&EPA
United States
Environmental Protection
Agency
EPA/600/R-16/195 August 2016
www.epa.gov/ord
Modeling Total Suspended Solids (TSS)
Concentrations in Narragansett Bay
Layerl
• Laye r6
Layer2
-Layer?
TSS at CP
Layer3
Laye r8
•Laye r4
•Deposition
• Layers
Office of Research and Development
National Health and Environmental Effects Research Laboratory
-------
-------
vvEPA
United States EPA/600/R-16/195 | August 2016
Environmental Protection . ,
Agency www.epa.gov/ord
Modeling Total Suspended Solids (TSS)
Concentrations in Narragansett Bay
by
Mohamed A. Abdelrhman
U.S. Environmental Protection Agency
Atlantic Ecology Division
NHEERL, ORD
27 Tarzwell Drive
Narragansett, RI 02882 USA
National Health and Environmental Effects Research Laboratory
Office of Research and Development
Narragansett, RI 02882 USA
-------
DISCLAIMER
This document is a preliminary draft. It has not been formally released by the U.S.
Environmental Protection Agency and should not at this stage be construed to represent Agency
policy. It is being circulated for comments on its technical merit and policy implications.
Although the material described here has been funded by the U.S. Environmental Protection
Agency, it has not been subject to Agency-level review and therefore does not necessarily reflect
the views of the Agency, nor does mentioning trade names or commercial products endorse or
recommend them. This report has the Tracking Number ORD-017732 of USEPA Office of
Research and Development, National Health and Environmental Effects Research Laboratory,
Atlantic Ecology Division.
-------
CONTENTS
DISCLAIMER ii
FIGURES v
TABLES vii
ACKNOWLEDGMENTS viii
1. Introduction 1
1.1. General Definitions 1
1.1.1. Water clarity 1
1.1.2. Turbidity 1
1.1.3. Total suspended solids 2
1.1.3.1. Types of suspended particles 2
1.1.3.1.1. Living organic particles 2
1.1.3.1.2. Nonliving organic particles 3
1.1.3.1.3. Mineral (non-organic) particles 3
1.1.3.2. Quantifying types of TSS from field measurements 4
1.2. Objectives 4
1.3. Approach 5
2. Data 9
2.1. Bed Sediment Data 9
2.2. Total Suspended Sediment Data 9
2.3. Inferences from available sediment data 10
2.4. Environmental conditions in 2009 11
3. Model equations 14
4. Model setting 16
4.1. Initial Conditions 16
4.2. Boundary Conditions 16
4.2.1. Bed 16
4.2.2. Point sources 17
4.2.3. Seaward open boundary 17
4.3. Time step 17
5. Calibration and validation 20
6. Results 22
7. Concluding remarks 31
-------
References: 33
Appendix A. Bed Sediment 36
Appendix B. TSS Concentration in Riverine Flow 40
Appendix C: TSS Concentration in WWTPs Flow 44
Appendix D: TSS Concentration in the Bay 47
D.I. AED TSS data in 2014-2015 47
D.2. Collins TSS data in 1973 56
D.S.Morton TSS data in 1965 59
D.4. Schenck and Davis data in 1971 61
D.5. Oviatt and Nixon data in 1972-1973 62
Appendix E. Input files 63
Appendix F: Input parameters for the EFDC model 64
Appendix G: Predicted TSS results for Narragansett Bay 70
IV
-------
FIGURES
Figure 1. Schematic representation of the various types of suspended particulates and their modeling
status in this work 7
Figure 2. Map of Narragansett Bay showing main point sources from WWTPs and major rivers together
with locations of observation stations for hydrodynamics 8
Figure 3. Time series of wind energy in 2009 12
Figure 4. Time series of precipitation in 2009 12
Figure 5. Time series of total freshwater discharge in 2009 13
Figure 6. Tide elevation showing spring-neap tides during 2009 13
Figure 7. Cohesive sediment processes 15
Figure 8. Distribution of sediments on the bed: 19
Figure 9. Predicted TSS mineral concentration and the range of observations (1.3-2.6 mg L"1) at station
CP 21
Figure 10. Test Casel: loading from bed only 25
Figure 11. Test Case 2: loading from open boundary only 25
Figure 12. Test Case 3: loading from rivers only with: (A) settling speed 3xlO"5 m s"1 and (B) settling
speed 6xlO"5 m s"1 26
Figure 13. Test Case 4: loading from all sources 27
Figure 14. Vertical profiles of TSS for Cases 1-4 on day 16 at time 00:00 hour 27
Figure 15. Effect of Spring-Neap tide on resuspension periods 28
Figure 16. Effect of tide levels on TSS concentration at station CP. Layer 1 is at the bottom and Layer 8 is
at the surface 28
Figure 17. Effect of river discharge on TSS concentration at station PR. Layer 1 is at the bottom and
Layer 8 is at the surface 29
Figure 18. Predicted average TSS concentrations and net deposition at stations along the West Passage. 29
Figure 19. Predicted average TSS profiles at stations along the West Passage (see Fig. 2 for station
locations) 30
Figure 20. Overall average phytoplankton and its carbon from field observations in 2009 32
Figure A-l. Locations of 493 bed sampling stations (McMasterl960) 36
Figure A-2. Sediments of Narragansett Bay 37
Figure A-3. The percent distribution of bed sediment on the bed of Narragansett Bay:
(A) sand, (B) silt, (C) clay, and (D) gravel 38
Figure B-l. NBC River stations for TSS, used for loading estimates in 2009 41
Figure B-2. Reported time series of TSS concentrations in all rivers in 2009 42
Figure B-3. Adjusted time series of TSS concentrations all rivers in 2009 42
Figure C-l. WWTPs with direct discharge to the Bay 44
-------
Figure C-2. The time series of organic particle concentrations from all WWTPs in 2009 45
Figure D-l. Locations of sampling stations in Narragansett Bay 48
Figure D-2. Time series of the observed average TSS concentrations 49
Figure D-3. The vertical trend of the observed TSS concentrations at the surface, middle,
and bottom of the water column during the summer months (June, July, and August): 50
Figure D-4. Histograms of observed TSS concentrations: 51
Figure D-5. Detritus concentration from 48 samples during each winter month (November
and December) of 2014 and 2015 52
Figure D-6. Observed TSS concentration and spring-neap tide: 53
Figure D-7. Station locations for TSS measurements in lower Narragansett Bay 56
Figure D-8. Longitudinal TSS concentrations in the West Passage from mid-Bay (stations
W 1,2,3) to the Bay mouth 58
Figure D-9. Stations for TSS data reported by Morton (1967) 59
Figure D-10. Stations for turbidity measurements (Schenck and Davis 1973) 61
Figure D-ll. Stations for deposition from Oviatt and Nixon (1975) 62
Figure G-l. Predicted TSS concentration and sediment deposition at station PD 70
Figure G-2. Predicted TSS concentration and sediment deposition at station PR 70
Figure G-3. Predicted TSS concentration and sediment deposition at station BR 71
Figure G-4. Predicted TSS concentration and sediment deposition at station CP 71
Figure G-5. Predicted TSS concentration and sediment deposition at station NPI 72
Figure G-6. Predicted TSS concentration and sediment deposition at station MV 72
Figure G-7. Predicted TSS concentration and sediment deposition at station QP1 73
Figure G-8. Predicted TSS concentration and sediment deposition at station GD 73
Figure G-9. Predicted TSS concentration and sediment deposition at station GB 74
Figure G-10. Predicted TSS concentration and sediment deposition at station SR 74
Figure G-ll. Predicted TSS concentration and sediment deposition at station PP 75
Figure G-12. Predicted TSS concentration and sediment deposition at station TW 75
Figure G-13. Predicted TSS concentration and sediment deposition at stationNP 76
Figure G-14. Predicted TSS concentration and sediment deposition at station MH 76
VI
-------
TABLES
Table 1. Types of TSS Particulates contributing to water clarity 6
Table 2. Calibration parameters 18
Table 3. Contribution of TSS by each source on January 16, 2009 24
Table 4. Summary of TSS predictions at all stations 24
Table A-l. Statistical parameters of bed samples based on observations in Narragansett Bay.... 39
Table B-l. Statistical parameters of reported TSS concentrations (mgL"1) 43
Table B-2. Statistical parameters of the adjusted TSS concentrations (mg L"1) 43
Table C-l. Statistical parameters for TSS concentrations from eleven WWTPs (mg I/1)3 46
Table D-1. Station locations for TSS samples collected by AED in 2014-2015 54
Table D-2. General statistical parameters from AED observations of suspended sediment
concentrations (mgL"1) in Narragansett Bay in 2014-2015 54
Table D-3. Statistical parameters of overall mean TSS concentrations (mg L"1) at surface,
middle, and bottom of the water column 55
Table D-4. Statistical parameters of background detritus concentration (mg L"1) from the
watershed and the water column 55
Table D-5. Measured TSS concentration from Collins (1976) 57
Table D-6. Statistical parameters for surface and bottom TSS concentrations (mg L"1) from
Collins (1976) 58
Table D-7. TSS concentrations reported by Morton (1967) 60
Table D-8. Statistical parameters for TSS concentrations (mg L"1) collected by Morton 60
VII
-------
ACKNOWLEDGMENTS
The author offers respect and gratitude to the late Dr. John Hamrick (Tetra Tech, Inc.) for
providing the executables for EFDC and the templates for sediment transport input files. The
author thanks Ms. Roxanne Johnson (USEPA-AED) for providing total suspended sediment data
as well as the field team (led by Dr. Richard McKinney and Mr. Donald Cobb) who collected the
data. The author thanks the in-house reviewers of this report, including Drs. Dan Campbell,
Jason Grear, Richard McKinney (USEPA-AED) for their technical reviews, insights, and
constructive comments.
VIM
-------
1. Introduction
This work covers mechanistic modeling of suspended particulates in estuarine systems with
an application to Narragansett Bay, RI. Suspended particles directly affect water clarity and
attenuate light in the water column (Abdelrhman 2016b). Water clarity affects both
phytoplankton and submerged aquatic vegetation (SAV), which control primary production
in estuarine systems.
This report is not intended as a comprehensive review of suspended particulates in estuarine
systems. The report presents a very brief background about suspended solids which helps
interpret their in-situ measurements and understand the logic behind modeling their behavior
under various environmental conditions.
Assumptions are made to highlight gaps in knowledge and theory and their impact on the
presented modeling analysis and results. These assumptions resemble facts that are practiced
in the fields of total suspended solids and water clarity. They are standard, usually because of
observations and analytical limitations. These assumptions are numbered throughout the text
and they are summarized in the conclusion section.
The organization of the report includes this introductory chapter with general definitions,
objectives, and approach. Chapter 2 introduces sediment data for Narragansett Bay. A reduced
set of the general model equations are presented in Chapter 3. Chapter 4 covers the model setting
with all initial conditions, boundary conditions, and time step for the year 2009. Model
calibration and validation are presented in Chapter 5. Chapter 6 includes a sample of model
results for the year 2009. The conclusions are included in Chapter 7. Due to the extensive
information in the report, most of the data tables, figures, and modeling results are presented
in Appendices A-G.
1.1 .General Definitions
Total suspended solid (TSS) can impact water clarity and reduce light availability, which affects
the health of algal and aquatic vegetation (Blom and Duin 1994). Total suspended solids are
defined differently by various researchers and organizations based on their interest. Before
proceeding to define TSS for Narragansett Bay (or the Bay), general definitions of relevant terms
are presented below.
1.1.1. Water clarity
Water clarity is a physical characteristic of how transparent water is. Clarity is determined by
the depth to which sunlight penetrates in water, which is also known as the photic zone. Water
clarity is usually measured with a Secchi disk (Wernerd 2010). The clearer the water, the deeper
the photic zone and the greater is the potential for photosynthetic production. Water clarity is
directly related to water turbidity.
1.1.2. Turbidity
Turbidity is a measure of transparency (clarity) of water. The transparency of water is indicated
by the amount of sunlight available at any depth. Turbidity is affected by total suspended solids
-------
(TSS) and colored dissolved organic matter (CDOM). Water turbidity can be measured with
a turbidity meter which depends on light transmission in the water (USEPA 1993).
1.1.3. Total suspended solids
Total suspended solids (TSS) include the dry weight of any drifting or floating particles in the
water with size >2 um including nonorganic (mineral) particles (i.e., clay, silt, and sand) and
organic particles (i.e., living plankton as well as nonliving decomposing organic materials)
(Fig. 1). The cutoff size (2 um) indicates the available minimum filter size to separate TSS.
Assumption 1: Particles <2 fjm (colloids) are ignored in the calculation of TSS. Table 1
summarizes the various types of suspended particles that can exist in a water body (e.g.,
Narragansett Bay) and their modeling status in this work.
1.1.3.1. Types of suspended particles
The total suspended solids (TSS) include different types of particulates from different origins
including the watershed, the open sea, and the bed of the estuary (Noel et al. 1995). Figure 1
presents a schematic diagram for the various components of TSS at various levels of realizations
in the water column (for water clarity), on the filter as dried particles, on the filter as combusted
(ashed) particles, and their treatment in the presented model. The two major categories of TSS
are organic, TSS0, and mineral, TSSm, particles. Gallegos et al. (2000) indicated that particulate
organic carbon can include living phytoplankton, TSSoi, bacteria, heterotrophic plankton and
their decomposition (dead) products including organic detritus from marshes and terrestrial
communities as well as detritus resuspended from decomposing SAV beds. Contributions from
all dead particulates are included in TSSod in Fig. 1. The type of particle defines its behavior with
respect to: (1) settling velocity, (2) entrainment and resuspension from the bed, and (3) impact on
water clarity and light attenuation. Modeling these behaviors is critical to identifying the TSS
concentration and its biogeochemical impact on the environment. The following categories may
be used to identify the behavior of the various particles.
1.1.3.1.1. Living organic particles
Living particles consist of various groups of phytoplankton (algae particles), TSSoip
(Fig. 1). These particles contain Chl-a which has pigment that absorbs light in the water
column. These particles can grow in any type of water (rivers, lakes, estuaries, and open
ocean) when the limiting factors (i.e., temperature, nutrients, light, salinity, and oxygen)
are favorable. These particles can only be loaded to a water body through exchanges
across the shared open boundaries with rivers and the open sea. In addition to light
absorption, these particles can also affect the scattering of light in the water column.
