technical data report hydrocarbon mass balance …hydrocarbon mass balance estimates: inputs for...

Technical Data Report

Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning

ENBRIDGE NORTHERN GATEWAY PROJECT

Hay and Company Consultants Vancouver, British Columbia

James Stronach, Ph.D., P.Eng.

2011

Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning Technical Data Report Preface

2011 Page i

Preface

This technical data report describes modelling that predicts the behaviour of spilled hydrocarbons in a marine environment. The mass balance estimates (from which are derived estimated pathways of spilled hydrocarbon) were used in the Application, Volume 7C and Volume 8C, but without a detailed description of the modelling, which is contained in this technical data report.

Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning Technical Data Report Table of Contents

2011 Page iii

Table of Contents

1 Introduction .................................................................................................................... 1-1 2 Description and Application of Numerical Models..................................................... 2-1

2.1 Hydrodynamic Model...................................................................................................... 2-1 2.1.1 Regional Model .......................................................................................................... 2-8 2.1.2 Local Model ............................................................................................................. 2-11 2.1.3 Kinematic Wind Model ............................................................................................ 2-13

2.2 Oil Spill Model .............................................................................................................. 2-17 2.2.1 Input and Forcing Data ............................................................................................. 2-18 2.2.2 Hydrocarbon Weathering Model .............................................................................. 2-19

3 Model Validation ............................................................................................................ 3-1 3.1 Hydrodynamic Model...................................................................................................... 3-1

3.1.1 Validation of the Regional Model .............................................................................. 3-1 3.1.2 Validation of the Local Model ................................................................................... 3-6 3.1.3 Validation against ASL Observations in 2005 ......................................................... 3-10 3.1.4 Validation of Kinematic Wind Model ...................................................................... 3-25

3.2 Oil Spill Model .............................................................................................................. 3-25 3.2.1 Spill Examples ......................................................................................................... 3-25

4 Model Results ................................................................................................................. 4-1 4.1 Hydrodynamic Model...................................................................................................... 4-1

4.1.1 River Inflow Effects ................................................................................................... 4-1 4.1.2 Wind and Tidal Effects .............................................................................................. 4-5

4.2 Oil Spill Model .............................................................................................................. 4-11 4.2.1 Kitimat Terminal ...................................................................................................... 4-11 4.2.2 Emilia Island ............................................................................................................ 4-16 4.2.3 Principe Channel ...................................................................................................... 4-18 4.2.4 Wright Sound ........................................................................................................... 4-21 4.2.5 Ness Rock in Caamaño Sound ................................................................................. 4-23 4.2.6 Butterworth Rocks in North Hecate Strait ................................................................ 4-26

5 Summary and Recommendations ................................................................................. 5-1 6 References ....................................................................................................................... 6-1

6.1 Literature Cited ............................................................................................................... 6-1 6.2 Personal Communications ............................................................................................... 6-3 6.3 Internet Sites .................................................................................................................... 6-3

Appendix A Models – Additional Technical Information ............................................ A-1 Appendix B Surface Currents and Salinities at the Head of Kitimat Arm .................B-1 Appendix C Specific Trajectory Examples .................................................................... C-1


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List of Tables

Table 2-1 Shore Types and Oil Retention .......................................................................... 2-18Table 3-1 Comparison of Harmonic Constants for Observed and Modelled Water

Levels: M2 ............................................................................................................ 3-1Table 3-2 Comparison of Observed and Modelled Harmonic Constants: M2 ..................... 3-6Table 4-1 Condensate Mass Balance at Kitimat Terminal ................................................. 4-12Table 4-2 Diluted Bitumen Mass Balance for Kitimat Terminal ....................................... 4-14Table 4-3 Syncrude Synthetic Light Oil Mass Balance for Emilia Island ......................... 4-17Table 4-4 Diluted Bitumen Mass Balance for Principe Channel ....................................... 4-20Table 4-5 Diluted Bitumen Mass Balance for Wright Sound ............................................ 4-22Table 4-6 Diluted Bitumen Mass Balance for Ness Rock .................................................. 4-25Table 4-7 Syncrude Synthetic Light Oil Mass Balance for Butterworth Rocks ................ 4-27

