KCD COD decay rate (per day) 1
TRCOD reference temperature for COD decay (C) 20
85
-------
Value
Parameter Description CR28
KTCOD temperature rate constant for COD decay 0.041
AOCRpm macroalgae photosynthesis oxygen-to-carbon ratio 2.67
AOCRrm macroalgae respiration oxygen-to-carbon ratio 2.67
C29 constant parameters for TAM & FCB (see Table 3-7)
KHbmf D.O. concentration where TAM release is half the anoxi rate 0.5
BFTAM anoxi release rate of TAM (mol/m2/day) 0.1
Ttam reference temperature for TAM release (C) 20
Ktam temperature effect constant for TAM release 0.2
TAMdmx TAM solubility at anoxi conditions (mol/m3) 0.015
Kdotam constant relating TAM solubility to D.O. 1
KFCB first-order fecal coliform bacteria decay rate (1/day) 0.5
TFCB temperature effect constant for KFCB decay rate 1.07
C45 spatially/temporally constant ALGAL PARAMETERS
PMc max. growth rate for dinoflagellates (1/day) 3
PMd max. growth rate for algae diatoms (1/day) 2.6
PMg max. growth rate for algae greens (1/day) 2.85
PMm max. growth rate for macroalgae (1/day) 0
BMRc basal metabolism rate for dinoflagellates (1/day) 0.14
BMRd basal metabolism rate for algae diatoms (1/day) 0.14
BMRg basal metabolism rate for algae greens (1/day) 0.14
BMRm basal metabolism rate for macroalgae (1/day) 0
PRRc predation rate on dinoflagellates (1/day) 0.035
PRRd predation rate on algae diatoms (1/day) 0.035
PRRg predation rate on algae greens (1/day) 0.03
PRRm predation rate on macroalgae (1/day) 0
Keb background light extinction coefficient (1/m) 0.38
C46 spatially/temporally constant SETTLING VELOCITIES
WSc settling velocity for dinoflagellates (m/day) 0.5
WSd settling velocity for algae diatoms (m/day) 0.5
WSg settling velocity for algae greens (m/day) 0.15
WSrp settling velocity for refractory POM (m/day) 0.2
WSip settling velocity for labile POM (m/day) 0.2
WSs settling velocity for particles sorbed to TAM (m/day) 0.1
WSM settling velocity for macroalgae (m/day) 1
REAC reaeration adjustment factor 0.8
86
-------
Appendix D: Validation of DO time series
87
-------
Appendix D presents comparisons between predicted and observed time series of DO
concentration near the surface and bottom at all buoy stations (NBC-RIDEM).
Pred Surf DO
PD Surface DO
-Otas Surf DO Chronic DO Acute DO
_ 20
^ 18
ao 16
14
| 12
S 10
i 8
V a
o 6
c
o 4
u
O
Q
= ,ll
ffi=l
m
m
J.il
ll III
iLu
klMLLZ\
¦¦¦ill
liiiua
J^gj
oo
o
O
o
O
N tD m ul ^
*—I t—I rH t—l
\ \ "v. v,
Ln t£» r>* co 16
-14
.9 12
2 10
u 4
O 2
00
o
en
o
en
o
en
o
ID ID LT)
T—I T—I T—I
\ \ \
<£> r-» oo
Date
m m <-vj
(B)
Figure D-l. Predicted and observed DO concentrations at the surface (A)
and bottom (B) at station PD.
88
-------
Pred Surf DO
CP Surface DO
¦Otas Surf DO Chronic DO Acute DO
20
^ 18
ap 16
¦S 14
c
.2 12
2 10
4->
£ 8
c 6
o
u 4
° 9
O 2
00
o
o
O
o
co co r-j
•Pred Bot DO
id ;£> Ln
*—I rH t—l
r-- oo
Date
CP Bottom DO
-Otas Bot DO Chronic DO Acute DO
14
12
10
¦= 8
E 4
O 2
00
o
O
O
O
^ Ln
*—I rH t—l
\
r-* oo
Date
co co
-------
Pred Surf DO
GB Surface DO
¦Otas Surf DO Chronic DO Acute DO
ao 16
2 10
GB Bottom DO
Pred Bot DO
-Obs Bot DO
Chronic DO
Acute DO
18
16
jjp 14
c" 12
¦3 io
^ H
u 6
^SBr
oo
o
o
o
O
id Ln
*—I rH t—l
\
r>* oo
Date
O
rH
rri* cnJ
-------
Pred Surf DO
SR Surface DO
¦Otas Surf DO Chronic DO Acute DO
20
^ 18
ao 16
14
o 12
ro 10
8
6
4
2
0
00
o
00*
r—I
fN
O
O
O
id t£» Ln
*—I rH t—l
"V. "V.