The mass concentration of phytoplankton particles can be modeled with mechanistic
water quality models (Abdelrhman 2016a).
Other living particles include zooplankton, TSSoiz (Fig. 1), but their population
concentration is very small compared to phytoplankton in Narragansett Bay (~1
zooplankton cell to 105 phytoplankton cells, Martin 1970, Hulsizer 1976). The reported
annual average dry weight of zooplankton has the same order of magnitude as
phytoplankton (60 ug L"1, Hulsizer 1976). Nonetheless, zooplankton have swim-ability
and they can avoid being captured in the usual field sampling bottles (see Appendices B,
-------
C, and D) (personal communication: Richard McKinney, The United States
Environmental Protection Agency (USEPA)-Atlantic Ecology Division (AED)). Unlike
phytoplankton, the contribution of zooplankton to light attenuation in the water column is
expected to be small and they are not considered as an inherent water property due to
their sparseness in the water column. Assumption 2: Contribution of zooplankton
particles to TSS is considered to be insignificant.
1.1.3.1.2. Nonliving organic particles
Nonliving (dead) organic particles, TSSod (Fig. 1), consist of the following three major
subgroups which can affect both the absorption and scattering of light in the water
column. Assumption 3: Nonliving organic particles have nopigmented Chl-a. The mass
concentration of nonliving organic particles can be obtained from field measurements or
from mechanistic water quality models (Abdelrhman 2016a).
a) Dead phytoplankton particles. These particles result from the death of living
phytoplankton. Their concentration can be parameterized based on the
respective living phytoplankton. These particles can be transported between
various waters (similar to living phytoplankton). Such particles are assumed
to lose their pigmented Chl-a content shortly after their death and their light
attenuation is based on the particles without pigment.
b) Fecal pellets. These particles result from predation on phytoplankton and
detritus and their concentration can be parameterized accordingly (assuming
that the grazing rate is known).
c) Detritus. As dead plants and organisms decay, small organic particles break
away and enter the water column as suspended solids, which are referred to
here as "detritus". These particles can also originate in the watershed before
being transported and loaded into the water body through rivers, streams,
other open boundaries, and surface runoff water. Dead organisms, carcasses,
and human waste (e.g., from waste water treatment plants (WWTPs)) can
contribute to detritus. Nonetheless, except for dead phytoplankton inferred as
a general proportion from living cells, other detrital organic particulates are
not quantitatively known, except from field samples. Assumption 4: Detrital
organic particulates from non-phytoplankton origins are either ignored or
inferred from field observations. In this work, detritus concentration is
inferred from field samples.
1.1.3.1.3. Mineral (non-organic) particles
Non-organic particles originate from erosion and scour of bed material and land. They
are classified as mineral particles, TSSm (Fig. 1). Mineral particles in the sand size range
(64 um - 2 mm), TSSms (Fig. 1), are considered to be non-cohesive. All clay and silt
particles (also called "mud"), TSSmm (Fig. 1), are non-organic and considered to be
cohesive particles (Table 1) as described below.
-------
Clay is a fine-grained sediment with a typical grain size less than 4um and to the family
of minerals that has similar chemical compositions and common crystal structural
characteristics (Velde 1995, p.8-42). The main mineral groups of clays are kaolinite,
montmorillonite, illite, and chlorite. There are approximately 30 different types of "pure"
clays (based on their crystal structure) in these categories, but most "natural" clay
deposits are mixtures of these different types, along with other weathered minerals.
Clay and silt particles possess electro-magnetic properties which %h bind the grains
together to give a bulk strength or cohesion (CIRIA 1996). This process is called
"flocculation" which takes place when the dispersed phase of a colloid (i.e., mud)
forms discrete particles which are capable of settling out from the dispersion medium
(i.e., water). Flocculation is almost inevitably a result of a colloidal solution (e.g., river
discharge) mixing with a solution containing electrolytes, e.g., sea water.
Settling speed as well as erosion and deposition behaviors of cohesive and non-cohesive
particles are treated differently. Cohesive particles aggregate to form larger particles with
higher settling velocities which pull particles out from the water column, reduce turbidity,
and improve water clarity. This process is a result of the electric charges on the surface of
cohesive particles (clay and silt). Salt ions can enhance this process, which is the reason
why oceans and estuaries tend to have lower turbidity (higher clarity) than lakes and
rivers. The mass concentration of cohesive particles can be mechanistically modeled as
presented in this work.
1.1.3.2. Quantifying types of TSS from field measurements
The laboratory methods to quantify TSS include three major steps (ICES 2004, see also DRAFT
National Estuarine Research Reserve System Standard Operating Procedure for Measurement of
Total Suspended Solids and Volatile Suspended Solids in Water, Personal communication
Roxanne Johnson, USEPA-AED) (see Fig. 1): (1) filtering a known volume (usually 1 liter) of
the collected water sample to separate the suspended solids, (2) drying the filter with the TSS in
100-105°C oven for 24 hour until a constant weight is reached to obtain the combined dry weight
(mg L"1) of both minerals, TSSmm, and dried organic particles (TSS0iP)dry and (TSSod)dry; (3)
Combusting the filter with the dry weights in a 450°C furnace for 4 hours to ash organics and
obtains only the weight of minerals (TSSmm mg L"1). In summary, wet particulates in the water
column include both minerals and undried organics, dry particulates include minerals and dried
organics, and combusted particles include minerals from mineral particulates (e.g., silt, and clay)
and a minute amount of minerals from organics (e.g., silicate from diatom particles). Assumption
5_: Minerals from organic origin are considered to be negligible. The TSSmm is alternately
referred to as cohesive sediment by the model used in this report.
1.2. Objectives
The main objective of this work is to demonstrate that the Environmental Fluid Dynamics Code
(EFDC) model is capable of predicting sediment processes and TSS in estuarine systems. The
specific objective is to present methods to model the TSS concentrations in Narragansett Bay in
both space and time throughout the full year of 2009, as a prototype for future implementation to
other systems.
-------
1.3. Approach
The TSS composition and concentration are site specific because, as discussed above, they
originate from watershed detritus and soil erosions (urban, agricultural, forest), industrial and
wastewater treatment plants (WWTPs) discharges, and plankton and algae growth in the system.
To mechanistically model TSS, the suspended mineral particulates, TSSm, have to be predicted
in the system using a physical model, and the organic particulates (e.g., phytoplankton) have to
be predicted with a biogeochemical water quality model (see Abdelrhman 2016a). The
contribution of combusted phytoplankton particles to the mineral particles is very small and may
be inferred as a ratio from the predicted phytoplankton concentration otherwise it is assumed to
introduce a negligible error (see assumption 5 above).
TSS in Narragansett Bay enters the Bay as point sources from eight rivers and eleven WWTPs
and as bed sediment resuspension into the overlying water column (Fig. 2). The benthic sediment
acts as a huge reservoir of particulates which can contribute to TSS loading when they are
entrained by the flowing water.
Modeling TSSm in Narragansett Bay can cover the two major types of particulates: cohesive
mud, TSSmm, which includes clay and silt particles, and non-cohesive sand particles, TSSms.
These two types of particles exist in both the water column and in bed sediment. The description
in the EFDC for the suspended and bedded sediment process model is very extensive (Tetra Tech
2007). For reader convenience and for completeness, a brief description is presented here for
modeling TSSmm. The EFDC hydrodynamic model (Abdelrhman 2015) includes the sediment
modules to predict both the cohesive and non-cohesive particulates in the water column and on
the bed. Nonetheless, only cohesive sediment, TSSmm, is considered in this work for
Narragansett Bay.
The process of calibration and validation of model results did not include any field monitoring
programs. Only existing historical data were used (Appendixes A-D).
-------
Table 1. Types of TSS Particulates contributing to water clarity.
(ISO 2002, see also https://en.wikipedia.org/wiki/Grain_size)
Particulate
Phytoplankton
Detritus
WWTP
Very fine sanda
Silt
Clay
Colloids
Size range
(|im)
N/A
N/A
N/A
62.5-125
3.9-62.5
<3.9
< 1
Cohesive"5
N/A
N/A
N/A
N
Y
Y
N/A
Organic"5
Y
Y
Y
N
N
N
N/A
Living"5
Y
N
N
N
N
N
N/A
Modeled
Yc
N
N
N
Y
Y
N
a All size classes of sand are not included in the TSS for Narragansett Bay
b Y = Yes, N=No, N/A = Not applicable
c Modeled in Abdelrhman (2016a)
-------
In Water
On Filter
(dried)
On Filter
(ashed)
Modeled
< 2 jam
No
TSS
TSSm TSS0
TSS0| TSSod
TSSmm TSSms TSSolp TSS0|Z
T^ Not (TSS,)H Not (TSS )
1 jomm r. i V ' -'-Jolp/dry f. ,\> -"od/drv
mm confirmed confirmed
TSS Minerals Minerals
only on|V
Yes |\|0 NO No No
>62.5 jam
No
Figure 1. Schematic representation of the various types of suspended particulates and their
modeling status in this work. Subscripts m = mineral, o = organic, mm = mineral mud,
ol = organic living, od = organic dead, ms = mineral sand, olp = organic living phytoplankton
(modeled in Abdelrhman 2016a), olz = organic living zooplankton
-------
-71°20'
-7T101
41°
501'
41°
40'"
41°
30''
*as*%' /
\\ 1PD
!*
PR
Providence 2*
6 Km
Figure 2. Map of Narragansett Bay showing main point sources from WWTPs and major rivers
together with locations of observation stations for hydrodynamics (Abdelrhman 2015).
Observation stations include: PR=Providence River, CP=Conimicut Point, GB=Greenwich Bay,
TW=T-Wharf, FRl,2=Fall River, NP=Newport, TFG=T.F. Green Airport, GD=URI Graduate
School URI/GSO, QPl,2=Quonset Point, PD=Phillipsdale, BR=Bullock Reach, SR=Sally Rock,
NPI=N. Prudence Island, PP=Poppasquash Point, MV=Mount View, MH=Mount Hope Bay);
and WWTPs include: l=Bucklin Point, 2=Fields Point, 3=E. Providence, 4=Warren, 5=Bristol,
6=Fall River, 7=Newport, 8=Jamestown, 9=Quonset Point, 10=E. Greenwich, ll=Somerset.
-------
2. Data
Available sediment data are presented in Appendixes A-F. The data include the distribution of
bed sediment, TSS concentration in riverine flow, TSS concentration in effluents from WWTPs,
and TSS concentrations in the Bay. Inferences based on available data are utilized to develop the
TSS model for Narragansett Bay.
2.1. Bed Sediment Data
The main source of information for bed sediments is provided in McMaster (1960) (Appendix
A). The general statistical values from the 493 observations of bed sediment in Narragansett Bay
(Table A-l) indicate that the bay-wide average ratios of gravel, sand, silt, and clay are 10%,
39%, 37%, and 14.0%, respectively. The general trend of bed sediment has not changed much
since McMaster's surveys (personal communication: John King, Graduate School of
Oceanography, University of Rhode Island). Gravel and sand particles are non-cohesive with low
capacity to be entrained and stay in suspension in the water column of Narragansett Bay. Very
fine sand has a settling speed of 0.01 m s"1 (Vanoni 1975, page 25) and it can descend a distance
of 36 m in about one hour. As the average depth in the Bay is 8 m, such particles may not stay in
the water column more than a few minutes before returning to the bed. Only silt and clay
particles are susceptible to entrainment and resuspension from the bed. These particles can stay
in suspension for few days. For example, silt particles with settling speeds of 5 x 10'5 m s"1 (Lin
and Kuo 2003) can spend at least two days in the water column before settling to the bed. During
stormy conditions, suspended particles can spend longer times in the water column.
Cohesive sediments are modeled in Narragansett Bay. The bed sediment is assumed to be
composed of 50% cohesive sediment, which can contribute to TSS in the water column, with the
remaining 50% as non-cohesive sand and gravel, which do not contribute to TSS. Appendix A
presents the distributions of cohesive and non-cohesive sediments in the Bay. Areas within the
model grid which have no data are assumed to have the same ratios of cohesive and non-
cohesive bed sediments.
2.2. Total Suspended Sediment Data
Available TSS data for Narragansett Bay are described in Appendixes B-D which include the
following data:
1. Concentration of TSS in riverine inflows (mg L"1) (Appendix B). These data are provided
by the Narragansett Bay Commission (NBC) for the 8 major rivers considered in this
work (Fig. 2). These data are used to calculate loading of TSS from the watershed.
Although the riverine TSS can include both mineral and organic particles, in this work all
the loaded particles are considered to belong to cohesive sediments (silt and clay).
2. Concentration of TSS from WWTPs (mg L"1) (Appendix C). These data are available
from the USEPA's Data Monitoring Report (DMR) for the 11 WWTPs which discharge
directly into the Bay (Fig. 2). These particles belong to the detritus group and they are not
included (see assumption 4 above).
3. Concentrations of TSS (mg L"1) in the Bay (Appendix D). The first set of data (Appendix
D.I) were collected by the USEPA-AED) (personal communication: Roxanne Johnson,
USEPA-AED) from surface, mid-depth, and bottom at 8 stations during 2014-2015. The
-------
concentration of TSS (mg L"1) and % organic matter and minerals were calculated. The
average TSS concentration for the whole Bay was 5.3 mg L"1. On average mineral
particles constituted 65% of the TSS. Although these particles can include all type of
particles in the Bay (Section 1.1.3.1, Table 1), they are treated as cohesive sediments by
the model. The calculated % mineral is assumed to represent the general conditions in the
Bay at any time. These data are used for qualitative calibration and validation of model
predictions of TSS concentration in the Bay. The background concentration of detritus
from the watershed and the water column is estimated from measurements of organic
matter in November and December (when both plankton and grazers are minimal). The
Detritus concentration was found to be 1.2 mg L"1 and it is assumed to be uniformly
distributed within the Bay throughout the year.
The second set of data were reported by Collins (1976) (Appendix D.2). Near bottom
turbid layers thickened towards the Bay mouth. On average, bottom concentrations were
twice surface concentrations. Surface concentrations decreased from north to south while
bottom concentrations increased from north to south causing the overall concentration to
increase southward. Large fluctuations in turbidity were reported near the bottom.