List of Figures

Figure 1-1 Hypothetical Mass Balance Plot − Example Locations ....................................... 1-2Figure 2-1 Model Process Flowchart ..................................................................................... 2-1Figure 2-2 Bathymetry: 3-km Grid Model ............................................................................ 2-3Figure 2-3 Bathymetry: 400-m Grid Model .......................................................................... 2-4Figure 2-4 Typical Model Grid Mesh .................................................................................... 2-6Figure 2-5 Wind Observation Sites, 2004: 3-km Grid Model ............................................... 2-9Figure 2-6 Freshwater Inflow Sites: 3-km Grid Model ....................................................... 2-10Figure 2-7 River Inflow Locations: 400-m Grid Model ...................................................... 2-12Figure 2-8 H3D Hydrodynamic Model: Interpolated Wind Field ....................................... 2-14Figure 2-9 Kinematic Wind Model: Initial Interpolation Flow Field .................................. 2-15Figure 2-10 Kinematic Wind Model: Volume-Conserving Flow Field ................................ 2-16Figure 3-1 M2 Co-Amplitude, Co-Phase: 3-km Grid Model ................................................. 3-2Figure 3-2 Simulated Sea Surface Temperature, 3-km Grid Model ...................................... 3-4Figure 3-3 Simulated Sea Surface Temperature .................................................................... 3-5Figure 3-4 3-km Model Current Validation ........................................................................... 3-7Figure 3-5 3-km Model Drifter Validation ............................................................................ 3-8Figure 3-6 M2 Co-Amplitude, Co-Phase: 400-m Grid Model ............................................... 3-9Figure 3-7 Current Meter Locations .................................................................................... 3-11Figure 3-8 CTD and Model Temperature and Salinity ........................................................ 3-12Figure 3-9 400-m Model Current Validation: CM1, September to October 2005 .............. 3-14Figure 3-10 400-m Model Current Validation: CM1, October to November 2005 .............. 3-15Figure 3-11 400-m Model Current Validation: CM2, September to October 2005 .............. 3-16Figure 3-12 400-m Model Current Validation: CM2, October to November 2005 .............. 3-17


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Figure 3-13 400-m Model Current Validation: CM4, September to October 2005 .............. 3-18Figure 3-14 400-m Model Current Validation: CM4, October to November 2005 .............. 3-19Figure 3-15 Harmonic Analysis for Validation: Current Meter Site 1 .................................. 3-21Figure 3-16 Harmonic Analysis for Validation: Current Meter Site 2 .................................. 3-22Figure 3-17 Harmonic Analysis for Validation: Current Meter Site 4 .................................. 3-23Figure 3-18 Comparison of Modelled and Observed Winds: January and July 2004 ........... 3-24Figure 4-1 Surface Currents in Kitimat Arm near High Tide ................................................ 4-3Figure 4-2 Mean Surface Currents ̶ Local Model ................................................................ 4-4Figure 4-3 Time Series for Model Surface Layer at Current Meter Site 2 ............................ 4-6Figure 4-4 Time Series for Model Layer12 at Current Meter Site 2 ..................................... 4-8Figure 4-5 Time Series for Model Layer16 at Current Meter Site 2 ................................... 4-10Figure 4-6 Wind Speed and Direction for Kitimat Terminal ̶ Condensate Spill ................ 4-12Figure 4-7 Condensate Mass Balance for Kitimat Terminal ............................................... 4-13Figure 4-8 Wind Speed and Direction for Kitimat Terminal ̶ Diluted Bitumen Spill ........ 4-14Figure 4-9 Diluted Bitumen Mass Balance for Kitimat Terminal ....................................... 4-15Figure 4-10 Wind Speed and Direction for Emilia Island ..................................................... 4-16Figure 4-11 Syncrude Synthetic Light Oil Mass Balance for Emilia Island ......................... 4-18Figure 4-12 Wind Speed and Direction for Principe Channel ............................................... 4-19Figure 4-13 Diluted Bitumen Mass Balance for Principe Channel ....................................... 4-20Figure 4-14 Wind Speed and Direction for Wright Sound .................................................... 4-22Figure 4-15 Diluted Bitumen Mass Balance for Wright Sound ............................................ 4-23Figure 4-16 Wind Speed and Direction for Ness Rock ......................................................... 4-24Figure 4-17 Diluted Bitumen Mass Balance for Ness Rock .................................................. 4-25Figure 4-18 Wind Speed and Direction for Butterworth Rocks ............................................ 4-26Figure 4-19 Syncrude Synthetic Light Oil Mass Balance for Butterworth Rocks ................ 4-28

Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning Technical Data Report Abbreviations

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Abbreviations

1/r2 .................................................................................................. inverse distance squared ADCP ............................................................................... acoustic Doppler current profiler ASL ................................................................................ ASL Environmental Services Ltd. CCAA .............................................................................. confined channel assessment area CHD .............................................. Queen Charlotte Sound–Hecate Strait–Dixon Entrance CM ................................................................................................................... current meter cm/s .................................................................................................... centimetre per second CRW* .................................................................................................................. condensate CTD ............................................................ conductivity and temperature at various depths H3D ....................................................................... three-dimensional hydrodynamic model Hay & Co ............................................................................... Hay & Company Consultants M2 .................................................................... principal lunar semidiurnal tidal constituent m/s ............................................................................................................ metres per second MKH* ........................................... MacKay River heavy bitumen diluted with synthetic oil MSC ............................................................................... Meteorological Service of Canada QRA ......................................................................................... quantitative risk assessment SLO ........................................................................................................... synthetic light oil SL Ross ........................................................................... SL Ross Environmental Research SOR ............................................................................................ successive over-relaxation SYN* ......................................................................................... Syncrude synthetic light oil VLCC .............................................................................................. very large crude carrier Z0 ............................................................................................................................ the mean

Note: *acronym appears only in Appendix C

Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning Technical Data Report Section 1: Introduction

2011 Page 1-1

1 Introduction This report provides the technical background for modelling used to estimate hydrocarbon mass balances (i.e., the distribution of hydrocarbons in the air, water column, sediment, and on shore) in the event of accidental spills at the Kitimat Terminal, in the confined channel assessment area (CCAA), and in the open water area that is between the CCAA and the Territorial Sea of Canada.