r- oo
Date
O
rH
rri* cnJ
r-* oo
Date
O
rH
rri* cnJ
-------
Predicted
BR Surface DO
¦Otas Surf DO Chronic DO Acute DO
20
~ 18
_l
tiO 16
14
.2 12
2 10
8
6
4
2
0
c
0)
o
c
o
u
O
O
00
o
o
O
o
^ ;£> Ln
*—I rH t—l
"V. "V.
r-- oo
Date
O
rH
rri* cnJ
O
o
o
id t£» Ln
*—I rH t—l
\
r>* oo
Date
O
rH
rri* cnJ
-------
20
5;18
— PredSurf [
NPI Surface DO
)0 Obs Surf DO Chronk
DO
Acute DC
ftp 16
¦S 14
c
.2 12
2 10
£ 8
c 6
o
o 4
§ 2
gj
0
00
o
00*
T—1
H
Ln
T—1 T—1
f- co
e
\
0 \\\N^"Nh"NhVNVN>'>'>VN
-------
Pred Surf DO
PP Surface DO
¦Otas Surf DO Chronic DO Acute DO
20
~ 18
i
ao 16
14
.1 12
2 10
8
6
4
2
0
i
Srfm, lh,
I
i jb
1 1
\ML.
JMJk
AL
Lim
it,
/¦W
¦
Wf
r
I 1
oo
o
o
O
o
id t£» Ln
*—I rH t—l
r- oo
Date
ro m cnJ
¦ Pred Bot DO
PP Bottom DO
¦Otas Bot DO Chronic DO Acute DO
14
12
10
~ 8
§ 4
o
O 2
o
w
00
o
o
O
id Ln
*—I rH t—l
\
r-* oo
Date
CPi o
O
>
m (N
t—I rH
Figure D-7. Predicted and observed DO concentrations at the surface (A)
and bottom (B) at station PP.
94
-------
20
_ 18
1j 16
£ 14
c 12
¦B io
TO
£ 8
c
8 6
o 4
U 2
0
MV Surface DO
•PredSurfDO ObsSurfDO Chronic DO Acute DO
cocncncncncncncncncncpicpicpio
OOOOOOOOOOOOOrH
oor^uDCor^r^uDuDLj-i^^romrNj
t—It—It—It—It—It—It—It—It—It—ItHt—It—It—I
">\"V'VN^"nh'nhvnvn>'>Nvn
\\\N^"Nh"NhVNVN>'>'>VN
r--co
-------
QP1 Surface DO
Pred Surf DO
¦Otas Surf DO
Chronic DO
Acute DO
20
~ 18
i
eo 16
14
.1 12
2 10
£ 8
u 4
° 7
Q l
0
00
O
O
O
O
id Ln
*—I rH t—l
"V. "V.
r- oo
Date
O
rH
rri* cnJ
O
o
id t£» Ln
*—I rH t—l
\
r-* oo
Date
CPi o
O
>
m (N
t—I rH
Figure D-9. Predicted and observed DO concentrations at the surface (A)
and bottom (B) at station QP1.
96
-------
Pred Surf DO
TW Surface DO
-ObsSurfDO Chronic DO Acute DO
20
^ 18
g) 16
•S 14
c
.2 12
2 10
8
6
4
2
0
c
0)
o
c
o
u
O
O
00
o
o
O
o
^ ;£> Ln
*—I rH t—l
r-- oo
Date
co co r-j
(A)
TW Bottom DO
14
no
£
12
10
¦§ 8
E 6
O
O
O
id t£» Ln
*—I rH t—l
\
r-* oo
Date
co co
-------
Pred Surf DO
MH Surface DO
-Otas Surf DO Chronic DO Acute DO
20
~ 18
i
ao 16
14
.2 12
2 10
S 8
£ 6
3 4
O
o
00
o
O
O
O
id Ln
*—I rH t—l
r-- oo
Date
co m c-j
(A)
Pred Bot DO
MH Bottom DO
-ObsBotDO Chronic DO Acute DO
14
12
10
~ 8
£ 4
O 2
——
00
o
o
O
O
id t£» Ln
*—I rH t—l
\
r-* oo
Date
ro m cnJ
(B)
Figure D-ll. Predicted and observed DO concentrations at the surface (A)
and bottom (B) at station MH.