The third set of TSS data were reported by Morton (1967) (Appendix D.3). Surface and
bottom samples were collected at ten stations within Narragansett Bay, which gave good
representation of the spatial (horizontal and vertical) concentrations within the Bay. The
overall average TSS concentration was 2.56 mg L"1 and it was used to represent initial
TSS concentration in the Bay.
The fourth set of data included turbidity measurements that were reported by Shenck and
Davis (1973) (Appendix D.4). The turbidity data indicated higher water clarity towards
the mouth of the Bay in the East and West Passages.
The fifth set of data included sediment deposition rates during 1972-1973 which were
reported by Oviatt and Nixon (1973) (Appendix D.5). Deposition rates increased from the
inner Bay towards the mouth of the Bay.
2.3. Inferences from available sediment data
The following inferences are deduced from the above-mentioned data:
1. Bed sediment has 50% cohesive and 50% non-cohesive sediment particles (Appendix A).
2. TSS has 65% mineral and 35% organic particles in the Bay (Appendix D. 1).
3. All loaded TSS from rivers is cohesive sediments.
4. Detritus has an average concentration of 1.2 mg L"1 within the Bay at all times.
5. Detritus is one third from phytoplankton origin and two thirds from watershed origin
(Appendix D.I)
6. Overall average TSS concentration is 2.56 mg L"1 (Appendix D.3)
10
-------
7. TSS concentration of cohesive sediment at the open boundary is 1.0 mg L"1 throughout
the year (Appendix D.2).
2.4. Environmental conditions in 2009
The three major environmental forcing functions that may affect TSS concentration in the water
column are wind storms, tide, and river discharge. Dates of three major storms during 2009 are
presented below.
(https://en.wikipedia.org/wiki/List_of_New_England_hurricanes#2005.E2.80.93present)
• Storml: August 21, 2009 - Hurricane Bill passed just offshore of New England causing
very heavy surf, and a period of rain and gusty winds over Southeastern Massachusetts.
• Storm2: August 29, 2009 - Tropical Storm Danny passed over Nantucket as an extra-
tropical storm, causing up to 2 inches of rain in Massachusetts and Rhode Island, and
brought wind gusts up to 60 mph off the coast of Nantucket and Maine.
• StormS: November 12, 2009 - Hurricane Ida, after hitting the northeast Gulf Coast as a
tropical storm, redeveloped off the Carolina coast as a strong nor'easter, bringing severe
damage as far north as New Jersey, where severe flooding, beach erosion, and strong
winds were reported. As the center of the storm moved out to sea, a batch of moisture
broke off of it, and moved north, bringing moderate rain to New England. The storm
caused millions of dollars in damage.
Figures 3, 4, and 5 present time series of wind energy, precipitation, and total stream flow during
2009. The figures indicate that conditions during the above-mentioned three storms were not
extreme compared to other times during the year. Other New England storms were reported
during 5-7 January, 21-23 February, 12-13 April, 16-19 December, 2009
(https://en.wikipedia.org/wiki/Global_storm_activity_of_2009). Tide elevation is presented in Fig. 6,
which shows spring-neap cycles during 2009.
11
-------
Wind energy
250
Date
Figure 3. Time series of wind energy in 2009 (Abdelrhman 2015). U is the measured wind speed
(m s-1). Dates of the three major storms in 2009 are marked by the vertical dashed lines.
T.F. Green Precipitation Rate
0.070 -i
•TFGreen precipitation (mm/s
Storml Storm2 Storm3
Date
Figure 4. Time series of precipitation in 2009 (Abdelrhman 2015). Dates of the three major
storms in 2009 are marked by the vertical dashed lines.
12
-------
Total freshwater inflow
•Total dischage Storml StormZ Storm3
Date
Figure 5. Time series of total freshwater discharge in 2009 (Abdelrhman 2015). Dates of the
three major storms in 2009 are marked by the vertical dashed lines.
NPTide Elevation
1.5
c
o
•£= 0.5
0.0
-0.5
5 -i.o
-1.5
00 01
5. 5.
oo h-
g
g
a
g g 0 g 0 g
Date
I
01
s
Figure 6. Tide elevation showing spring-neap tides during 2009 (Abdelrhman 2015).
13
-------
3. Model equations
The major equations for the mass transport of TSS are summarized below (Hamrick 1992, 1996;
Tetra Tech 2007). Figure 7 shows a schematic representation of cohesive sediment process,
which are modeled by EFDC in the water column and the bed (Tetra Tech 2007).
dHC dHuC dHvC d(wC) - 5(wsC)
dt dx dy do
Where C is the cohesive suspended sediment concentration (kg m"3 = g L"1); u, v, and w are
water velocities in the x, y, and z (i.e., G) directions (m s"1); ws is particle settling velocity (m s"1);
AH and Av are horizontal and vertical eddy diffusivities (m2 s"1); Qs is external source/sink fluxes
(g m"3 m s"1 or g m"2 s"1) ; H is the water depth (m), and J0 is the net sediment flux from the bed to
the water column (g m"2 s"1). The boundary conditions for the vertical sediment transport reflect
the no net transport at the water surface (G = 1) and that the net transport at the bed (G = 0) is
equal to (resuspension - deposition), i.e.,
AvdC
~-w,C = 0, a=l (2)
A dC
Where the superscripts r and d for J0 indicate resuspension and deposition, respectively, given by
the following equations.
dme /Tb - Tce\a
Jr0 = Tcd
Where Tb is the flow-exerted bed stress (N m"2), dnWdt is the surface erosion rate (g m"2 s"1), xcd
is the critical stress for deposition (N m"2), Tce is the critical stress for erosion (N m"2), Sd is the
near bed deposition sediment concentration (g m"3), and a is an exponent used for cohesive
sediment.
14
-------
0>
m
Advection
Dispersion
Suspended
sediment
plume
Shear stress
conditions
Figure 7. Cohesive sediment processes.
http://www.intechopen.com/source/html/38257/media/image66.jpeg
15
-------
4. Model setting
The general physical setting and forcing functions for Narragansett Bay were presented in
Abdelrhman (2015). The hydrodynamic model provided the spatial and temporal predictions for
water temperature and salinity. The setting for water quality and algal processes are presented in
Abdelrhman (2016a). The EFDC has built in water quality capacities that can model three types
of phytoplankton groups (Diatoms, Dinoflagellates, and Greens (Abdelrhman 2016a)), which
also contribute to suspended particulates.
The sediment model parameters were set according to measured or published values (Liu and
Huang, 2009). Unless otherwise specified, initial conditions in the Bay were consistent with
conditions at 00:00 time on January 1, 2009. The spatial (horizontal and vertical) distribution of
the initial values in the water column was prepared for temperature and salinity as described in
Abdelrhman (2015). The spatial distributions of initial concentrations for TSS and the various
water quality state variables were assumed to have uniform values throughout the Bay
(Abdelrhman 2016a). Nonetheless, the effect of initial values in the water column would be
forgotten as the simulation proceeds and the initial distributions are updated.
Boundary values for TSS had to be specified throughout the simulation period at the four
boundaries of the Bay: the surface boundary with the overlying atmosphere, the bottom boundary
with the underlying bed sediment, the landward boundary with its adjacent watershed, and the
seaward (open) boundary with the RI Sound,
Sediment flux at the surface (the air-water interface) was assumed to be negligible as indicated
by the boundary conditions for the vertical sediment transport equation (Section 3).
4.1. Initial Conditions
Initial concentrations of cohesive sediments in the water column were set to the average of the
observed TSS values 2.56 mg L"1 (Morton 1967, Schenck and Davis 1973) and the concentration
of non-cohesive sediment was set to zero.
4.2. Boundary Conditions
Atmospheric deposition through the air-sea boundary is assumed to be negligible. The following
three types of boundaries: bed, point sources, and seaward open boundary are defined throughout
the simulation.
4.2.1. Bed
The distribution and composition of bed sediments followed the information from McMaster
(1960). Bed sediment was assumed to maintain the same composition throughout the simulation
period (one year for 2009). The flow exerted bed shear stress defines the resuspension and
deposition from and to the bed (Fig. 7).
The bed acted as a source/sink for the TSS in the water column. Based on the predicted
hydrodynamics and the bed mechanical properties, the sediment resuspension and entrainment
rates in the Bay were calculated by the model. Figure 8 presents the initial distribution of bed
sediments. The equations for resuspension from and deposition to the bed (Eqs. (4) and (5),
respectively) are presented in Section 3. The erosion rate, settling speed and critical stresses are
16
-------
assumed based on literature values for cohesive estuarine sediments (Lin and Kuo 2003, Liu and
Huang 2009): dnWdt = 5xlO'4 g m'2 s'1, ws = 5xlO'5 m s'1, Tce = 0.1 N m'2, Tcd = 0.035 N m'2.
These values were modified and calibrated during the various model runs to insure that the
sediment flux to and from the bed (J0, in Section 3) is properly modeled. All values used have
also been reported in other TSS models (see Table 2).
4.2.2. Point sources
Time series of the TSS concentration at the mouth of each river (Appendix B) was used with its
flow rate (Abdelrhman 2015) to define the TSS load (assumed cohesive) at the mouth of the
river. These loads were internally interpolated by the model to the time step of the model.
The landward boundary was defined by the watershed of the Bay, 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. The ninth sub-watershed
(498 km2) was un-gauged. The TSS loading from the upper half this sub-watershed was divided
equally between four rivers including Pawtuxet, Taunton, Warren, and Hunt. Loads from the
lower half of the riparian area were assumed to enter the lower part of the Bay at three
intermediate locations within the Sakonnet River and the East and West passages (Abdelrhman
2015). The river's load per unit of its sub-watershed area was assumed to apply to the added un-
gauged area. Appendix B presents time series of TSS concentration for all the major rivers in
Narragansett Bay. These concentrations were internally used by the model to calculate loads
from riverine point sources (Qs term, Eq. (1), Section 3).
Similarly, eleven waste water treatment plants (WWTPs) existed along the shore line and
discharged their TSS loads directly into the Bay (Abdelrhman 2016a) (Appendix C). These point
source loads of TSS could be internally used by the model to calculate additional contributions to
the Qs term (Eq. (1), Section 3). However, this option is not currently used due to the lack of
information about the physical nature (settling speed, cohesion, etc.) of these particles.
4.2.3. S eaward op en b oundary
Boundary concentrations of TSS at the seaward open boundary of the Bay were controlled by
their values in the RI Sound (Collins 1976, Appendix D.2). Accordingly, TSS concentration of
cohesive sediment 1.0 mg L"1 was assumed to exist there throughout the year.
4.3. Time step
The model time step was set to 15 s, similar to the water quality simulations (Abdelrhman
2016a).
17
-------
Table 2. Calibration parameters
Parameter
Erosion rate, dme/dt
(gm m"2 s"1)
Settling velocity, ws
(m s-1)
Critical stress for erosion, Tce
(Nm-2)
Critical stress for deposition xcd
(Nm-2)
Calibrated value
5 x 10-4
5 x 10-5
0.1
0.035
Published range
0.3
5 x ID'4
2x ID'1
5 x ID'5
1 x 10'4
0.04
0.1
0.4
0.03
0.035
0.2
Reference
Liu and Huang (2009)
Lin and Kuo (2003)
Liu and Huang (2009)
Lin and Kuo (2003)
Bai and Lung (2005)
Liu and Huang (2009)
Lin and Kuo (2003)
Bai and Lung (2005)
Liu and Huang (2009)
Lin and Kuo (2003)
Bai and Lung (2005)
18
-------
% Cohesive (Clay+Silt)
100
(A)
% Non-Cohesive (SanOJ
I 100
90
I BO
70
(B)
Figure 8. Distribution of sediments on the bed:(A) cohesive sediment, and (B) non-cohesive
sediment. (Based on data from McMaster (1960), Appendix A)
19
-------
5. Calibration and validation
The hydrodynamic model for Narragansett Bay was calibrated and validated for the year 2009
(Abdelrhman 2015). The water quality simulations were also calibrated and validated for the
same year. There are no adequate TSS data in the Bay during 2009. However, the composition of
bed sediments has not changed significantly for over fifty years (Section 2.1), which supports a
quasi-steady state for TSS concentration in the Bay. It is assumed that such state exists in
Narragansett Bay and that the TSS data in Appendixes A-D are valid for the year 2009.
For a one-year simulation, TSS concentrations of cohesive sediment are generated every hour at
all eight vertical layers and all buoy stations. Such information requires a targeted field
monitoring program to provide adequate observations for model calibration and validation. Until
such a program is executed, qualitative analysis are conducted to compare model predictions
with the general TSS information presented in Appendix D.
The historical overall mean TSS concentration in the Bay was 2.56 mg L"1 with a range of 2.0
mg I/1 to 4.0 mg I/1 (Collins 1973, Morton 1967, Oviatt and Nixon (1975, Appendix D). The
recent measurements by AED in 2014-2015 confirmed the same order of magnitude of the
above-mentioned historical TSS concentration values in the Bay (Appendix D.I). The AED
observed TSS concentrations included contributions from the suspended sediments as well as the
dry weight of organic particulates (e.g., phytoplankton and detritus). Predicted phytoplankton
concentrations are presented elsewhere (Abdelrhman 2016a). Only the mineral part of TSS is
presented here. According to AED data, observed TSS concentrations contained 65% minerals
and 35% organics, which modifies the above-mentioned range to 1.3 - 2.6 mg L"1 for the mineral
particulates.
Model parameters for TSS were adjusted until qualitative agreement between predictions and
observations was acceptable. Figure 9 presents an example of the comparison between predicted
concentrations at station CP throughout the full year 2009 and the yearly range of observed
values from 2014-2015. More agreements between predicted TSS activities and observations are
presented below (see Results).
No further calibration or validation is feasible due to the lack of proper field data. Such data
should expand in both space and time to provide more vertical resolution through the water
column at selected stations. The data should include samples during high and low tides for at
least one month to cover spring-neap tide phases.
20
-------
CP
Date
Figure 9. Predicted TSS mineral concentration and the range of observations (1.3-2.6 mg L"1) at
station CP.