Also, this technical data report (TDR) examines the effects of winds and currents on spilled diluted oil and condensate in the marine environment to better understand how these hydrocarbons might behave under different oceanographic and meteorological conditions. This supports emergency response planning and spill response activities by providing predictions on where the oil is expected to go and providing recommendations on the most effective spill response actions.

Spill locations for this modelling study (see Figure 1-1) were selected based on the quantitative risk assessment (QRA)1

There were seven simulated spills at six locations:

results (DNV 2010). The oil spill simulations make use of surface currents from a three-dimensional circulation model and oil weathering properties for each of the three representative hydrocarbons (diluted bitumen, synthetic light oil and condensate). Weathering properties for these hydrocarbons were provided by SL Ross Environmental Research (SL Ross 2010a, 2010b). Spills were assumed to occur in each of the four seasons (using sea and weather data from 2004).

• Kitimat Terminal: 250 m3 spill of diluted bitumen; 250 m3 spill of condensate • Emilia Island: 10,000 m3

spill of synthetic light oil • Principe Channel: 10,000 m3

spill of diluted bitumen • Wright Sound: 36,000 m3 spill of diluted bitumen • Ness Rock in Caamaño Sound: 10,000 m3

spill of diluted bitumen • Butterworth Rocks in North Hecate Strait: 10,000 m3

spill of synthetic light oil

Mass balances were determined for each spill example (see Section 4.2).

Hydrocarbon Terminology

The following hydrocarbons are referred to in the modelling results reported in this TDR:

• Syncrude synthetic light oil (SYN)

• CRW condensate (CRW)

• MacKay River heavy bitumen diluted with Suncor synthetic light oil (MKH)

This is the same range of products that were examined in the Application, Volumes 7C and 8C. Throughout this report, SYN may also be referred to as synthetic oil light (SOL), MKH may be referred to as diluted bitumen, and CRW condensate is typically referred to as condensate.

1 The QRA is a statistical analysis of both the potential risk of a hydrocarbon spill and the associated uncertainty of that probability estimate. It accounts for operating conditions, navigational hazards, global incident frequencies, and mitigation measures taken to reduce potential risk and consequences of spills.

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REFERENCES: NTDB Topographic Mapsheets provided by the Majesty the Queen in Right of Canada, Department of Natural Resources. All rights reserved.

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Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning Technical Data Report Section 2: Description and Application of Numerical Models

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2 Description and Application of Numerical Models

The following models were used to determine mass balances for hypothetical accidental spills:

• hydrodynamic model • kinematic wind model • oil spill model • hydrocarbon weathering model

A flow chart of the modelling process is shown in Figure 2-1.

Figure 2-1 Model Process Flowchart

2.1 Hydrodynamic Model To provide quantitative information on the behaviour of oil, it is necessary to examine the various oceanographic processes (e.g., tides, winds, river flow) that influence surface currents, and thus the fate of spilled hydrocarbons in the region. A general description of the oceanography of the CCAA portion of the modelled area can be found in the Marine Physical Environment Technical Data Reports (ASL 2010a, 2010b). Surface currents in Douglas Channel and adjacent waters were calculated using Hay & Company Consultants’ (Hay & Co’s) proprietary three-dimensional hydrodynamic model, H3D.

The H3D model is derived from GF8 (Stronach et al. 1993a) developed for Fisheries and Oceans Canada. An extensive application of an operational version of this model to the St. Lawrence Estuary is described in Saucier and Chasseé (2000). H3D is a three-dimensional, time-stepping numerical model that computes the three components of velocity (u, v and w) on a regular grid in three dimensions (x, y and z), as well as scalar fields such as temperature and salinity. A time-stepping numerical model is one in which the period

Hydrodynamic Model

Wind Model

Oil Spill Model

Weathering Model

Stochastic Simulations

Specific Spill Examples

Mass Balances


Page 2-2 2011

of interest, e.g., a month-long simulation of currents in Douglas Channel, is broken up into a number of small time intervals, e.g., 100 seconds each. The model then takes advantage of the fact that over a short time interval, known as a time-step, changes in currents, salinities, and other properties are small, and can be computed in a rather simple fashion, suitable for coding in a numerical model.

H3D is a semi-implicit model, using the numerical scheme described in Backhaus (1983), and the staggered Arakawa C-grid (Arakawa and Lamb 1977). It uses only two time levels, and computes internal and external modes using the same time-stepping structure. To allow for better simulation of features such as river plumes in conjunction with large tidal excursions, the number of vertical layers representing the water column is allowed to increase and decrease as water levels rise and fall: new layers are successively turned on as the water level rises, and are then allowed to drain as the water level falls. This feature allows plumes that have vertical dimensions of 1 to 2 m to be resolved in the presence of tidal ranges of 5 m or more, an important consideration given the large tidal ranges characteristic of the Douglas Channel region. This layer schematization has been shown to work well for simulations of the Fraser River as it enters the Strait of Georgia (Stronach et al. 2006).