98
-------
20
^ 18
ap 16
¦S 14
c
.2 12
2 10
£ 8
c 6
o
u 4
° 7
Q 2
0
GD Surface DO
•PredSurfDO ObsSurfDO Chronic DO Acute DO
"y
cocncncncncncncncncncpicpicpio
OOOOOOOOOOOOOrH
oor^uDCor^r^uDuDLj-i^^romrNj
t—It—It—It—It—It—It—It—It—ItHtHt—It—It—I
•>\hv'VN^^'nhvnvn>'>'>vn
-------
Appendix E: Validation of DO Profiles
100
-------
Appendix E presents comparisons between predicted and observed DO profiles (Insomniacs
data, Prell et al. 2015).
MV 6/18/2009 10:13 AM
Obs DO Pred DO
Concentration (mg L*1)
0 2 4 6 8 10 12
MV 7/15/2009 11:26 AM
ObsDO Pred DO
Concentration (mg l-1)
0 1 2 3 4 S
& 7 8 9
2
/ j
2
?
£ 6
5.
OJ
Cl
a
10
12
i"
-£ 6
Q.
«
Q
8
10
12
MV 7/23/200911:23 AM
ObsDO Pied DO
Concentration (mg L A)
2 3 4 5
E,
¦5 6
MV 8/4/2009 11:27 AM
ObsDO Prod DO
Concentration (mg L x}
MV 8/13/2009 11:08 AM
ObsDO Pred DO
Concentration (mg L1)
01234S67S
MV 9/1/2009 11:51AM
Obs DO Pred DO
Concentration (mg L1)
0123456789
2
4
£
&
a.
V
o
3 1
I
/
7
4
f
f 6
a.1
Q
\
—— r
10
12
1
i
10
12
/
Figure E-l. Predicted and observed DO profiles at station MV.
101
-------
o 10
13
QPl 6/18/2009 8:39 AM
ObsDO PredDO
Concentration (mg L')
4 6 8
o 10
1?
QPl 7/15/2009 12:14 PM
Obs DO PredDO
Concentration (mg L ')
2 3 4 5 6
O jo
12
QPl 7/23/2009 12:18 PM
ObsDO PredDO
Concentration (mg L1)
3 4 5 6 7
S
V
o 10
12
14
16
QPl 8/4/2009 12:31PM
Obs DO Pied DO
Concentration {mg L1}
3 4 S 6
QPl 8/13/2009 12:04 PM
Obs DO Pred DO
Concentration (mg L"1}
2 3 4 5
QPl 9/1/2009 12:48 PM
ObsDO PredDO
Concentration (mgL-1)
3 4 5
Figure E-2. Predicted and observed DO profiles at station QPl.
102
-------
CP 8/13/2009 10:19 AM
Obs 00 Pied DO
Concentration (mg l:1)
23456789
CP 6/18/2009 10:16 AM
Obs DO Pred DO
Concentration {mg L"1)
4 6 8 10 12
CP 7/23/2009 10:12 AM
ObS DO Pred DO
Concentration (mg L"1)
4 6 8 10
CP 7/15/2009 10:22 AM
ObS DO Pred DO
Concentration (mg Il)
2 4 6 3 10
CP 8/4/2009 10:12 AM
Obs DO Pred 00
Concentration (mg L *)
123456789
CP 9/1/2009 9:49 AM
Obs DO Pred 00
Concentration (mg l1)
1 2 3 4 5 6 7
Figure E-3. Predicted and observed DO profiles at station CP.