21
-------
6. Results
For convenience, the abbreviation of TSS is used to represent the predicted concentration of the
mineral cohesive sediment for all the following model results, tables, and figures. The TSS
results indicate that concentrations vary greatly in space and time. A sample of the predictions
obtained at station CP during 2009 are presented below. Time series of TSS concentrations at all
stations are presented in Appendix G. The following test cases identify the general behavior of
TSS concentration.
Each source of TSS was examined separately in test cases 1-3 which included loading from bed
sediment, open boundary, and river discharge, respectively. All tests ran for 31 days during the
month on January, 2009. Settling speed was set to 3xlO"5 m s"1 for all cases. Figures 10-12
present time series of surface and bottom concentrations as well as bottom deposition (g m"2).
The initial concentration was set to 0.0 mg L"1 to allow comparison between the inception of TSS
activity at surface and bottom layers. The following observations were obtained from the test
runs. Deposition began when the TSS concentration was at a peak and starting to decline. Sharp
drops in deposition occurred when TSS concentration started to increase in the water column.
With few exceptions, bottom TSS concentration was usually higher than surface concentration.
An exception was clear at the beginning of case 3 for TSS loading from rivers.
Figure 13 shows the overall concentration from all three sources including the initial
concentration (2.56 mg L"1). The TSS predictions show high concentration periods which
coincide with the spring neap tide cycles throughout the year 2009 (see below). The relative
contributions from these sources change in space and time. Table 3 and Fig. 14 present a sample
of the vertical distribution of the relative contribution from each TSS loading source at station
CP on January 16, 2009 (00:00 hour). This example indicates that higher concentrations exist
near the bed and that resuspension from the bed makes the least contribution to TSS followed by
the transport through the open boundary and the highest contribution is from watershed loading
through riverine discharge.
High TSS concentrations coincide with the spring tide at most of the stations which are not in the
vicinity of a river discharge (Fig. 15). The range of TSS concentration between spring and neap
tides can exceed 20 mg L"1 (e.g., stations NP and TW, Appendix G). In addition, surface TSS
concentrations vary with tidal phase during the day indicating that lower concentrations coincide
with high tide (e.g., Fig. 16). Changes close to 5 mg L"1 are predicted at some stations. Bottom
TSS concentrations show similar variation with tide, which sometimes lags the peak tide and
reflect interference by other mechanisms (e.g., settling from above).
The TSS concentration correlates with high river discharge in their vicinity (Fig. 17). Deposition
is also high at these locations (Table 4). These correlations change based on the location relative
to riverine discharges. Notice the high correlations at stations PD and PR and the lower
correlations at stations BR and CP and the lack of correlation at the other stations (Appendix G).
The yearly average TSS concentrations are calculated from hourly predictions at all eight vertical
layers at all stations (Table 4). Figure 18 shows the longitudinal behavior of the predicted
average TSS concentrations and net deposition along the West Passage in 2009. An increase in
22
-------
concentration toward the Bay mouth was reported by Collins (1976) (Appendix D.2). Figure 18
shows a clear spatial correlation between TSS concentration in the water column and its net
deposited mass on the bed. At station PD, high TSS concentrations in the water column proceed,
without deposition, to Providence River (station PD) where TSS concentration drops and
significant deposition takes place. Within the middle stations (BR, CP, and NPI) both TSS
concentrations and net deposition are low, which indicates the transport of TSS through this
region with minimal effects from resuspension and deposition. At the beginning of the West
Passage (station MV) there is no net deposition and TSS concentration increase due to TSS loads
from the Hunt River and the active interaction with flow from Greenwich Bay. The high TSS
concentration continues to station QP1 where high deposition takes place due to the deeper
navigation channel to Quonset Point and the widening of the Bay cross section as well as the
wake in the vicinity of the northern tip of Conanicut Island. At station GD, TSS concentration
was higher with no net deposition on the bed, which indicates the active turbulent environment
due to the exchange through the open boundary with RI Sound.
The longitudinal behavior of predicted net deposition in 2009 along the West Passage reflects a
general trend with increasing values from the mid-Bay towards the lower Bay as reported in the
literature (Oviatt and Nixon 1975, Appendix D.5). It is important to notice that although net
deposition is negligible at the end of the year, during favorable events deposition may show
considerable values, as indicated by the maximum deposition values in Table 4. The high
deposition at station PR agrees with field observations (Morton 1976, Appendix D.3).
Figure 19 presents the predicted average vertical TSS profiles at the same stations along the
West Passage. The profiles reflect the same trend of the overall TSS concentrations (Fig. 18).
Time series of the instantaneous TSS concentrations are presented in Appendix G.
Model results are sensitive to many factors including settling speed, erosion rate, and critical
shear stresses for erosion and resuspension (section 3, Fig. 7). For example, the effect of
increasing the settling speed from 3xlO"5 m s"1 to 6xlO"5 m s"1 is shown in Fig. 12(B) for test case
3 with TSS loading from rivers. The higher settling speed caused TSS concentrations to drop
throughout the water column and altered the behavior of deposition on the bed.
23
-------
Table 3. Contribution of TSS by each source on January 16, 2009
Case
Case 1
Case 2
Case 3
Case 4
Setting
Only bed load on
Only open boundary on
Only rivers on
All loads are on
Average TSS
concentration
(mgL-1)
0.10
0.19
1.58
6.03
% relative to all
loads (Case 4)a
1.60
3.07
26.20
100.00
a Values in this column do not add to 100% because each case has its own independent setting
Table 4. Summary of TSS predictions at all stations
Mean
concentration
Station (mg L'1)
PD
PR
BR
CP
GB
SR
NPI
MV
PP
QP1
TW
GD
NP
MH
2.94
0.55
0.44
0.44
0.03
0.22
0.83
2.03
2.65
5.00
5.00
4.23
0.48
Maximum
concentration
(mgL-1)
50.1
5.17
5.32
6.09
1.28
2.66
4.84
10.3
11.2
14.7
23.3
15.5
19.6
4.07
Net deposition
& (maximum)51
(gm-2)
0.0 (270)
1,130
78.2
63.2(75)
56.7 (120)
162
0.0 (21)
0.0 (20)
1,580
649
1,860
5.62
49.4 (190)
863
Notes
Correlated with river discharge
Correlated with river discharge
Correlated with spring tide
Correlated with spring tide
Correlated with spring tide
Correlated with spring tide
Correlated more with spring tide and
to some extent with river discharge
Correlated more with spring tide and
to some extent with river discharge
Correlated with spring tide
Correlated with spring tide
Correlated with spring tide
Correlated with spring tide
Correlated with spring tide
Correlated more with spring tide and
to some extent with river discharge
Net deposition at the end of 2009 with maximum observed deposition during the year
24
-------
CP Bed Only
• Bottom
•Surface
•Deposition
1C)
15 20
Time (day)
25
30
Figure 10. Test Casel: loading from bed only
CP Open Boundary Only
• Bottom
•Surface
•Deposition
US
10
15 20
Time (day)
25
30
Figure 11. Test Case 2: loading from open boundary only
35
35
25
-------
(A)
CP Rivers Only
• Bottom
•Surface
•Deposition
10
15 20
Time (day)
25
30
30
35
Rivers only with double settling speed
10
15 20
Time (day)
25
30
35
(B)
Figure 12. Test Case 3: loading from rivers only with: (A) settling speed 3x10"
(B) settling speed 6x10~5 m s"1
m s"
and
26
-------
CP All loads
• Bottom Surface —
•Deposition
12
10
15 20
Time (day)
25
30
Figure 13. Test Case 4: loading from all sources
8
:
S 5
^4
3
2
1
{
CPon day 16 at 00:00
Bedonly —Open Boundary only — Riversonly —All
!
V
I
^~~-.
-^
\
1\ )
V
112345678
Concentration (mg I/1)
Figure 14. Vertical profiles of TSS for Cases 1-4 on day 16 at time 00:00 hour
27
-------
CP
90
Date
Figure 15. Effect of Spring-Neap tide on resuspension periods
CP Rivers Only
•Laye rl
• Laye r8
-Tide
6 8 10
Time (day)
12
16
Figure 16. Effect of tide levels on TSS concentration at station CP. Layer 1 is at the bottom and
Layer 8 is at the surface.
28
-------
PR
•Laye rl
•Layers
•Deposition
•River discharge
Date
Figure 17. Effect of river discharge on TSS concentration at station PR. Layer 1 is at the bottom
and Layer 8 is at the surface.
Longitudinal TSS behavior for 2009
•Average concentration — • — Net deposition
1200
10
20 30
Distance (km)
40
50
Figure 18. Predicted average TSS concentrations and net deposition at stations along the
West Passage.
29
-------
•PD
v
8
7
5
5
4
3
2
Average TSS profiles for 2009
•PR BR
•CP
•NPI MV
•QP1 GD
345
Concentration [mg L-l)
Figure 19. Predicted average TSS profiles at stations along the West Passage
(see Fig. 1 for station locations).
30
-------
7. Concluding remarks
Future work should incorporate more representative spatial and temporal information to refine
model predictions. As the presented TSS predictions include only the mineral cohesive
sediments, the organic phytoplankton and detritus concentrations should be added. Figure 20
shows the calculated overall average of phytoplankton from field observations during the
summer of 2009 (Abdelrhman 2016b). The parti culate carbon is calculated using a Chi-a to
carbon ratio of 43. This ratio varies widely and it has to be reexamined for the modeled system
(Kremer and Nixon 1978). Comparing the TSS profiles in Fig. 19 with the phytoplankton carbon
profile in Fig. 20, it is clear that the latter can have significant contribution to TSS at all
locations, especially in the upper Bay. To provide a more inclusive estimate of the total TSS
concentration, both phytoplankton contribution (~ 0.5 mg L"1) and detrital concentration (-1.13
mg L"1, Appendix D.I) should be added to the presented model predictions at all locations
throughout the year. In addition, physical properties and loading of organic particles from
WWTPs should be included in future predictions of TSS in the Bay.
Light attenuation in the water column is affected by both mineral and organic particles as well as
other water properties (Abdelrhman 2016b). This work covered predictions of the mineral part of
TSS. Predictions of the organic particles (mainly phytoplankton) is covered elsewhere
(Abdelrhman 2016a). The following five assumptions were invoked in this work and their impact
on light attenuation has to be evaluated.
Assumption 1: Particles <2 jum (colloids) are ignored in the calculation of TSS.
Assumption!': Contribution of zooplankton particles to TSS is considered negligible.
Assumption 3: Nonliving organic particles have nopigmented Chl-a.
Assumption 4: Detrital organic particulates from non-phytoplankton origins are either ignored
or inferred from field observations.
Assumption 5: Minerals from organic origin are considered to be negligible.
These assumptions are standard, usually because of limitations in observational techniques in the
field, analytical techniques in the laboratory, or modeling techniques and practices.
31
-------
Average profiles
chl-a phytoplankton
Concentration
0123456789 10 11 12
2
4
6
£ 8
Q.
-------
References:
Abdelrhman, M.A. 2015. Three-dimensional Modeling of the Hydrodynamics and Transport in
Narragansett Bay. United States Environmental Protection Agency Report tracking number
ORD-008162, pp. 169.
Abdelrhman, M.A. 2016a. Three-dimensional Modeling of Water Quality and Ecology in
Narragansett Bay. United States Environmental Protection Agency Report tracking number
ORD-008354.
Abdelrhman 2016b (in review/ Quantifying Contributions to Light Attenuation in Estuaries and
Coastal Embayments: Application to Narragansett Bay, Rhode Island. United States
Environmental Protection Agency tracking number ORD-015494.
Bai, S., and Lung, W.S. 2005. Modeling sediment impact on the transport of fecal bacteria.
Water Research 39:5232-5240.
Blom, G., Duin, E.H.S. 1994. Sediment resuspension and light conditions in some shallow Dutch
lakes. Water Science and Technology 30(10): 243-252.
CIRIA. \996.BeachManagementManual. CIRIA Report 153.
Collins, B.P. 1974. Suspended material transport in lower Narragansett Bay and western Rhode
Island Sound. M.S. Thesis, University of Rhode Island, Kingston, 85 pp.
Collins, B.P. 1976. Suspended material transport: Narragansett Bay Area, Rhode Island.
Estuarine and Coastal Marine Science 4:33-44.
Gallegos, C.L. and Moore, K.A. 2000. Factors contributing to water-column light attenuation. In:
Batiuk, R.A. (ed.), Chapter IV, Chesapeake Bay submerged aquatic vegetation water quality and
habitat-based requirements and restoration targets: A second technical synthesis. Annapolis, MD:
EPA Chesapeake Bay Program, pp. 35-54.
Hamrick, J.M. 1992. A three-dimensional environmental fluid dynamics computer code:
theoretical NS COMPUTATIONAL ASPECTS. The college of William and Mary, Virginia
Institute of Marine Science. Special Report 317, 63 pp.
Hamrick, J.M. 1996. User's manual for the environmental fluid dynamics computer code,
Special Report No. 331 in Applied Marine Science and Ocean Engineering, Virginia Institute of
Marine Science, College of William and Mary, Gloucester Point, VA.
Hulsizer, E.E. 1976. Zooplankton of lower Narragansett Bay, 1972-1973. Chesapeake Science
17(4):260-270.
33
-------
ICES. 2004. Chemical measurements in the Baltic Sea: Guidelines on quality assurance. Ed. E.
Lysiak Pastuszak and M. Krysell. ICES Techniques in Marine Environmental Sciences, No. 35.
149 pp.
ISO 2002. International Organization for Standardization. "ISO 14688-1:2002 - Geotechnical
investigation and testing - Identification and classification of soil - Part 1: Identification and
description".
Kremer, J. N. and Nixon, S.W. 1978. A costal marine ecosystem simulation and analysis.
Ecological Studies 24, Springer-Verlag, NY.
Lin, J. and Kuo A.Y. 2003. A model study of turbidity maxima in the York River Estuary,
Virginia. Estuaries 26(5): 1269-1280.
Lin, J. and Kuo, A.Y. 2003. A model study of turbidity maxima in the York River Estuary.
Estuaries 26(5): 1269-1280.
Liu, X. and Huang, W. 2009. Modeling sediment resuspension and transport induced by storm
wind in Apalachicola Bay, USA. J. Environmental Modelling & Software 24:1302-1313.