Two separate H3D implementations were used to conduct this study. A 3-km resolution Regional Model of the Queen Charlotte Sound–Hecate Strait–Dixon Entrance (CHD) system (Figure 2-2) provided boundary conditions for a nested 400-m grid Local Model of the Hecate Strait–Douglas Channel system (Figure 2-3). The following discussion provides characteristics common to both models.

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The model grid may be visualized as a number of interconnected computational cells collectively representing the water body. Figure 2-4 shows a schematic of a typical grid. For the simulations reported here, the boundary between the vertical layers of the grid occurs at depths, relative to mean sea level, of -3, -2, -1, 0, 1, 2, 3, 4, 6, 8, 10, 15, 20, 50, 100, 200, 500, 1000, 2000 and 4000 m. The negative depths represent water levels above mean sea level and are included so that the near-surface part of the water column can be resolved at 1-m intervals as the tide rises and falls. Velocities are determined on the faces of each cell and non-vector variables, such as temperature or salinity, are situated in the centre of each cell. All cells have identical x and y dimensions. The selection of grid size is based on consideration of the scale of the phenomena of interest, the grid domain and available computational resources. In the vertical, the cells are usually configured such that they are relatively thin near the surface and increase in thickness at depth. The increased vertical resolution near the surface is needed because much of the variability (stratification, wind mixing, inputs from streams and land drainage) is concentrated near the surface.

The principal driving force is water level fluctuations, primarily tidal, derived from water level variations at the open boundaries of the model grids. Tidal fluctuations are computed from tidal constituents for the open boundaries of the 3-km model, and are provided from the 3-km grid model to the 400-m grid model as a time series.

Wind forcing causes both currents and water level differences. Consideration of wind forcing is also important because wind energy has a notable effect on vertical mixing, and therefore, distributions of salinity and temperature. For the Regional Model, wind stresses acting at the water surface are derived from wind records collected from coastal Meteorological Service of Canada (MSC) stations and moored buoys. The raw data are processed into hourly time-series of over-water winds at the observation points. The Regional Model then interpolates these wind fields in space and time to meet model requirements. For the Local Model, the observed winds were first interpolated in a volume-conserving sense onto an alternate 400-m grid model that resolved topographic features such as the valleys in which most of the waterways are situated. This modelling procedure, referred to as the kinematic model, is discussed in more detail in Section 2.1.3. The kinematic model is necessary so that the wind field would be steered adequately by the topography of the mountain valleys where most of the waterways are situated.

H3D incorporates inflows from rivers and creeks. These inflows contribute mass and momentum to the water body, and consequently have a substantial influence on surface currents. The boundary condition for river flow is represented by a time-varying flow rate. Where available, the flow rate is generated from daily or hourly hydrographs of the particular river under consideration. Monthly mean river flows were used for the simulations reported because most of the freshwater sources are ungauged and detailed flow data are unavailable.

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Besides winds, other meteorological data are needed to compute heat flux into the water. In most applications, data are limited for calculating heat flux across the water surface. Reasonable estimates can be made from wind speed, wet bulb and dry bulb air temperatures and cloud cover or insolation. In summer, heat input leads to increased temperature stratification within the water column. In winter, when salinity stratification is often minimal, cooling can lead to static instabilities and overturning in the upper part of the water column. Because the model is run over all seasons, the ability to simulate winter cooling is important. To treat winter cooling effectively, H3D includes a convective overturning mechanism, so that if the water in a surface cell cools to the point that it is denser than the water in the cell beneath it, H3D will vertically mix the water in these two cells, thus propagating the cooling water downward. H3D’s ability to simulate both summer heating and winter cooling can be seen best in simulations done for freshwater lakes, where temperature is the only scalar value affecting density (Zaremba et al. 2005).

Turbulence modelling is important in determining the correct distribution of velocity and other water properties such as temperature and salinity. The diffusion coefficients for momentum, temperature and salinity at each computational cell depend on the level of turbulence at that point. H3D uses a shear-dependent turbulence formulation in the horizontal direction (Smagorinsky 1963) and a shear- and stratification-dependent formulation in the vertical dimension for momentum. This procedure is referred to as the Mellor-Yamada Level 2 scheme (Mellor and Yamada 1982), a local boundary layer simplification of the full turbulence closure model. These parameters have been shown to work well when simulating the annual cycle of salinity and temperature in the Strait of Georgia (Stronach et al. 2006) and also allowed a good calibration of both the Regional and Local models against observed data. For scalar values, such as salinity, constant horizontal eddy diffusivity is used, and the vertical diffusivity is similar to the vertical eddy viscosity, but scaled by a fixed ratio of 0.1, a value found to work well for British Columbia coastal waters.