103
-------
0
2
4
£
6
.e
8
9_
O
10
12
14
16
NPI 6/18/2009 9:07 AM
Obs LXJ PredDO
Concentration (mg L'1)
3 4 5 6 7
NPI 7/15/2009 9:44 AM
Obs DO PredDO
Concentration (mg L"1}
4 6
NPI 7/23/20099:35 AM
Obs DO Pred DO
Concentration (mg L1)
0 1 2 3 4 5 6
7 8 9
2
I 1 : JJ
I ^
S 8
G.
flf
Q 10
12
14
16
-------
PD 6/18/2009 8:07 AM
Qbs DO PredDO
Concentration (mg L1)
2
_ 3
Ma
-C
5
u 11
O
6
7
PD 7/15/2009 7:47 AM
ObsDO Fred DO
Concentration (mg Lx)
2 3 4 5
2
3
I4
Q
6
7
PD 7/23/2009 7:45 AM
ObsDO PredDO
Concentration (mg I'1)
2 3 4 S
PD 8/4/2009 7:52 AM
-ObsDO PredDO
Concentration (rng Ll)
2 3 4 S
PD 8/13/2009 7:56 AM
ObsDO Pied DO
Concentration (mg L"1)
2
3
I4
f 5
Q
6
7
8
9
PD 9/1/2009 8:05 AM
ObsDO PredDO
Concentration (mg L*1)
2 3 4 5
Figure E-5. Predicted and observed DO profiles at station PD.
105
-------
SR 6/18/2009 12:06 PM
Obs DO PredDO
Concentration (mg L1)
4 6 8
2
3
I4
.e
Cl C
OJ
Cl
S
7
SR 7/15/2009 9:11 AM
Obs DO Pred DO
Concentration (mg l"1)
3 4 5
SR 7/23/2009 9:16 AM
Obs DO PredDO
Concentration (mg I"1)
1
2
_ 3
£1
SR 8/4/2009 10:12 AM
Obs DO Pied DO
Concentration (mg L1)
4 6 8
Cl c
oj
Q
6
SR 8/13/2009 9:58 AM
Obs DO Pred DO
Concentration (mg L*1)
! 3 4 S
SR 9/1/2009 9:43 AM
Obs DO Pied DO
Concentration (mg L"1)
3 4 S
Figure E-6. Predicted and observed DO profiles at station SR.
106
-------
GB 6/8/2009 11:15 AM
Obs 00 Pred 00
Concentration (mg Lrl)
3 4 5 6
J
2
3
£4
b
a
6
GB 7/15/2009 9:01 AM
Obs DO Pred DO
Concentration (mg l*1)
2 3 4 5
-L
2
3
-C
5
GB 7/23/2009 8:59 AM
Obs DO Pred DO
Concentration (mg 1rl)
2 3 4 5
S" &
Q
6
?
GB 8/4/2009 9:11 AM
Obs DO Pred DO
Concentration {mg L*1)
3 4 5 6
GB 9/1/2009 8:53 AM
Obs DO Pred DO
Concentration (mg l1)
2 3 4
g- 5
a
6
7
8
Figure E-7. Predicted and observed DO profiles at station GB.
107
-------
I10
a.
as ir
O
20
TW 6/18/2009 8:15 AM
Gbs DO Pred 00
Concentration (rug LJ)
3 4 S 6 7
E 10
TW 7/15/2009 11:59 AM
Obs DO Pred DO
Concentration (mg L"1)
3 4 5
s
"e io
Q.
g is
20
TW 7/23/2009 12:04 PM
Obs DO Pred DO
Concentration (rng L*}
I 3 4 S 6
5
I 10
a.
S is
20
25
TW 8/4/2009 12:19 PM
Obs DO Pred DO
Concentration (mg L'1)
2 3 4 5 6
0
5
I 10
a.
® ir
Q l->
20
TW 8/13/2009 11:48 AM
Ob$ DO Pred DO
Concentration (mg Ll)
2 3 4 S
I10
Q.
£ 15
20
TW 9/1/2009 12:35 PM
Obs DO Pted DO
Concent rat ion (mg I *)
Figure E-8. Predicted and observed DO profiles at station TW.
108
-------
PP 6/18/2009 8:44 AM
PP 7/15/2009 9:25 AM
ObsDO Pred DO
Obs DO Pred DO
Concentration (mg L'1)
Concentration (mg l1)
0 123456789 10
0 2 4 6
10 12
J I
( )
5
%
s— •
£ 6
«
Q
10
10
1?