Martin, J.H. 1970. Phytoplankton-zooplankton relationship in Narragansett Bay. IV. The
seasonal importance of grazing. Limnology and Oceanography 15(3):413-418. doi:
10.4319/lo.l970.15.3.0413.
McMaster, R.L. 1960. Sediments of Narragansett Bay and Rhode Island Sound, Rhode Island.
Journal of Sedimentary Petrology 3 0(2): 249-274.
Morton, R.W. 1967. Spatial and temporal observations of suspended sediment: Narragansett Bay
and Rhode Island Sound. Technical Memorandum, TM No. 396. Naval underwater weapons
research and engineering station, Newport, R.I. 33 pp.
Noel, J.M., Chamberlain, R.H., and Steinman, A.D. 1995. Environmental factors influencing
suspended solids in the Loxahatchee Estuary, Florida. American Water Resources Association,
Water Resources Bulletin 31 (1): 21 -3 2.
Oviatt, C.A. and Nixon, S.W. 1975. Sediment resuspension and deposition in Narragansett Bay.
Estuarine and Coastal Marine Science 3:201-217.
Oviatt, C.A., Smith, L., Krumholz, J., Coupland, C., Stoffel, H., Keller, A., McManus, M.C.,
and Weber, L. (submitted). Nutrient Concentrations, Metabolism and Hypoxia in a Temperate
Estuary. Estuaries and Coasts.
Pilson, M.E.Q. 1985. On the residence time of water in Narragansett Bay. Estuaries 8(1):2-14.
34
-------
Quality Assurance Project Plan, U.S. EPA - Atlantic Ecology Division, Project Title: Bay
Ecosystem Time Series (BETS), Project Leader(s): Autumn Oczkowski, Jason Grear, Richard
McKinney, Alana Hanson, Donald Cobb, Cathy Wigand, Principal Investigator(s): Autumn
Oczkowski, GPRACode: SSWR4.02B, September, 2015.
Schenck, Jr., H., and Davis, A. 1973. Aturbidity survey of Narragansett Bay. Ocean Engineering,
2:169-178.
Tetra Tech. 2007. The Environmental Fluid Dynamics Code Theory and Computation, Volume:
2: Sediment and Contaminant Transport and Fate. Tetra Tech, Inc. 10306 Eaton Place, Suite 340,
Faifax, VA 22030. 96pp.
USEPA. 1993. Determination of turbidity by nephlometry. O'Dell, J.W. (ed.) Method 180.1-1,
Revision 2.0, Environmental Monitoring Systems Laboratory, ORD, USEPA, Cincinnati, OH
45268. 10pp.
Vanoni, V.A. (ed.) 1977. Sedimentation Engineering. ASCE-Manuals and Reports on
Engineering Practice-No 54. Headquarters of the Society, New York, N.Y. 10017.
Velde, B. 1995. Composition and mineralogy of clay minerals, in Velde, B (ed.), Origin and
mineralogy of clays: New York, Springer-Verlag.
Wernand, M.R. 2010. On the history of the Secchi disc. Journal of the European Optical Society,
Rapid Publications 5, 10013s.
35
-------
Appendix A. Bed Sediment
The main source of information for bed sediments in Narragansett Bay is provided in McMaster
(1960).
http://catalog.data.gov/dataset/mcmaster60-sediments-of-narragansett-bay-acquired-in-1960
The data included percentages of clay, silt, sand, and gravel from 493 locations within the Bay
(Fig. A-l) as well as the inferred bed types (Fig A-2). Table A-l shows some general statistical
values of these observations. It is clear that cohesive sediments (silt and clay) are dominant with
an average ratio of 50.7% in the bed samples. The non-cohesive sediments (sand and gravel)
occupy the remainder of the ratio (49.3%) in the bed samples. In this work, gravel is ignored and
considered to be completely sedentary to any sediment transport process on the bed or in the
water column. Figure A-3 shows the distributions of cohesive and non-cohesive sediment in the
Bay which are used by the TSS sediment model. The unsampled regions (Fig. A-l) were
assumed to have 50% cohesive and 50% non-cohesive sediments.
* \iit-_ •••••••»• ......
*~t_ •••••••• • *••••
•*|***».«*« « •*»•
•••* • *••• ... •••,«»
.
• •••*•*• *..*..•_
•*••-•• ••*» •«*
••••* •*-*»«•»
Sampling Stations
I 100
(A)
(B)
Figure A-l. Locations of 493 bed sampling stations (McMaster 1960). (A) locations for actual
samples, and (B) blue areas outside the sampling locations indicating the unsampled regions.
36
-------
Upland
Gravel
Sandy gravel
Gravel-sand-silt
Sand
Gravelly sand
Silty sand
Silt
Sandy silt
Clay-silt
Sand-silt-clay
Gravel-silt-clay
Rock
Figure A-2. Sediments of Narragansett Bay. All sediment data are from McMaster (1960) as
presented in Rhode Island Geographic Information System (RIGIS, www.edc.uri.edu/rigis)
and Lee et al. (2000).
37
-------
(D)
Figure A-3. The percent distribution of bed sediment on the bed of Narragansett Bay:
(A) sand, (B) silt, (C) clay, and (D) gravel.
38
-------
Table A-1. Statistical parameters of bed samples based on observations in Narragansett Bay
McMaster(1960).
Statistical Parameter
Mean
Standard Error
Median
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Count
Confidence Level (95.0%)
Gravel
10.1
0.7
3.7
16.6
276.8
13.3
3.4
100.0
0.0
100.0
493
1.5
Sand
39.2
1.3
32.9
30.0
898.1
-1.2
0.4
99.0
0.0
99.0
493
2.7
Silt
36.7
1.1
39.9
24.5
600.8
-1.5
-0.1
83.7
0.0
83.7
493
2.2
Clay
14.0
0.4
15.9
9.7
93.3
-1.3
-0.1
38.5
0.0
38.5
493
0.9
39
-------
Appendix B. TSS Concentration in Riverine Flow
Concentration of TSS in riverine inflows was reported by NBC for all rivers (Fig. B-l).
http://snapshot.narrabay.com/appAVaterOualityInitiatives/NutrientMonitoring. Statistical
parameters of the reported values are presented in Table B-l.
The time series of TSS concentrations (mg L"1) in the eight major rivers (Woonasquatucket,
Pawtuxet, Ten Mile, Taunton + Mill + 3 mile, Moshassuck, Blackstone, Hunt, and Palmer) were
considered in this work (Fig. B-2). The data are adjusted as described below and they were used
to calculate loading of TSS from the watershed to the Bay.
Reported TSS concentrations during the three major storms never exceeded 20 mg L"1 in the
freshwater discharge from any river (Fig. B-2). Accordingly, any reported concentration that
exceeded this limit was reduced to the smallest of the reported replicates, or the average of the
respective values from the other rivers. Figure B-3 presents the adjusted time series of TSS
concentrations in all rivers. Statistical parameters of the adjusted values are presented in Table
B-2. The loaded particles are considered to include 65% cohesive sediments (clay and silt) and
35% detritus (see Appendix D.I).
40
-------
A
N
6MMlua«l «wr g EMondMil Rd
Figure B-1. NBC River stations for TSS, used for loading estimates in 2009.
41
-------
TSS Concentration in Rivers
Woonasquatucket
• Moshassuck
- • - Storm2
Ten Mile
—•— Blackstone
— — — Storrn3
Taunton
- Palmer
Pawtuxet
Storml
Date
Figure B-2. Reported time series of TSS concentrations in all rivers in 2009. Dates of the three
major storms in 2009 are marked by the vertical dashed lines.
Adjusted TSS Concentration in Rivers
• Woonasquatucket
• Moshassuck
Ten Mile
•Blackstone
Taunton
-Palmer
Pawtuxet
25
:r- 20
ij
ac
E
-15
g
1
£ 10
OJ
u
5 5
00
I
rrT
t-l
ffi
rH
Date
Figure B-3. Adjusted time series of TSS concentrations all rivers in 2009.
42
-------
Table B-l. Statistical parameters of reported TSS concentrations (mg L"1)
Woona-
squatucket
Mean
Standard
Error
Median
Standard
Deviation
Sample
Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Count
Confidence
Level (95.0%)
9.49
3.49
6.00
21.77
473.84
34.21
5.71
137.00
1.00
138.00
39
7.06
Ten
Mile
12.38
2.96
9.00
11.85
140.38
8.92
2.71
50.00
2.00
52.00
16
6.31
Table B-2. Statistical parameters of the
Statistical
parameter
Mean
Standard Error
Median
Standard
Deviation
Sample
Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Count
Confidence
Level (95.0%)
Woona-
squatucket
5.23
0.42
5.00
2.60
6.78
-0.12
0.43
11.00
1.00
12.00
39
0.84
Ten
Mile
9.44
1.30
8.00
5.51
30.35
-1.47
0.32
16.00
2.00
18.00
18
2.74
Taunton
9.45
2.48
8.00
8.24
67.87
1.52
1.31
27.00
1.00
28.00
11
5.53
Pawtuxet
14.39
6.48
6.00
31.08
965.98
17.05
3.99
147.00
1.00
148.00
23
13.44
Mosha-
ssuck
7.00
1.54
6.00
6.90
47.58
9.18
2.63
31.00
1.00
32.00
20
3.23
Black-
stone
8.73
2.32
4.50
10.86
117.92
6.75
2.53
45.00
1.00
46.00
22
4.81
Palmer
14.91
4.70
10.00
15.58
242.69
-0.29
0.89
45.00
1.00
46.00
11
10.47
All
Rivers
11.40
1.37
6.00
21.13
446.29
24.39
4.66
147.00
1.00
148.00
239
2.69
adjusted TSS concentrations (mg L"1)
Taunton
7.
1.
6.
5.
29.
1.
1.
19.
1.
20.
27
57
00
44
54
46
08
00
00
00
12
3.45
Pawtuxet
5.51
0.70
6.00
3.43
11.78
0.84
0.69
14.00
1.00
15.00
24
1.45
Mosha-
ssuck
5.80
0.80
6.00
3.58
12.80
-0.99
0.12
11.00
1.00
12.00
20
1.67
Black-
stone
5.95
0.81
5.00
4.20
17.63
-0.22
0.87
13.00
1.00
14.00
27
1.66
Palmer
7.
1.
7.
5.
30.
-1.
0.
14.
1.
15.
.20
.58
.10
.48
.00
.66
.17
.00
.00
.00
12
3.48
All
Rivers
6.29
0.34
6.00
4.20
17.67
0.48
0.92
19.00
1.00
20.00
152
0.67
43
-------
Appendix C: TSS Concentration in WWTPs Flow
The concentration of TSS (mg dry weight L"1) was provided by the EPA's DMR for the eleven
WWTPs which discharged directly into Narragansett Bay in 2009 (Fig. 1). These particles are
considered to be organic particles. These data are used to calculate point-source loading of
organic particles to the Bay (Fig. C-1). Figure C-2 presents the time series of TSS concentrations
from WWTPs in 2009. Table C-1 shows the major statistical parameters of these data. Although
the data are not utilized in the current model due to lack of knowledge about its physical
behavior (i.e., settling speed, cohesiveness, entrainment stress, etc.), the data are presented here
for completeness and for future consideration (see Concluding Remarks).
Figure C-1. WWTPs with direct discharge to the Bay. (1) Bucklin Pt, (2) Fields Pt.:
(3) E. Providence, (4) Warren, (5) Bristol, (6) Fall R., (7) Newport, (8) Jamestown,
(9), QuonsetPt, (10) E. Greenwich, (11) Somerset.
44
-------
60
50
40
e
S 20
c
o
u
10
CO
o
TSS Concentration in WWTPs
• Bucklin Pt.
•Bristol
-Quonset Pt.
•Fields Pt.
-FallR.
•E. Greenwich
• E. Providence
•Newport
•Somerset
Warren
-Jamestown
g
g g
g
g
r-
g
I
to
Date
g
g g
LT]
rH
00
CTl O1
O O
m m
Figure C-2. The time series of organic particle concentrations from all WWTPs in 2009
45
-------
-Ka
Table C-l. Statistical parameters for TSS concentrations from eleven WWTPs (mg L )'
Mean
Standard
Error
Median
Standard
Deviation
Sample
Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Count
Confidence
Level (95.0%)
Bucklin
Pt.
7.11
0.28
6.00
5.34
28.51
7.09
2.14
42.00
1.00
43.00
365
0.55
Fields
Pt.
12.40
0.23
12.00
4.38
19.21
0.68
0.57
27.00
2.00
29.00
365
0.45
E.
Providence
20.78
3.32
18.65
11.49
131.92
3.90
1.65
43.70
7.10
50.80
12
7.30
Warren
4.73
0.63
4.55
2.18
4.74
1.86
1.50
7.20
2.60
9.80
12
1.38
Bristol
10.73
0.52
10.67
1.79
3.20
-0.72
-0.29
5.69
7.69
13.38
12
1.14
Fall
River
9.83
0.89
10.00
3.10
9.61
0.19
0.38
11.00
5.00
16.00
12
1.97
Newport
11.83
1.48
11.00
5.11
26.15
1.67
1.14
18.00
6.00
24.00
12
3.25
James-
town
4.39
0.35
4.58
1.23
1.50
0.71
0.32
4.67
2.28
6.95
12
0.78
Quonset
Pt.
12.02
1.02
10.66
3.54
12.51
1.84
1.58
12.02
7.78
19.80
12
2.25
E.
Greenwich
4.13
0.44
4.40
1.51
2.27
-1.04
0.04
4.60
1.90
6.50
12
0.96
Somerset
6.38
1.03
5.40
3.57
12.75
-0.76
0.35
11.50
1.00
12.50
12
2.27
TSS concentrations were provided by the EPA's DMR for the eleven WWTPs
-------
Appendix D: TSS Concentration in the Bay
Various in-situ efforts were conducted to assess TSS concentration in Narragansett Bay as
described in this appendix. Five data sets are presented in separate sections together with their
illustrations and tables.