The hydrodynamic model operates in a time-stepping mode over the period of simulation. The time-step length is variable, depending on the maximum velocity present in the model at that particular time-step. During each time-step, values of velocity, temperature and salinity are updated in each cell. Typically, data were archived (saved to disk) hourly or daily, so that a manageable amount of data were generated for subsequent analysis. The model is initialized with salinity and temperature fields obtained by interpolating observations archived at the Institute of Ocean Sciences, and provided for use in this study by the Ocean Productivity Group, Institute of Ocean Sciences, Sidney, British Columbia (Fisheries and Oceans Canada 2010). An initial condition of zero velocity is chosen, and the water level is initially set to mean sea level. The model is run in prognostic mode from this initial state, with the tide and wind being ramped up over one day. The first 15 days of the run are discarded, as they are deemed to be contaminated by start-up transients.

As mentioned above, H3D is implemented in a nested configuration. The coarse grid (Regional) and fine grid (Local) models were run separately. One-way communication from the 3-km grid Regional Model to the 400-m grid Local Model is implemented using binary direct access files. Thus the coarse grid Regional Model provided the necessary hydrodynamic boundary conditions to the fine grid Local Model.


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2.1.1 Regional Model

2.1.1.1 Model Domain

The domain of the Regional Model grid (Figure 2-2) extends from the north quarter of Vancouver Island northward up the British Columbia coast to Prince of Wales Island in Alaska, and from the waters 70 km off the west coast of Haida Gwaii2

2.1.1.2 Input and Forcing Data

eastward to Douglas Channel and Kitimat. The grid is rotated 30 degrees counter-clockwise, and is composed of 145 by 270 grid cells. It is referred to as a 3-km grid model, although the grid cell size is 2.7 km. Water depth is defined for each grid cell from available bathymetric charts and data sets. This model has a similar domain to that of Cummins and Oey (1997), although it does not extend as far offshore. However, the resolution is approximately twice that of their model (2.7 km versus 5 km). This increased resolution should allow better reproduction of oceanographic phenomena in the area, and in particular, should interface well with the Local Model.

Wind forcing for this model is interpolated from an array of MSC stations, including Bonilla Island, North and South Hecate, Holland Rock, Nanakwa Shoal and Sandspit. Figure 2-5 shows the locations of observation sites available for simulating the wind conditions in 2004.

Tidal variations in water level along the open boundaries of the model are specified using harmonic constants derived from a global ocean database (Schrama and Ray 1994). The GOT00.2 ocean tide model is the latest solution in a series beginning with Schrama and Ray (1994). Its immediate predecessor (GOT99.2) is described in Ray (1999). The database consists of independent near-global estimates of seven tidal constituents (Q1, O1, K1, N2, M2, S2 and K2, with P1 inferred). These constituents were extracted from the database and used to compute the time-varying water level along the open boundaries.

Meteorological data for computing heat input was obtained from the Sandspit airport station. Because some years did not have full coverage, in particular the year selected for the oil spill simulations, the year 1994 is used for all simulations. Thus, the details of the thermal forcing will be somewhat inaccurate for years other than 1994, because a single point is used to describe the heat input over the entire region, and because the year being used for heat flux calculations is not the same as the year used for wind data. However, the adopted procedure will ensure that the model temperatures track relatively closely to the actual seasonal variations. Incorporating data such as air temperature from the network of wave observing buoys in the model would likely improve the simulations, and it is recommended that future work consider these data.

For freshwater input, 18 named river inflows, including the Nass, Skeena, Kitimat, Kitlope, Kemano, Kildala, Bella Coola and Dean rivers and Orchard Creek were tabulated by mean monthly flows. Ungauged rivers were added to the model and their flows were estimated on a drainage basin basis. Table A-1 provides a list of inflows and their historic monthly mean flow values and Figure 2-6 shows the locations of these rivers.

2 The name of Queen Charlotte Islands was changed to Haida Gwaii in December 2009. However, for consistency with source information used for mapping, Queen Charlotte Islands is used on all maps.



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S. Hecate

W. Sea Otter

E. Dellwood

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Cathedral Point

Cumshewa

Herbert Island

Holland Rock

Kindakun Rock

Langara

Grey IsletLucy Island

Mid Nomad

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Nanakwa ShoalN. Nomad

Prince Rupert

Rose Spit

S. Brooks

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Freshwater Inflow Sites:

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Nass River

Skeena River

Kitimat River

Kitlope River

Kowesas RiverKiltuish R.

Triumph R.Collins Bay

Brim R.Kemano River

Foch & Gilttoyees InletsKildala River

Klekane Inlet Aaltanhash Inlet

Green Inlet

Surf InletKhutze Inlet

Bella Coola River

Dean River

Orchard Creek

Klahini River & Unuk River

Salmon River & Bear River

Observatory InletDavis River

Naden Harbour

Masset Inlet

Cumshewa Inlet

Selwyn Inlet

Lyell Island

Unnamed QC1

Unnamed QC2 Unnamed QC3

Unnamed QC4

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Unnamed QC6Unnamed QC7

Unnamed A

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Kunghit Island South Bentinck Arm

Smith Inlet

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Kingcome Inlet

Knight Inlet

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Boundary and initial conditions for temperature and salinity were generated from historical conductivity, temperature and depth (CTD) data supplied by the Ocean Productivity Group (Fisheries and Oceans Canada 2010). The full set of CTD profiles in the region is grouped by month, and a three-dimensional salinity and temperature field is interpolated over the model domain for each month. For both the Regional and Local models, a spin-up time of 15 days is assumed (i.e., the first 15 days of all runs are discarded) and the model simulation data are assumed to be valid starting on the 16th day of the simulation. This spin-up time is selected based on a visual examination of the distribution of surface salinities. It is chosen so that the effects of inaccurate initial conditions would have minimal effect on river plumes and associated surface currents. Currents at depth would likely require considerably longer spin-up times, possibly up to a year.