12
PP 7/23/2009 9:22 AM
ObsDO Pred DO
Concentration (mg L lJ
0123456789
PP 8/4/2009 9:10 AM
ObsDO Pred DO
Concentration (mg L lJ
312345678*
2
4
?
£ 6
0
o
8
2
4
E,
•£ 6
8
o
10
10
12
12
PP 8/13/2009 9:06 AM
PP 9/1/2009 9:36 AM
Concentration (mg I'1}
Concentration {mg L1)
Figure E-9. Predicted and observed DO profiles at station PP.
109
-------
BR 6/18/2009 9:54 AM
ObsDO Pred DO
BR 7/15/2009 9:57 AM
Obs DO Pred DO
Concentration (mg L1)
Concentration (rng L
BR 7/23/2009 9:52 AM
BR 8/4/2009 9:52 AM
Concentration (rng Ll)
Concentration (mg L"1)
BR 8/13/2009 9:45 AM
BR 9/1/2009 9:35 AM
Concentration (mg L l)
Concentration (rng L1)
Figure E-l 0. Predicted and observed DO profiles at station BR.
110
-------
Appendix F: Validation of Chl-a time series
111
-------
Appendix F presents comparisons between predicted and observed time series of Chi-a
concentration near the surface at all buoy stations (NBC-RIDEM).
60
1j
50
W)
40
c
o
4->
30
4->
c
o
in
o
O
o
rH
r--
00
oT
O
rH
Date
CO
rH
fN
O
rH
(N
Figure F-l. Predicted and observed surface Chl-« concentrations at station PD.
¦ Pre d Chla
60
^ 50
CtD
3- 40
c
0
30
03
1 20
(_>
c
o 10
0
CP Surface Chl-a
- Obs Night Chla Obs Daily Avg Chl-a • Profiles
00
o
rH
ro
rH
ro
rH
"
rH
oT
rH
Figure F-2. Predicted and observed surface Chl-« concentrations at station CP.
112
-------
GB Surface Chl-a
• Pred Chla
o 10
Obs Night Chla
-Obs Daily Avg Chla
Date
Figure F-3. Predicted and observed surface Chl-« concentrations at station GB.
45
-p
40
CtD
35
30
c
o
25
'To
i—
20
¦»—»
C
ld
rH
rH
rH
r-
00
G)
Date
rH
O"
m
rH
In
o
rH
-------
BR Surface Chl-a
• Pred Chla
Obs Night Chla
-Obs Daily Avg Chla
• Profiles
80
ST 70
50 60
^ 50
o
40
ro
g 30
o>
20
c
o
u 10
00
o
Date
Figure F-5. Predicted and observed surface Chl-a concentrations at station BR.
NPI Surface Chl-a
Pred Chla Obs Night Chla Obs Daily Avg Chla • Profiles
45
40
_l
35
30
C
o
25
4->
CO
1—
20
c
r-- oo cn o
Date
Figure F-6. Predicted and observed surface Chl-« concentrations at station NPI.
114
-------
35
" 30
^ 25
I 20
¦*->
£ 15
c
^ 10
u
c
o
u
•Pred Chla
PP Surface Chl-a
— Obs Night Chla Obs Daily Avg Chla
00
o
T—1
LO
rH
tH
>
rH
ro
rH
ro
rH
CnT
r—1
rH
C\l
ro
LO
r--
00
oT
O*
rH
>
rH
fN
rH
Date
Figure F-7. Predicted and observed surface Chl-« concentrations at station PP.
30
25
W)
3 20
c
0
~ 15
ro
1 10
u
c
° 5
u 3
0
0
c
0
r
««¦
r
r
— PredChla
MV Surface Chl-a
— Obs Night Chla Obs Daily Avg Chla
•
Profiles
•
1
A
J
L
M
\l,
u i
w
if
wp
m
\
J
r
i
Vr i
"I w
r» c
5 r
o* r
H r
^ ;
H
D
H
--
si
H
H
0 (J) \ \ s
o r-» (£» o
H rH rH r
¦> ^ *"
M rH 0s! cti
D O O C
o r-- r—
H rH rH
0 ^ LT)
h
H rH
•X -
d r^
Date
.1/ 1 »/ u»
9/14/09
10/14/09
11/13/09
Figure F-8. Predicted and observed surface Chl-« concentrations at station MV.