D.I. AED TSS data in 2014-2015
Water samples were collected by AED staff at the surface, mid-depth, and bottom at 8 stations in
the Bay during 2014-2015 (Fig. D-l, Table D-l, personal communication Ms Roxanne Johnson,
USEPA-AED). The concentration of TSS (mg L"1) and % organics and minerals were calculated
(Figs. D-2 and D-3, Table D-2) for 2014 and 2015. The average TSS concentration for the whole
Bay was 5.12 mg L"1. The organic matter (35%) is considered to include detritus from the
watershed, human organics from WWTPs, phytoplankton (alive and dead) in the water column,
and other organism carcasses. These values agree with Collins (1974) who gave organic values
averaging 20-30% of dry weight (Oviatt and Nixon 1975).
The minerals (65%) are assumed to originate from the watershed (i.e. silt and clay) as well as
from the resuspended bed sediment (Appendix A).
The AED data are used for calibration and validation of model-predicted TSS. The data are also
used to define initial conditions in water column at the beginning of the simulation. The ratio of
the average minerals (65%) in the TSS is assumed to be valid for all TSS samples collected by
NBC, which do not report minerals content (Appendix B).
A trend analysis was performed on the mean values to identify the general shape of the vertical
profile of TSS during the summer months of any year (Table D-3, Fig. D-3). The trend equation
(R2 = 1 for the averages, R2 = 0.1312) was
Sz = 3.3841 Z2 - 1.8218 Z + 3.4957
Where Sz (mg L"1) is the calculated TSS concentration at the normalized depth, Z, below the
water surface.
The histograms of actual TSS measurements in 2014-2015 are presented in Fig. D-4. Most of the
measurements have concentrations below 5 mg L"1. More than 80% of the measurements show
concentrations 5 mg L"1 or less. These concentrations include detritus and phytoplankton.
Background detritus concentrations from the watershed and the water column are estimated from
TSS concentrations during the cold months (November and December) when phytoplankton is
minimal. Figure D-5 presents TSS concentrations from all samples and duplicates at the surface,
middle, and bottom of the water column for all 8 stations. Table D-4 presents the statistical
parameters for detritus measurements. The overall mean concentration of detritus is -1.13 mg L"1
(22%), which is assumed to be present in the water column throughout the year. The estimated
phytoplankton concentration is ~ 0.5 mg dry weight L"1 (~ 10%) (See Fig. 19). Thus, the above-
47
-------
mentioned ratio of organic matter (35%) is approximately one third from phytoplankton and two
thirds from watershed detritus.
Figure D-6 presents observed TSS concentrations with tide elevation for 2014-2015. With few
exceptions, observed high TSS concentrations exist during spring tides.
•
2 ,
.11
40'
41°
30'
£ C Blackstone River
V i \
(A) (B)
Figure D-l. Locations of sampling stations in Narragansett Bay. (A) TSS stations used by
AED in 2014-2015 (see Table D-l), and (B) Chl-or stations used by URI in 2009.
48
-------
Average TSS in NB 2014
• Avg TSS
Avg Minerals
Avgorganics
% minerals %Organic
Date
(A)
20
18
•j= 10
ra
4= 8
c
U
Average TSS in NB2015
AvgTSS Avg Minerals
% minerals %Organic
i -»
§
r 100
- 90
- 80
- 70
- 60 |
- 50 "ro
- 30
- 10
- 0
VD LTI r--
«. ^ CL
rH (N (V)
a
a
CTl
m
(N
i n
Sr
iN
tH"
Date
(B)
Figure D-2. Time series of the observed average TSS concentrations. (A) 2014, and (B) 2015.
49
-------
I 5
ro 4
I 3
u
§ 2
u
1
0
(A)
12
-10
_j
no
-§ 8
I 6
-
o
TSS Trend
V = 3.3841X2 - 1.8218X + 3.4957
R2 = l
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Normalized depth
TSS Trend
' = 3.3841X2 - 1.8218X + 3.4957
R2= 0.1312
i
i
0.2
0.4 0.6
Normalized depth
0,8
(B)
Figure D-3. The vertical trend of the observed TSS concentrations at the surface, middle, and
bottom of the water column during the summer months (June, July, and August): (A) trend of
mean values with error bars represent ± standard deviations (Table D-4), and (B) trend with
actual values.
50
-------
100 -
80 -
>
I-
2
40 -
20 -
2014 Histogram
^^ Frequency — • — Cumulative %
.^-~"~~~-
X-^
f
llh i,..
* 'lD CO 0 'rN '<* ' CO 0 'fN W '^ CO 0 '(S '^ 'lB CO O '(N V 'lO 'cO O
Concentration (mg L1)
90%
80%
70%
60%
50%
40%
30%
20%
10%
250 -|
200 -
, 150
I
"• 100
so -
0 -P
2015 Histogram
^H Frequency —•—Cumulative %
r"~~
i
\
.
, i, i, i, i, •!•- , ,.,.,.,-,., ,.,.,. -i ,,-,,,,-,,,
Concentration (mg L ')
100%
90%
so:;
70%
60%
50%
40%
30%
20%
10%
0%
(A)
(B)
250 -i
200 -
>.150 -
V
2
i 100
50 -
r-,
2014-2015 Histogram
^^ Frequency —•— Cumulative %
.-—"""""*
ir
llll.i
"'""SEISSSSSSSSSSSSSgSSSSS
Concentration (mg L1)
- 100%
90%
80%
70%
- 60%
50%
40%
30%
20%
- 10%
O"/
(C)
Figure D-4. Histograms of observed TSS concentrations: (A) 2014, (B) 2015, and (C) 2014
and 2015.
51
-------
o
I
£
Nov, 2014 •Dec, 2014 Nov, 2015 Dec, 2015
. il' . •.-
•+••+•••• ,^v«
!••• ^** **•• .•
0
10
20 30
Sample Number
40
50
Figure D-5. Detritus concentration from 48 samples during each winter month (November and
December) of 2014 and 2015 (Table D-4). The 48 samples represent 6 samples at each one of
the 8 station (Fig. D-l) which included 2 replicates at the surface, 2 replicates at mid depth,
and 2 replicates at the bottom.
52
-------
60
2014
TSS (mg/L)
-Tide (m)
Date
£
-------
Table D-l. Station locations for TSS samples collected by AED in 2014-2015
Station # Latitude (N)
1 41
2 41
3 41
4 41
5 41
6 41
7 41
8 41
45.
41.
.606
.939
39.5
35.
29.
38.
.9
.553
.5
33.998
29.
.693
Longitude (W)
071
071
071
071
071
071
071
071
22.
19.
23.
22.
24.
18.
18.
21.
.696
.564
.2
.9
.695
.6
.665
.229
Location Approximate Depth (m)
Prov. River
Upper Bay
S Warwick Neck
E
W
SE
of Quonset Pt
SEofGSO
of Hog Island
of Prudence Is
W of Ft. Adams
6-8
7-9
5-6
11
15
10-11
18
33
Table D-2. General statistical parameters from AED observations of suspended sediment
concentrations (mg L"1) in Narragansett Bay in 2014-2015
Statistical Parameter
Meana
Standard Error
Median
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Count
Confidence Level
(95.0%)
TSS
(mgL-1)
5.12
0.73
4.45
3.11
9.68
4.63
1.87
12.77
1.98
14.76
18
1.55
Minerals
(mgL-1)
3.51
0.60
2.84
2.53
6.42
3.45
1.71
9.95
1.05
11.01
18
1.26
Organics
(mgL-1)
1.61
0.18
1.55
0.77
0.59
2.52
1.04
3.26
0.49
3.75
18
0.38
Minerals
(%)
65.35
3.02
68.76
12.83
164.58
-1.27
-0.20
39.14
45.01
84.15
18
6.38
Organics
(%)
34.65
3.02
31.24
12.83
164.58
-1.27
0.20
39.14
15.85
54.99
18
6.38
a All measurements at the surface, mid-depth, and bottom at all 8 stations contributed to the
overall mean value
54
-------
Table D-3. Statistical parameters of overall mean TSS concentrations (mg L"1) at surface, middle,
and bottom of the water column.
Statistical parameter
Mean
Standard Error
Median
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Count
Confidence Level (95. C
Surface Mid-depth
3.50 3.43
0.33 0.44
3.32 3.12
1.31 1.77
1.72 3.13
-0.72 3.75
0.45 1.58
4.19 7.22
1.60 1.29
5.79 8.51
16 16
i%) 0.70 0.94
Bottom
5.06
0.67
4.24
2.67
7.13
0.18
0.99
8.38
2.14
10.53
16
1.42
Table D-4. Statistical parameters of background detritus concentration (mg L"1) from the
watershed and the water
Statistical Parameters
Mean
Standard Error
Median
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Count
Confidence Level
(95.0%)
column based on values in November and
Nov, 2014 Dec, 2014
1.25 1.20
0.04 0.08
1.26 1.14
0.30 0.53
0.09 0.28
-0.70 5.58
0.15 2.00
1.18 2.86
0.70 0.48
1.88 3.34
48 48
0.09 0.15
Nov, 2015
0.97
0.04
0.94
0.31
0.10
20.43
3.81
2.24
0.46
2.70
48
0.09
December of 2014 and 2015
Dec, 2015
1.09
0.10
1.12
0.66
0.43
3.24
1.47
3.07
0.19
3.26
47
0.19
55
-------
D.2. Collins TSS data in 1973
Collins TSS data were collected from 32 stations in the East Passage, West Passage, Sakonnet
River, and Rhode Island Sound during March and April of 1973 (Collins 1976) (Fig. D-7, Table
D-5). Table D-6 presents the statistical parameters of the collected data within the Bay. The
observed mean TSS concentrations at the surface and bottom were 1.02 mg L"1 and 1.66 mg L"1,
respectively, with ranges (0.46-1.44 mg L"1) and (0.97-3.23 mg L"1), respectively. The TSS
concentrations in the West Passage showed increasing values from the middle bay toward the
Bay mouth (Fig. D-8). The average of the stations in the RI Sound (~ 1.0 mg L"1) represented the
yearly TSS concentration at the seaward boundary.
?I*30'
• Spot stations
ttattone
Bottom samples
Figure D-7. Station locations for TSS measurements in lower Narragansett Bay (Collins 1976).
56
-------
Table D-5. Measured TSS concentration from Collins (1976)
Bay location Station
West Passage
Wl
W2
W3
W4
W5
W6
W7
W8
W9
East Passage
El
E2
E3
E4
E5
E6
Sakonnet River
SI
S2
S3
S4
S5
S6
S7
S8
Depth
(m)
5
7
8
10
19
5
19
17
9
8
13
22
16
16
27
3
Distance
(km)
0
0
0
5
5
5
13.93
13.93
13.93
0
0
7.14
7.14
9.65
14.65
0
0
5
5
10.7
10.7
16.1
16.1
Surface TSS
(mgL-1)
1.44
1.4
1.21
1.19
0.97
0.84
1.27
0.92
1.07
1.36
0.91
0.59
0.71
0.46
1.19
2.03
1.39
0.94
3.03
1.56
0.84
1.31
Bottom TSS
(mgL-1)
1.71
1.51
1.21
1.79
2.02
1.43
3.17
1.58
3.23
1.48
1.41
1.37
1.02
0.97
1.03
5.46
2.75
1.25
6.78
4.3
5.36
57
-------
Table D-6. Statistical parameters for surface and bottom TSS concentrations (mg L"1) from
Collins (1976).
Parameter
Mean
Standard Error
Median
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Count
Confidence Level (95.0%)
Surface
1.02
0.08
1.02
0.31
0.09
-0.82
-0.35
0.98
0.46
1.44
14
0.18
Bottom
1.66
0.18
1.48
0.69
0.47
2.02
1.60
2.26
0.97
3.23
15
0.38
Concentration (mg L1)
O l-» NJ CO
oLni— 'Lnl-oLnOJLn
• Su
1 ir
j_
rface
ear (Surfa
• Bottom • Ave
ce) •••• Linear (Bottom) •• Lin<
^{f
— •—
__..'•""
,*»*•*****
rage
;ar( Average)
._
i 2 4 6 8 10 12 14 16
Distance (km)
Figure D-8. Longitudinal TSS concentrations in the West Passage from mid-Bay (stations
W 1,2,3) to the Bay mouth (Collins 1976). Linear trends are presented for surface, bottom, and
average concentrations along the lower Bay.
58
-------
D.3. Morton TSS data in 1965
Morton's TSS data were collected at the surface and bottom from stations within Narragansett
Bay and Rhode Island Sound during October-November, 1965 (Fig D-9, Table D-7) (Morton,
1967). Station PR-1 showed extremely high TSS concentrations (96.38 mg L"1 at surface and
13.21 mg L"1 at bottom) which sharply dropped due to deposition within a short distance as
indicated by observations at station PR-2. Statistical parameters for the other stations within
Narragansett Bay are presented in Table (D-8). The overall average (2.56 mg L"1) is used to
represent initial TSS concentration in the Bay.
x
Ris-a
R1S-5
X
RIS-5
RIS-G
X
RIS-C
X
RI3-0
Figure D-9. Stations for TSS data reported by Morton (1967).
59
-------
Table D-7. TSS concentrations reported by Morton (1967)
Station
PR-2
PR-3
EP-1
EP-2
EP-3
WP-1
WP-2
WP-3
WP-4
Surface TSS
(mgL-1)
4.71
3.96
2.13
1.48
0.79
2.87
2.56
2.72
1.63
Bottom TSS
(mgL-1)
4.71
3.22
2.18
2.17
0.93
2.62
3.45
2.65
1.31
Average
(mgL-1)
4.71
3.59
2.16
1.83
0.86
2.75
3.01
2.69
1.47
Table D-8. Statistical parameters for TSS concentrations (mg L"1) collected by Morton
(After Morton 1967, Schencketal. 1973).
Mean
Standard Error
Median
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Count
Confidence Level (95.0%)
2.54
0.37
2.55
1.16
1.34
0.24
0.52
3.92
0.79
4.71
10
0.83
2.58
0.34
2.60
1.07
1.15
0.81
0.43
3.78
0.93
4.71
10
0.77
2.56
0.35
2.62
1.09
1.19
0.68
0.47
3.85
0.86
4.71
10
0.78
60
-------
D.4. Schenck and Davis data in 1971
Schenck and Davis (1973) compared their turbidity data during the summer of 1971 with TSS
data from Morton (1967) (Table D-7). The turbidity data indicated reduced turbidity (i.e., higher
water clarity) towards the mouth of the Bay in the East and West Passages. This trend differs
from observations by Collins (1973) in March and April of 1973 (Fig. D-8) and the monthly
observations by Oviatt and Nixon (1975) during 1972-1973. The reason may be attributed to the
fact that turbidity is affected by other water properties including colored dissolved organic matter
(CDOM) and colloids, which do not contribute to TSS, but contribute to water clarity.