2.1.2 Local Model

2.1.2.1 Model Domain

The domain of the 400-m grid Local Model extends from Aristazabal Island in the south to Porcher Island in the north, and from Kitimat and Kemano Bay to beyond Banks and Bonilla Islands (see Figure 2-3). The grid is rotated 30 degrees counter-clockwise, similar to the 3-km Regional Model. It is composed of 400 by 420 grid cells, each 400 m in size. Water depth is defined for each grid cell from available bathymetric charts and data sets.

2.1.2.2 Input and Forcing Data

Wind forcing for the Local Model is taken from the kinematic wind model, described in Section 2.1.3. Water levels, currents, temperatures and salinities at the open boundaries are prescribed from the 3-km Regional Model on inflow, and are extrapolated from the interior on outflow. Data from the Regional Model were archived at three-minute intervals to provide continuously varying boundary conditions. Meteorological forcing, other than winds, is treated the same way as in the Regional Model; data from Sandspit airport for 1994 were used, based on Julian day.

Freshwater input from rivers is provided and tabulated by monthly mean flow rate. Some of the inflows were from ungauged catchments and their flows were estimated on a drainage basin basis. Table A-2 provides information on all these rivers, mean annual flow rates and historical monthly flow rates. Figure 2-7 shows the map of the river inflows for the Local Model.

The initial salinity and temperature fields were constructed by interpolating data from the Ocean Productivity Group (Fisheries and Oceans Canada 2010). The full set of CTD profiles in the region is grouped by month. A salinity and temperature field is interpolated over the model domain for each month.

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2.1.3 Kinematic Wind Model The existing network of weather buoys and shore stations provides adequate spatial resolution of the wind field over most of the Regional Model grid. As an example, Figure 2-8 shows the active wind stations for the Regional Model for 2004, the calendar year for which the spill scenarios were executed, as well as a typical interpolated wind field, using an inverse distance squared (1/r2) weighting.

To provide an adequate wind field for the 400-m grid Local Model, there is the difficulty that topographic influences and the relative sparseness of observation sites could be expected to render the simple spatial resolution scheme used for the Regional Model invalid. For example, a wind blowing down-channel in Kitimat Arm would be directed from the northwest. Because there are no wind stations in the lower part of Douglas Channel, if a simple interpolation scheme were to be used, this northwest wind direction would persist all the way down Douglas Channel, which is oriented north-south in its lower reaches. An interpolated northwest wind would lead to oil being preferentially driven to the westward shore of Douglas Channel, an unrealistic outcome.

The solution to the problems induced by the complex topography involved constructing a two-dimensional volume-conserving interpolation scheme, referred to as the kinematic wind model. The topography of the region was downloaded from a Natural Resources Canada website (Natural Resources Canada 2004, Internet site) and interpolated onto a 400-m non-rotated grid. Elevations below 200 m are assigned a value of zero, and elevations above 200 m are assigned a very large value, so that the result is an interconnected network of channels of uniform depth, bounded by high cliffs. This schematization of the topography is somewhat simplistic but gave good results and executed relatively rapidly.

Once a grid for the wind model was developed, the volume-conserving scheme is implemented. The following discussion describes the process for a single hour; this process is then repeated for each hour needed for the simulation. First, the available data are interpolated using the same 1/r2 method used for the Regional Model and, second, wind values normal to the channel walls are set to zero, meeting the condition of zero flow through solid boundaries. The resulting wind field is still unrealistic, and does not conserve volume. Figure 2-9 shows an example of this first interpolation wind field, as well as the observed wind stations available for the 2004 simulations. The modelled wind vectors shown in this plot are sub-sampled to every sixth vector in the X and Y directions. An indication of the type of errors generated by the interpolation procedure can be seen in the upper part of Douglas Channel, near Nanakwa Shoal, where the wind velocity has a substantial component of its motion directed toward the shore, rather than along the channel. To address this type of problem, a hypothetical pressure field is conceived such that its gradient, when applied to the interpolated wind field, gives a velocity field that satisfies volume conservation as well as no flow through solid boundaries. When this pressure gradient is applied formally in the volume conservation equation, the result is a Helmholtz equation for the pressure field, with the divergence of the initial field being the source term. The solution for the pressure field is obtained by a successive over-relaxation (SOR) technique Figure 2-10 shows the resulting interpolated field. The maximum divergence in the initial field was initially 0.027/s, and was reduced to 0.0016/s by the addition of the pressure gradient. The resulting volume-conserving wind field was subsampled from the 400-m (non-rotated) grid on a 6 by 6 basis, and provided to the Local Model, where it was used in a 1/r2 interpolation scheme.