115
-------
QP1 Surface Chl-a
•Pred Chla
- Obs Night Chla
-Obs Daily Avg Chla
• Profiles
c
a>
u
c
o
u
18
16
14
12
10
8
6
4
2
0
00
o
o
O
o
o
O
o
O
(j)
o
00
T—i
r-
T—1
U3
T—1
00
T—1
r-
T—1
r*-
T—1
T—1
T—1
LO
rH
CnT
r—1
T—1
C\l
ro
LO
00
ro
ro
fN
i—1
T—1
T—1
T—1
Date
Figure F-9. Predicted and observed surface Chl-« concentrations at station QP1.
35
30
^ 25
0 20
¦*->
1 15
S io
c
o
<-> 5
0
•Pred Chla
MH Surface Chl-a
— Obs Night Chla Obs Daily Avg Chla
00
o
G\
O
O
G\
O
G\
o
O
ro
ro
fN
rH
rH
rH
rH
Figure F-10. Predicted and observed surface Chl-« concentrations at station MH.
116
-------
• Pred Chla
12
10
8
6
4
2
0
GD Surface Chl-a
Obs Night Chla Obs Daily Avg Chla • Profiles
00
o
O
G\
O
en
o
G\
o
G\
O
O
O
00
T—i
r--
T—1
U3
T—1
00
T—1
r--
T—1
r--
T—1
U3
T—1
rH
CnT
r—1
T—1
C\l
ro
LO
r-
LO
T—I
CO
"it
tH
(j)
cn
cn
O
o
o
o
rH
>
ro
ro
fN
rH
T—1
rH
rH
Date
Figure F-ll. Predicted and observed surface Chl-« concentrations at station GD.
117
-------
Appendix G: Validation of Chl-a profiles
118
-------
Appendix G presents comparisons between predicted and observed Chl-a profiles (personal
communication: Candace Oviatt and Heather Stoffel URI-GSO, Narragansett, RI).
NPI 6/1/2009 10:46 AM
Obs Chl-a Pred Chl-a
NPI 6/10/2009 11:31 AM
Obs Chl-a Pred Chl-a
Concentration (ng LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (ng LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
0
1
2
3
4
5
E 6
r 7
Q. 8
a>
Q 9
10
11
12
13
14
15
0
1
2
3
4
5
E 6
r 7
Q. 8
ai
Q 9
10
11
12
13
14
15
1
c
J
1
x
//
f
/
\
(
(
(
NPI 6/25/2009 10:44 AM
Obs Chl-a Pred Chl-a
NPI 7/10/2009 11:20 AM
Obs Chl-a IPred Chl-a
Concentration {|ag L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration {|ag L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
0
1
2
3
4
5
E 6
r 7
o. 8
ai
O 9
10
11
12
13
14
15
0
1
2
3
4
5
E 6
r 7
o. 8
ai
Q 9
10
11
12
13
14
15
" —
L
V
1
)
119
-------
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
NPI 7/22/2009 10:50 AM NPI 8/3/2009 10:40 AM
Obs Chl-a Pred Chl-a Obs Chl-a Pred Chl-a
Concentration (ng L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (ng LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
NPI 8/20/2009 11:36 AM
CP 6/1/2009 10:02 AM
-Obs Chl-a
— Pred Chl-a
-Obs Chl-a
Pred Chl-a
Concentration (|ag L
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (|ag L
0 2 4 6 8 1012 141618 20 22 24 26 28 30
0
1
2
3
4
5
E 6
r ^
Q. 8
a>
Q 9
10
11
12
13
14
15
120
-------
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
CP 6/10/2009 10:25 AM CP 6/25/2009 9:51 AM
Obs Chl-a Pred Chl-a Obs Chl-a Pred Chl-a
Concentration (ng LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
0
1
2
3
4
5
£ 6
r ^
Q. 8
a>
O 9
10
11
12
13
14
15
Concentration (ng L
0 2 4 6 8 1012 141618 20 22 24 26 28 30
CP 7/10/2009 10:20 AM
Obs Chl-a Pred Chl-a
Concentration (|ag L
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (|ag L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
CP 7/22/2009 10:04 AM
Obs Chl-a Pred Chl-a
121
-------
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
CP 8/3/2009 10:02 AM
CP 8/20/2009 10:52 AM
—Obs Chl-a
Pred Chl-a
-Obs Chl-a
Pred Chl-a