Figure D-10. Stations for turbidity measurements (Schenck and Davis 1973).
61
-------
D.5. Oviatt and Nixon data in 1972-1973
Oviatt and Nixon presented their monthly sediment resuspension and deposition data at three
locations in the upper, middle, and lower Bay during 1972-1973 (Oviatt and Nixon 1975). The
data indicated total deposition of 18.3 kg m"2 year"1 in the lower bay, 11 kg m"2 year"1 in the mid-
bay, and 7.4 kg m"2 year"1 in the upper bay.
41*45
4!" 35'
41"
RHODE ISLAND SOUND
71° 15'
Figure D-l 1. Stations for deposition from Oviatt and Nixon (1975).
62
-------
sdser.inp
snser.inp
sedw.inp
sndw.inp
bedbdn
Appendix E. Input files
The EFDC input files for TSS included the following files:
sedb.inp Cohesive sediment in the bed (%)
sndb.inp Non-cohesive sediment in the bed (%)
Concentration of cohesive sediment in inflows (mg L"1)
Concentration of non-cohesive sediment in inflows (mg L"1)
Initial concentration of cohesive sediment in the water column (mg L"1)
Initial concentration of non-cohesive sediment in the water column (mg L"1)
Bed bulck density (kg m"3)
bedddn.inp Bed dry density in terms of porosity ratio (0-1)
bedlay.inp Bed layer thickness (m)
63
-------
Appendix F: Input parameters for the EFDC model
This appendix includes the card input images for Narragansett Bay input parameters used in the input
file efdc.inp for the EFDC model. Card numbers are shown (e.g., C24) at the beginning of each card,
followed by the code names for the parameters and their descriptions, and ending with the values used
for Narragansett Bay. Cards are separated by a broken (dashed) line.
C24 VOLUMETRIC SOURCE/SINK LOCATIONS, MAGNITUDES, AND CONCENTRATION SERIES
C
IQS: I CELL INDEX OF VOLUME SOURCE/SINK
JQS: J CELL INDEX OF VOLUME SOURCE/SINK
QSSE: CONSTANT INFLOW/OUTFLOW RATE IN M*M*M/S
NQSMUL: MULTIPLIER SWITCH FOR CONSTANT AND TIME SERIES VOL S/S
= 0 MULT BY 1. FOR NORMAL IN/OUTFLOW (L*L*L/T)
= 1 MULT BY DY FOR LATERAL IN/OUTFLOW (L*L/T) ON U FACE
= 2 MULT BY DX FOR LATERAL IN/OUTFLOW (L*L/T) ON V FACE
= 3 MULT BY DX+DY FOR LATERAL IN/OUTFLOW (L*L/T) ON U&V FACES
NQSMFF: IF NON ZERO ACCOUNT FOR VOL S/S MOMENTUM FLUX
= 1 MOMENTUM FLUX ON NEC U FACE
= 2 MOMENTUM FLUX ON NEC V FACE
= 3 MOMENTUM FLUX ON POSU FACE
= 4 MOMENTUM FLUX ON POSV FACE
NQSERQ: ID NUMBER OF ASSOCIATED VOLUMN FLOW TIME SERIES
NSSERQ: ID NUMBER OF ASSOCIATED SALINITY TIME SERIES
NTSERQ: ID NUMBER OF ASSOCIATED TEMPERATURE TIME SERIES
NDSERQ: ID NUMBER OF ASSOCIATED DYE CONCTIME SERIES
NSFSERQ: ID NUMBER OF ASSOCIATED SHELL FISH LARVAE RELEASE TIME SERIES
NTXSERQ: ID NUMBER OF ASSOCIATED TOXIC CONTAMINANT CONCTIME SERIES
NSDSERQ: ID NUMBER OF ASSOCIATED COHEASIVE SEDIMENT CONC TIME SERIES
NSNSERQ: ID NUMBER OF ASSOCIATED NONCOHEASIVE SED CONCTIME SERIES
QSFACTOR: FRACTION OF TIME SERIES FLOW NQSERQ ASSIGNED TO THIS CELL
C24
IQS
10
11
12
46
12
5
24
12
12
14
24
26
36
18
14
9
3
40
8
JQS
43
38
45
47
53
27
38
48
40
38
34
28
3
14
13
21
27
33
17
QSSE
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NQSMUL
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NQSMFF
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NQSERQ
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
NS-
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
1
NT-
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
1
ND-
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NSF-
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NTX-
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NSD-
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
NSN-
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
QSFACT
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
1 !
Woonsq & Mosh River
Pawtuxet River
Ten Mile River
Taunton River
Blackstone River
Hunt River
Warren/Palmer River
Bucklin Pt. WWTP
Fields Pt. WWTP
E. Providence WWTP
Warren WWTP
Bristol WWTP
Fall River WWTP
Newport WWTP
Jamestown WWTP
Quonset Pt. WWTP
E. Greenwich WWTP
Somerset WWTP
West-branch Riparian
64
-------
17 17 0 0 0 19 11000 19 19 1 ! East-branch Riparian
32 17 0 0 0 19 11000 19 19 1 ! Sakonnet Riparian
3 26 0 0 0 20 11000 20 20 1 ! Groupl Greenwich Cove
3 31 0 0 0 21 11000 20 20 1 ! Group2 Apponaug Cove
9 30 0 0 0 22 11000 20 20 1 ! Groups Oakland Beach
C36 SEDIMENT INITIALIZATION AND WATER COLUMN/BED REPRESENTATION OPTIONS
C DATA REQUIRED EVEN IF ISTRAN(6) AND ISTRAN(7) ARE 0
C
ISEDINT: 0 FOR CONSTANT INITIAL CONDITIONS
1 FOR SPATIALLY VARIABLE WATER COLUMN INITIAL CONDITIONS
FROM SEDW.INP AND SNDW.INP
2 FOR SPATIALLY VARIABLE BED INITIAL CONDITIONS
FROM SEDB.INP AND SNDB.INP
3 FOR SPATIALLY VARIABLE WATER COL AND BED INITIAL CONDITIONS
ISEDBINT: 0 FOR SPATIALLY VARYING BED INITIAL CONDITIONS IN MASS/AREA
1 FOR SPATIALLY VARYING BED INITIAL CONDITIONS IN MASS FRACTION
OF TOTAL SEDIMENT MASS (REQUIRES BED LAYER THICKNESS
FILE BEDLAY.INP)
ISEDWC: 0 COHESIVE SED WC/BED EXCHANGE BASED ON BOTTOM LAYER CONDITIONS
1 COHESIVE SED WC/BED EXCHANGE BASED ON WAVE/CURRENT/SEDIMENT
BOUNDARY LAYERS EMBEDDED IN BOTTOM LAYER
ISMUD: 1 INCLUDE COHESIVE FLUID MUD VISCOUS EFFECTS USING EFDC
FUNCTION CSEDVIS(SEDT)
ISNDWC: 0 NONCOH SED WC/BED EXCHANGE BASED ON BOTTOM LAYER CONDITIONS
1 NONCOH SED WC/BED EXCHANGE BASED ON WAVE/CURRENT/SEDIMENT
BOUNDARY LAYERS EMBEDDED IN BOTTOM LAYER
ISEDVW: 0 FOR CONSTANT OR SIMPLE CONCENTRATION DEPENDENT
COHESIVE SEDIMENT SETTLING VELOCITY
XL CONCENTRATION AND/OR SHEAR/TURBULENCE DEPENDENT COHESIVE
SEDIMENT SETTLING VELOCITY. VALUE INDICATES OPTION TO BE USED
IN EFDC FUNCTION CSEDSET(SED,SHEAR,ISEDVWC)
1 HUANG AND METHA - LAKE OKEECHOBEE
2 SHRESTA AND ORLOB - FOR KRONES SAN FRANCISCO BAY DATA
3 ZIEGLER AND NESBIT - FRESH WATER
98LICKFLOCCULATOIN
99 LICK FLOCCULATION WITH FLOC DIAMETER ADVECTION
ISNDVW: 0 USE CONSTANT SPECIFIED NON-COHESIVE SED SETTLING VELOCITIES
OR CALCULATE FOR CLASS DIAMETER IF SPECIFIED VALUE IS NEC
XL FOLLOW OPTION 0 PROCEDURE BUT APPLY HINDERED SETTLING
CORRECTION. VALUE INDICATES OPTION TO BE USED WITH EFDC
FUNCTION CSNDSET(SND,SDEN,ISNDVW) VALUE OF ISNDVW INDICATES
EXPONENTIAL IN CORRECT (1-SDEN(NS)*SND(NS)**ISNDVW
KB: MAXIMUM NUMBER OF BED LAYERS (EXCLUDING ACTIVE LAYER)
ISDTXBUG: 1 TO ACTIVATE SEDIMENT AND TOXICS DIAGNOSTICS
C36
ISEDINT ISEDBINT ISEDWC ISMUD ISNDWC ISEDVW ISNDVW KB ISDTXBUG
210000010
C36a SEDIMENT INITIALIZATION AND WATER COLUMN/BED REPRESENTATION OPTIONS
C DATA REQUIRED EVEN IF ISTRAN(6) AND ISTRAN(7) ARE 0
C
ISBEDSTR: 0 USE HYDRODYNAMIC MODEL STRESS FOR SEDIMENT TRANSPORT
1 SEPARATE GRAIN STRESS FORM TOTAL IN COH AND NONCOH COMPONENTS
2 SEPARATE GRAIN STRESS FROM TOTAL APPLY TO COH AND NONCOH SEDS
3 USE INDEPENDENT LOG LAW ROUGHNESS HEIGHT FOR SEDIMENT TRANSPORT
READ FROM FILE SEDROUGH.INP
4 SEPARATE GRAIN STRESS FROM TOTAL USING COH/NONCOH WEIGHTED
ROUGHNESS AND LOG LAW RESISTANCE (IMPLEMENTED 5/31/05)
5 SEPARATE GRAIN STRESS FROM TOTAL USING COH/NONCOH WEIGHTED
ROUGHNESS AND POWER LAW RESISTANCE (IMPLEMENTED 5/31/05)
ISBSDIAM: 0 USE D50 DIAMETER FOR NONCOHESIVE ROUGHNESS
1 USE 2*D50 FOR NONCOHESIVE ROUGHNESS
65
-------
2 USE D90 FOR NONCOHESIVE ROUGHNESS
3 USE 2*D90 FOR NONCOHESIVE ROUGHNESS
ISBSDFUF: 1 CORRECT GRAIN STRESS PARTITIONING FOR NONUNIFORM FLOW EFFECTS
CAN NOW BE USED FOR ISBEDSTR=4 AND 5
COEFTSBL: COEFFICIENT SPECIFYING THE HYDRODYNAMIC SMOOTHNESS OF
TURBULENT BOUNDARY LAYER OVER COEHESIVE BED IN TERMS OF
EQUIVALENT GRAIN SIZE FOR COHESIVE GRAIN STRESS
CALCULATION, FULLY SMOOTH = 4, FULL ROUGH = 100.