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Additional data to drive the interpolation process for simulation dates became available after January 6, 2006, when installation of six meteorological stations was completed as part of this study. Stations were installed in Douglas Channel, Squally Channel and Caamaño Sound. Their effect on the interpolation process is discussed in a separate TDR on wind observations and wind modelling (Hay & Co 2010).

2.2 Oil Spill Model Hay & Co has developed an oil spill model which functions as an add-on component to H3D. The model uses a Monte Carlo technique to simulate the dispersion of the oil by oceanographic processes. Spilled oil floating on the water surface is represented as a large number of independent floating particles, referred to as slicklets. The cloud of particles as a whole represents the area covered by the oil slick, and its progress is the slick’s dispersion and trajectory over the water surface.

Three key components drive the movement of oil particles:

• advection, based on surface currents from H3D • wind action, using winds from the kinematic wind model • eddy diffusion, simulated as a random velocity component

These three components and other aspects of the oil spill model are described in detail in Appendix A.

Two modes of operation were implemented for the oil spill model: stochastic and specific. Stochastic simulations were run to derive the most likely spill pathway for spills originating at each of the example spill locations. Specific simulations were used to determine mass balances of spilled hydrocarbons for each of the example spills in Section 4 and Appendix C.

When oil is spilled it is transported by the currents and winds occurring over the duration of the incident. Because these conditions vary over the course of a day, a month or a season, any single spill from the same location is likely to follow a different path. Running an oil spill model in stochastic mode allows one to simulate hundreds or thousands of individual spills originating at the same site but at different times of the day or year. By running many individual spill simulations with a different time of release it is possible to determine the probability that oil will pass through a section of the water surface or intersect a section of the shoreline for spills occurring at different times of year or under specific environmental conditions.

When mapped, the results from the stochastic simulations show the areas that could be affected by oil, and the spatial distribution of the probability of being oiled, for any spill that occurs at the specified location and during the specified season. In the stochastic simulations, a statistical description was developed by assuming hypothetical, independent spills could occur at any time during a particular month. Each individual spill is tracked separately for 15 days. The resulting spill simulations were analyzed to obtain the probability of oil contacting either the shoreline (resolved into 100 m increments), or the water surface (resolved into 400-m square grids). For those shoreline or water segments where contact occurred, the maximum thickness of oil and the minimum time for the contact to occur after the spill began were determined. The stochastic model is run for four seasons, four spill locations and three hydrocarbons, for a total of 48 stochastic runs. Any individual spill occurring at any of the four sites will fall within the probability footprint of the stochastic model results for that spill site.


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To obtain an appreciation of the characteristics of an actual spill, an additional 48 specific spill scenarios were generated, for the same four locations, three oil products and four seasons. This is accomplished by selecting a single spill from the stochastic model output that is most representative of the overall stochastic result at the release site. Each individual spill simulation is continued until no oil is left on the water, or for 15 days, whichever occurred first. The results from these spills were used to calculate the hydrocarbon mass balance time series.

2.2.1 Input and Forcing Data Oil particles in the oil spill model are moved by the combined forces of currents developed in the H3D hydrodynamic model and winds developed in the kinematic wind model. Currents at the water surface are taken from the top layer of the Local Model, which are saved at 15-minute intervals. For each particle, the H3D currents are spatially interpolated from the four surrounding grid points, as described in Bennett and Clites (1987). The wind field, determined by the kinematic wind model, is identical to the wind field used by H3D. As in H3D, the hourly wind field is temporally interpolated at each time-step.

Oil interactions with the shoreline area are accomplished by incorporating a coastline geometry data set with a 100 m resolution into the oil spill model. This high-resolution geometry is part of a coastline database that describes shoreline types necessary to determine oil retention. Table 2-1 summarizes the repetitive shore types contained in the database, and also lists the oil retention ascribed to each of the shore types. The shore retention for various shore types is based on data from Gundlach (1987). Table 2-1 also lists the coastal class, a more extensive classification scheme, associated with each repetitive shore type. The definition of coastal classes and repetitive shore type is taken from the British Columbia Government Provincial Corporate Shoreline Information website (RISC 1997, Internet site).