Concentration (ng LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (ng L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
BR 6/1/2009 9:16 AM BR 6/10/2009 9:41 AM
—Obs Chl-a
— Pred Chl-a
-Obs Chl-a
Pred Chl-a
Concentration (|ag L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (|ag LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
122
-------
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
BR 6/25/2009 9:13 AM
BR 7/10/2009 9:37 AM
Concentration (ng LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
—Obs Chl-a
Pred Chl-a
-Obs Chl-a
Pred Chl-a
Concentration (ng L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
BR 7/22/2009 9:26 AM BR 8/3/2009 9:20 AM
-Obs Chl-a
— Pred Chl-a
-Obs Chl-a
Pred Chl-a
Concentration (|ag L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (|ag LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
123
-------
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
BR 8/20/2009 10:14 AM MV 6/9/2009 8:15 AM
—Obs Chl-a
Pred Chl-a
-Obs Chl-a
Pred Chl-a
Concentration (ng LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
0 2
Concentration (ng LJ)
4 6 8 1012 141618 20 22 24 26 28 30
MV 6/24/2009 9:35 AM
Obs Chl-a Pred Chl-a
MV 7/13/2009 9:06 AM
Obs Chl-a Pred Chl-a
Concentration (|ag LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (|ag LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
>
s
/
)
t
/
/
1
0
1
2
3
4
5
£ 6
r ^
Q. 8
a>
~ 9
10
11
12
13
14
15
124
-------
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
MV 7/20/2009 8:27 AM
MV 8/5/2009 9:40 AM
—Obs Chl-a
Pred Chl-a
-Obs Chl-a
Pred Chl-a
Concentration (ng LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (ng L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
MV 8/24/2009 10:36 AM QP1 6/9/2009 7:36 AM
-Obs Chl-a
— Pred Chl-a
-Obs Chl-a
Pred Chl-a
Concentration (|ag L1)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
Concentration (|ag LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
125
-------
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
QP1 6/24/2009 8:50 AM
QP1 7/13/2009 8:26 AM
-Obs Chi
-a -
- Pred Chl-a
-Obs Chi
-a
- Pred Chl-a
Concentration (ng L"
l)
Concentration (|ag L"
0 2 4 6 8 1012 141618 20 22 24 26 28 30
0 2 4 6 8 1012 141618 20 22 24 26 28 30
ri
1
1
2
3
4
5
6
7
8
I
)
5
f
r
(
i
*
'
\
/
/
/
(
i
_s=
S"
Q
9
10
11
12
13
14
15
QP1 7/20/2009 7:39 AM
QP1 8/5/2009 9:01 AM
-Obs Chi
-a -
- Pred Chl-a
-Obs Chi
-a
- Pred Chl-a
Concentration (ng L"
Concentration (|ag L"
0 2 4 6 8 1012 141618 20 22 24 26 28 30
0 2 4 6 8 1012 141618 20 22 24 26 28 30
ri
1
1
2
3
4
5
6
7
8
s
f
V
/
/
)
/
S
(
L
J
'
r
>
_S=
/
r
c
S"
f
Q
9
10
11
12
13
14
15
126
-------
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
QP1 8/24/2009 8:54 AM
Obs Chl-a Pred Chl-a
Concentration (ng LJ)
0 2 4 6 8 1012 141618 20 22 24 26 28 30
127
-------
Appendix H: Sample of model result
128
-------
The following results are for the contemporary case with current loads from WWTPs. The
predictions are presented for all layers at all stations during the year 2009. The parameter
description and its output name are presented in the following table.