NOT USED FOR ISBEDSTR=4 AND 5
VISMUDST: KINEMATIC VISCOSITY TO USE IN DETERMINING COHESIVE GRAIN STRESS
ISBKERO: 1 FOR BANK EROSION SPECIFIED BY EXTERNAL TIME SERIES
2 FOR BANK EROSION INTERNALLY CALCULATED BY STABILITY ANALYSIS
C36a
ISBEDSTR ISBSDIAM ISBSDFUF COEFTSBL VISMUDSTISBKERO
0004 l.OOE-06 0
C36B SEDIMENT INITIALIZATION AND WATER COLUMN/BED REPRESENTATION OPTIONS
C DATA REQUIRED EVEN IF ISTRAN(6) AND ISTRAN(7) ARE 0
C
ISEDAL: 1 TO ACTIVATE STATIONARY COHESIVE MUD ACTIVE LAYER
ISNDAL: 1 TO ACTIVATE NON-COHESIVE ARMORING EFFECTS
2 SAME AS 1 WITH ACTIVE-PARENT LAYER FORMULATION
IALTYP: OCONSTANTTHICKNESS ARMORING LAYER
1 CONSTANTTOTAL SEDIMENT MASS ARMORING LAYER
IALSTUP: 1 CREATE ARMORING LAYER FROM INITIALTOP LAYER AT START UP
ISEDEFF: 1 MODIFY NONCOHESIVE RESUSPENSION TO ACCOUNT FOR COHESIVE EFFECTS
USING MULTIPLICATION FACTOR: EXP(-COEHEFF*FRACTION COHESIVE)
2 MODIFY NONCOHESIVE CRITICAL STRESS TO ACCOUNT FOR COHESIVE EFFECTS
USING MULT FACTOR: 1+(COEHEFF2-1)*(1-EXP(-COEHEFF*FRACTION COHESIVE))
HBEDAL: ACTIVE ARMORING LAYER THICKNESS
COEHEFF: COHESIVE EFFECTS COEFFICIENT
COEHEFF2: COHESIVE EFFECTS COEFFICIENT
C36B
ISEDAL ISNDAL IALTYP IALSTUP ISEDEFF HBEDAL COEHEFF COEHEFF2
00001 0.01 4 1
C37 BED MECHANICAL PROPERTIES PARAMETER SET 1
DATA REQUIRED EVEN IF ISTRAN(6) AND ISTRAN(7) ARE 0
C
ISEDDT: NUMBER OF SED/TOX BED PROCESSES STEPS PER HYDRO/WC TRANS STEPS
IBMECH: OTIME INVARIANT CONSTANT BED MECHANICAL PROPERITES
1 SIMPLE CONSOLIDATION CALCULATION WITH CONSTANT COEFFICIENTS
2 SIMPLE CONSOLIDATION WITH VARIABLE COEFFICIENTS DETERMINED
EFDC FUNCTIONS CSEDCON1,2,3(IBMECH)
3 COMPLEX CONSOLIDATION WITH VARIABLE COEFFICIENTS DETERMINED
EFDC FUNCTIONS CSEDCON1,2,3(IBMECH). IBMECH > 0 SETS THE
C38 PARAMETER ISEDBINT=1 AND REQUIRES INITIAL CONDITIONS
FILES BEDLAY.INP, BEDBDN.INP AND BEDDDN.IN
9 TYPE OF CONSOLIDATION VARIES BY CELL WITH IBMECH FOR EACH
DEFINED IN INPUT FILE CONSOLMAP.INP
IMORPH: 0 CONSTANT BED MORPHOLOGY (IBMECH=0, ONLY)
1 ACTIVE BED MORPHOLOGY: NO WATER ENTRAIN/EXPULSION EFFECTS
2 ACTIVE BED MORPHOLOGY: WITH WATER ENTRAIN/EXPULSION EFFECTS
HBEDMAX: TOP BED LAYER THICKNESS (M) AT WHICH NEW LAYER IS ADDED OR IF
KBT(I,J)=KB, NEW LAYER ADDED AND LOWEST TWO LAYERS COMBINED
BEDPORC: CONSTANT BED POROSITY (IBMECH=0, OR NSED=0)
ALSO USED AS POROSITY OF DEPOSITIN NON-COHESIVE SEDIMENT
SEDMDMX: MAXIMUM FLUID MUD COHESIVE SEDIMENT CONCENTRATION (MG/L)
SEDMDMN: MINIMUM FLUID MUD COHESIVE SEDIMENT CONCENTRATION (MG/L)
SEDVDRD: VOID RATIO OF DEPOSITING COHESIVE SEDIMENT
SEDVDRM: MINIMUM COHESIVE SEDIMENT BED VOID RATIO (IBMECH >0)
SEDVDRT: BED CONSOLIDATION RATED CONSTANT (I/SEC) (IBMECH = 1,2)
GT 0 CONSOLIDATE OVER TIME TO SEDVDRM
EQO CONSOLIDATE INSTANTANEOUSLYTO SEDVDRM
LTD CONSOLIDATE TO INITIAL VOID RATIOS
C37
66
-------
ISEDDT IBMECH IMORPH HBEDMAX BEDPORC SEDMDMXSEDMDMN SEDVDRD SEDVDRM SEDVRDT
2 0 0 10 0.4 l.OOE+04 5000 0.67 0.66667 -1
C38 BED MECHANICAL PROPERTIES PARAMETER SET 2 (CONSOLIDATION COEFFICIENTS)
C DATA REQUIRED EVEN IF ISTRAN(6) AND ISTRAN(7) ARE 0
C
IBMECHK: 0 FOR HYDRAULIC CONDUCTIVITY, K, FUNCTION K=KO*EXP((E-EO)/EK)
1 FOR HYD COND/(1+VOID RATIO),K', FUNCTION K'=KO'*EXP((E-EO)/EK)
BMECH1: REFERENCE EFFECTIVE STRESS/WATER SPECIFIC WEIGHT, SEO (M)
IF BMECHKO USE INTERNAL FUNCTION, BMECH1,BMECH2,BMECH3 NOT USED
BMECH2: REFERENCE VOID RATIO FOR EFFECTIVE STRESS FUNCTION, EO
BMECH3: VOID RATIO RATE TERM ES IN SE=SEO*EXP(-(E-EO)/ES)
BMECH4: REFERENCE HYDRAULIC CONDUCTIVITY, KO (M/S)
IF BMECH4O USE INTERNAL FUNCTION, BMECH1,BMECH2,BMECH3 NOT USED
BMECH5: REFERENCE VOID RATIO FOR HYDRAULIC CONDUCTIVITY, EO
BMECH6: VOID RATIO RATE TERM EK IN (K OR K')=(KO OR KO')*EXP((E-EO)/EK) |
C38
IBMECHK BMECH1 BMECH2 BMECH3 BMECH4 BMECH5 BMECH6
150 0.6667 l.OOE-07 0 0.6667
C39 COHESIVE SEDIMENT PARAMETER SET 1 REPEAT DATA LINE NSED TIMES
C DATA REQUIRED EVEN IF ISTRAN(6) AND ISTRAN(7) ARE 0
C
SEDO: CONSTANT INITIAL COHESIVE SEDIMENT CONC IN WATER COLUMN
(MG/LITER=GM/M**3)
SEDBO: CONSTANT INITIAL COHESIVE SEDIMENT IN BED PER UNIT AREA
(GM/SQ METER) IE 1CM THICKNESS BED WITH SSG=2.5 AND
N=.6,.5 GIVES SEDBO 1.E4, 1.25E4
SDEN: SEDIMENTSPEC VOLUME (IE 1/2.25E6 M**3/GM)
SSG: SEDIMENT SPECIFIC GRAVITY
WSEDO: CONSTANT OR REFERENCE SEDIMENT SETTLING VELOCITY
IN FORMULA WSED=WSEDO*( (SED/SEDSN)**SEXP )
SEDSN: NOT USED
SEXP: NOT USED
TAUD: BOUNDARY STRESS BELOW WHICH DEPOSITION TAKES PLACE ACCORDING
TO (TAUD-TAU)/TAUD (M**2/S**2)
ISEDSCOR: 1 TO CORRECT BOTTOM LAYER CONCENTRATION TO NEAR BED CONC
ISPROBDEP: 0 KRONE PROBABILITY OF DEPOSTION USING COHESIVE GRAIN STRESS
1 KRONE PROBABILITY OF DEPOSTION USING TOTAL BED STRESS
2 PARTHEN PROBABILITY OF DEPOSTION USING COHESIVE GRAIN STRESS
3 PARTHEN PROBABILITY OF DEPOSTION USING TOTAL BED STRESS
C39
SEDO SEDBO SDEN SSG WSEDO SEDSN SEXP TAUD ISEDSCOR ISPROBDEP
0 1.35E+05 4.40E-07 2.25 6.00E-05 1 0 4E-05 0 0
C40 COHESIVE SEDIMENT PARAMETER SET 2 REPEAT DATA LINE NSED TIMES
C DATA REQUIRED EVEN IT ISTRAN(6) AND ISTRAN(7) ARE 0
C
IWRSPlO USE RESUSPENSION RATE AND CRITICAL STRESS BASED ON PARAMETERS
ON THIS DATA LINE
XL USE BED PROPERTIES DEPENDEDNT RESUSPENSION RATE AND CRITICAL
STRESS GIVEN BY EFDC FUNCTIONS CSEDRESS AND CSEDTAUS
FUNCTION ARGUMENSTS ARE (BDENBED,IWRSP)
1 HWANG AND METHA-LAKE OKEECHOBEE
2 HAMRICK'S MODIFICATION OF SAN FORD AND MAA USING ACTUAL VOID RATIO
3 SAME AS 2 EXCEPT VOID RATIO OF COHESIVE SEDIMENT FRACTION IS USED
>99 SITE SPECIFIC
IWRSPBlO NO BULK EROSION
1 USE BULK EORSION CRITICAL STRESS AND RATE IN FUNCTIONS
CSEDTAUB AND CSEDRESSB
WRSPO: REF SURFACE EROSION RATE IN FORMULA
WRSP=WRSPO*( ((TAU-TAUR)/TAUN)**TEX ) (GM/M**2-SEC)
TAUR: BOUNDARY STRESS ABOVE WHICH SURFACE EROSION OCCURS (M/S)**2
TAUN: NORMALIZING STRESS (EQUAL TO TAUR FOR COHESIVE SED TRANS)
TEXP: EXPONENTIAL (COH SED)
VDRRSPO: REFERENCE VOID RATIO FOR CRITICAL STRESS AND RESUSPENSION RATE
67
-------
IWRSP=2,3
COSEDHID: COHESIVE SEDIMENT RESUSPENSION HIDING FACTOR TO REDUCE COHESIVE
RESUSPENSION BY FACTOR = (COHESIVE FRACTION OF SEDIMENT)**COSEDHID
C40
IWRSP IWRSPB WRSPO TAUR TAUN TEXP VDRRSPO COSEDHID
0 0 0.0005 0.0001 0.0001 110
C46 BUOYANCY, TEMPERATURE, DYE DATA AND CONCENTRATION BC DATA
C I
BSC: BUOYANCY INFLUENCE COEFFICIENT 0 TO 1, BSC=1. FOR REAL PHYSICS
TEMO: REFERENCE, INITIAL, EQUILIBRUM AND/OR ISOTHERMAL TEMP IN DEC C
HEQT: EQUILIBRUM TEMPERTURE TRANSFER COEFFICIENT M/SEC
ISBEDTEMI: 0 READ INTIAL BED TEMPERATURE FROM TEMPB.INP
1 INITIALIZE AT START OF COLD RUN
KBH: NUMBER OF BED THERMAL LAYERS
RKDYE: FIRST ORDER DECAY RATE FOR DYE VARIABLE IN I/SEC
NCBS: NUMBER OF CONCENTRATION BOUNDARY CONDITIONS ON SOUTH OPEN
BOUNDARIES
NCBW: NUMBER OF CONCENTRATION BOUNDARY CONDITIONS ON WEST OPEN
BOUNDARIES
NCBE: NUMBER OF CONCENTRATION BOUNDARY CONDITIONS ON EAST OPEN
BOUNDARIES
NCBN: NUMBER OF CONCENTRATION BOUNDARY CONDITIONS ON NORTH OPEN
BOUNDARIES
C46
BSC TEMO HEQT ISBEDTEMIKBH RKDYE NCBS NCBW NCBE
1 16 O.OOE+00 0 2 0 31 0 0
C47 LOCATION OF CONC EC'S ON SOUTH BOUNDARIES
C
ICBS: I CELL INDEX
JCBSlJ CELL INDEX
NTSCRS: NUMBER OF TIME STEPS TO RECOVER SPECIFIED VALUES ON CHANGE
TO INFLOW FROM OUTFLOW
NSSERS: SOUTH BOUNDARY CELL SALINITY TIME SERIES ID NUMBER
NTSERS: SOUTH BOUNDARY CELL TEMPERATURE TIME SERIES ID NUMBER
NDSERS: SOUTH BOUNDARY CELL DYE CONC TIME SERIES ID NUMBER
NSFSERS: SOUTH BOUNDARY CELL SHELLFISH LARVAE TIME SERIES ID NUMBER
NTXSERS: SOUTH BOUNDARY CELL TOXIC CONTAMINANT CONC TIME SERIES ID NUM.
NSDSERS: SOUTH BOUNDARY CELL COHESIVE SED CONC TIME SERIES ID NUMBER
NSNSERS: SOUTH BOUNDARY CELL NONCOHESIVE SED CONC TIME SERIES ID NUMBER
C47
NCBN
0
IBBS
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
JBBS
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
NTSCRS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
NSSERS
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
NTSERS
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
NDSERS
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NSFSERS
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NTXSERS
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NSDSERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
NSNSERS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
68
-------
Ol
UJUJUJUJUJUJUJUJ
OOOOOOOO
OOOOOOOO
OOOOOOOO
-------
Appendix G: Predicted TSS results for Narragansett Bay
The following results are for predictions of cohesive sediment concentrations in Narragansett Bay
during the year 2009 with a settling speed of 6 x 10"5 m s'1.
- Bottom TSS
- Surface TSS
PD
— Springtide
~|
Deposition Discharge
r 350
Date
Figure G-l. Predicted TSS concentration and sediment deposition at station PD.
Bottom TSS
- Surface TSS
PR
— Springtide
Deposition Discharge
r 1200
Date
Figure G-2. Predicted TSS concentration and sediment deposition at station PR.
70
-------
o
r- 1-
ft)
o
o
o
I
o
a
&;
3'
CD
r-K
&-
cp
T3
O
to
O
8
o
Concentration (mg L1)
ro UJ 4i Cn
1/12/10
o
ro
TD
o
Discharge (m3?1),Deposition (g nrr:
f
9
UJ
&
o'
O
O
o
CD
r- K
I
O
a>
&;
3'
G
r-K
&-
fB
T3
O
O
8
td
Concentration (mg L1)
Ul 01
1/12/10
NJ NJ UJ UJ
s g s a
Discharge (m3 ^Deposition (g m2)
o
-------
Bottom TSS
• Surface TSS
NPI
— Springtide
Deposition Discharge
- 350
Date
Figure G-5. Predicted TSS concentration and sediment deposition at station NPI.
Bottom TSS
• Surface TSS
Deposition Discharge
- 350
Figure G-6. Predicted TSS concentration and sediment deposition at station MV.
72
-------
Bottom TSS
• Surface TSS
QPI
Springtide
Deposition Discharge
$ s
Date
Figure G-7. Predicted TSS concentration and sediment deposition at station QPI.
Bottom TSS
• Surface TSS
GD
— Springtide
Deposition Discharge
- 350
CO
o
or
s
rH
° 1
*i ^
3 g
H rH
g
5
g
Sf
g
S
g
jj.
g
to
g
crT
cn
o
§•
rH
at
o
rH"
rH
cn
o
r?
rH
O
rH
rH
Date
Figure G-8. Predicted TSS concentration and sediment deposition at station GD.
73
-------
Bottom TSS
• Surface TSS
GB
— Springtide
Deposition Discharge
r 350
Date
Figure G-9. Predicted TSS concentration and sediment deposition at station GB.
Bottom TSS
• Surface TSS
SR
— Springtide
Deposition Discharge
r 350
Date
Figure G-10. Predicted TSS concentration and sediment deposition at station SR.
74
-------
Bottom TSS
•Surface TSS
PP
— Springtide
Deposition Discharge
Figure G-11. Predicted TSS concentration and sediment deposition at station PP.
• Bottom TSS
• Surface TSS
•Deposition Discharge
Figure G-12. Predicted TSS concentration and sediment deposition at station TW.
75
-------
Ol
t
fS
O
O-
a
a-
H
t/3
t/3
O
O
o
r+
I.
O
fa
a-
VI
a-
§'
o
B
a-
n>
T3
o
OJ
O
S
wa
r-K
&.
o
Concentration (mg L'1)
O M M UJ *>
1/12/10
o
IE
-
8888888888
o
Discharge (m3^1),Deposition (g rrv2)
03
§
O
3-
n
ro
3
^+
oJ
O
ns
•O
o
8 g 8 S 8 S
Discharge (m3?1),Deposition (g rrr2)
------- |