Parameter
Printout Name
1) dinoflagellates (Be)
CHC
2) diatom algae (Bd)
CHD
3) green algae (Bg)
CHG
4) refractory particulate organic carbon (RPOC)
ROC
5) labile particulate organic carbon (LPOC)
LOC
6) dissolved carbon (DOC)
DOC
7) refractory particulate organic phosphorus (RPOP)
ROP
8) labile particulate organic phosphorus (LPOP)
LOP
9) dissolved organic phosphorus (DOP)
DOP
10) total phosphate (P04)
P4D
11) refractory particulate organic nitrogen (RPON)
RON
12) labile particulate organic nitrogen (LPON)
LON
13) dissolved organic nitrogen (DON)
DON
14) ammonium nitrogen (NH4)
NHX
15) nitrate nitrogen (NO3)
NOX
16) particulate biogenic silica (SU)
suu
17) dissolved available silica (SA)
SAA
18) chemical oxygen demand (COD)
COD
19) dissolved oxygen (DO)
DOX
20) total active metal (TAM)
Not modeled
21) fecal coliform bacteria (FCB)
FCB
22) macro algae (Malg)
Not modeled
129
-------
Dinoflagellates
Diatoms
iwmL
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
130
-------
Greens
Time (day)
0.07
0.06
m 0.05
£ 0.04
O
2 0.03
c
<11
£ 0.02
o
u
0.01
0.00
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
ROC
131
-------
LOC
o.io
0.09
Time (day)
DOC
0.45
0.40
T—t
j_l
0.35
E
0.30
c
o
0.25
2
0.20
?¦
i
QJ
0.15
C
O
0.10
u
0.05
0.00
0 30
60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
132
-------
P4D
0.0014
_ 0,0012
H
_l
od 0.0010
= 0,0008
o
| 0.0006
c
« 0.0004
o
U 0.0002
0.0000
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
ROP
0.0014
_ 0.0012
T—I
_l
od 0.0010
£ 0.0008
o
2 0.0006
c
£ 0.0004
o
U 0,0002
0,0000
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
133
-------
LOP
0.0450
0.0400
5? 0.0350
0J3
0.0300
g 0.0250
2 0.0200
S 0.0150
<_>
o 0.0100
u
0.0050
0.0000
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
0,0600
~ 0.0500
J-l
CUD
0.0400
c
3 0.0300
TO
1—
5 0.0200
<_>
c
o
u 0.0100
0.0000 L-1 1 5 =—5
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
134
-------
0.0120
~ 0.0100
ftD
£ 0.0080
c
B 0.0060
TO
i
4-^
S 0.0040
(j
c
o
u 0.0020
0.0000
RON
) 30 60 90 120 150 180 210 240 270 300 330 360 390
i irne taayj
1 DM
0.0180
0.0160
1? 0.0140
<50
£ 0.0120
g 0.0100
2 0.0080
S 0.0060
o 0.0040
0.0020
0.0000
Li
) 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
135
-------
DON
0.6000
— 0.5000
1j
0D
E 0.4000
c
¦£ 0.3000
(T5
*->
£ 0.2000
<_>
c
o
u 0.1000
0.0000
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
NHX
0.7000
0.6000
H
w> 0.5000
E
<= 0.4000
o
2 0.3000
e
£ 0.2000
o
u 0.1000
0.0000
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
136
-------
0.7000
___ 0.6000
H
GD 0.5000
£
c 0.4000
o
2 0.3000
£
£ 0.2000
o
U 0.1000
0.0000
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
NOX
SUU
0.3000
— 0.2500
1j
OD
E 0.2000
c
¦£ 0.1500
ro
i_
4->
S o.iooo
u
c
O
u 0.0500
0.0000
30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
137
-------
SAA
6.0000
~ 5.0000
4,0000
c
$ 3.0000
CD
¦H'
S 2.0000
<_>
c
o
u 1.0000
0.0000
30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
COD
0.2000
0.1800
1—1
0.1600
—1
00
E
0.1400
c
0.1200
o
0.1000
2
c
0.0800
ID
U
0.0600
C
o
0.0400
0.0200
0.0000
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
138
-------
DOX
16.0000
14.0000
12.0000
10.0000
8.0000
c 6.0000
4.0000
u
2.0000
0.0000
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
FCB
o
o
c
o
u
45,000,000
40,000,000
35,000,000
30,000,000
25,000,000
20,000,000
15,000,000
10,000,000
5,000,000
0
0 30 60 90 120 150 180 210 240 270 300 330 360 390
Time (day)
139
------- |