Table 2-1 Shore Types and Oil Retention Repetitive

Type

Description

Coastal Class

Gundlach Classification

Oil Retention

(m3/m) 2 Rock Platform 2, 5 Steep Rock 0.01 3 Rock Cliff 1, 3, 4 Steep Rock 0.01 4 Rock with Gravel Beach 6-10 Gravel/Cobble 0.6 5 Rock, Sand and Gravel Beach 11 to 15 Gravel/Cobble 0.6 6 Rock with Sand Beach 16 to 20 Sand Beach 2.0 7 Gravel Beach 22 Gravel/Cobble 0.6 8 Gravel Flat 21, 23 Gravel/Cobble 0.6 9 Sand and Gravel Beach 25 Sand Beach 2.0 10 Sand Beach 27, 30 Sand Beach 2.0


2011 Page 2-19

Table 2-1 Shore Types and Oil Retention (cont’d) Repetitive

Type

Description

Coastal Class

Gundlach Classification

Oil Retention

(m3/m) 11 Sand and Gravel Flat 24, 26 Sand Beach 2.0 12 Sand Flat 28 Tidal Flat 0.12 13 Mud Flat 29 Tidal Flat 0.12 14 Estuary, marsh or Lagoon 31, 35 Marsh 0.3 15 Channel 34 Steep Rock 0.01 16 Man Made 32, 33 Steep Rock 0.01

This scheme does not include reference to the wave energy at the site, which has implications for the actual oil retention. Such information is contained in the Oil Residency Index, which provides semi-quantitative information on the residence time for oil remaining on the shore. Subsequent analyses of oil spill behaviour should consider this index as well. This index is also part of the British Columbia Government Provincial Corporate Shoreline Information (RISC 1997, Internet site). The interaction of oil with the shoreline is a complicated process; however, this model assumes simply that the shore retains oil upon contact, unless the shore’s capacity to retain oil is exceeded.

2.2.2 Hydrocarbon Weathering Model As the oil moves on the water surface and intersects the shoreline it undergoes weathering and degradation processes. The SL Ross weathering model is used to calculate hydrocarbon weathering for the spills simulated. The weathering model predicts evaporation, emulsion, dispersion, spreading and other property changes of spilled oil (SL Ross 2010a, 2010b; Belore 2006, pers. comm.). Inputs needed for the SL Ross model include the physical and chemical properties of the oil, obtained by testing samples, and the environmental conditions, provided by Hay & Co. For each simulation, Hay & Co sent SL Ross a time series of location, wind speed, air temperature and water temperature, extracted at 15-minute intervals from H3D at the position of the slick. In return, SL Ross provided the corresponding time series of parameters describing the oil’s weathering. No distinction is made between landed and floating oil in the SL Ross weathering model.

The weathering model assumed the wave action that would cause dispersion into the water column is directly related to the wind speed, and implicitly assumed an infinite fetch/infinite duration wave generation condition. In the narrow waters of Douglas Channel, fetch is limited by proximity to the upstream shoreline, and also by the narrow width of most of the channels. Thus, a modified wind, to be used for calculating dispersion into the water column, was also supplied to SL Ross. It is adjusted so that it would achieve, for an unlimited fetch case, the same wave field as would occur in the fetch-limited Douglas Channel, using the wind field determined for the simulation of currents and oil advection.

To generate a mass balance plot for each simulation, the outputs from the SL Ross and Hay & Co models were integrated. The volumes of oil dispersed and evaporated were taken directly from the SL Ross output. Of the remaining volume, the percentages on land and on water were taken from the Hay & Co oil spill model.

Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning Technical Data Report Section 3: Model Validation

2011 Page 3-1

3 Model Validation

3.1 Hydrodynamic Model The purpose of the hydrodynamic model is to provide information on surface currents. This information is then input to the oil spill model to help determine the fate of liquid hydrocarbons in the event of a spill to the marine environment. The following section provides a comparison of modelled and observed parameters, which assess the reliability of the hydrodynamic model in understanding how spilled oil would behave in the modelled areas near the example simulated-spill locations.

3.1.1 Validation of the Regional Model

Tides

Tides are measured at numerous stations along the coast. Because H3D also predicts the tidal variations in water level, these predictions can be compared with observations. Such a comparison serves as a check on the adequacy of the tidal boundary conditions, and of the adequacy of the grid with respect to resolving the important bathymetric features of the region. As an example of the model’s accuracy, the amplitude and phase of the M2 tidal component was determined at 10 coastal stations. These have been plotted in Figure 3-1, which also contains a co-amplitude co-phase plot of the M2 tide from the 3-km H3D model. Table 3-1 summarizes the comparison of observed and predicted tides at these ten stations.

Table 3-1 Comparison of Harmonic Constants for Observed and Modelled Water Levels: M2

Location

Observed Modelled Difference A

(cm) g (°)

A (cm)

g (°)

A (cm)

g (°)

Black Islands 155.1 26 162 25.3 6.9 -0.7 Langara Island 130.6 30.9 124.3 28.9 -6.3 -2 Queen Charlotte City 197.4 39.6 192.4 39.6 -5 0 Cape St. James 104.8 32 103.5 27.1 -1.3 -4.9 Cape Scott 108 12.3 111.4 9.7 3.4 -2.6 Griffith Harbour 181.6 30 184.6 28.2 3 -1.8 Claxton 194.2 38.5 197.5 32.2 3.3 -6.3 Smithers Island 141.2 23.6 148.2 21.2 7 -2.4 Prince Rupert 194.3 35.5 197.0 34.5 2.7 -1.0 Kitimat 165.0 25.9 177.8 24.6 12.8 -1.3 NOTES: A – amplitude g – phase



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The agreement is acceptable, but could be made better by further adjustments to the bathymetry, and possibly by the inclusion of more constituents. However, the agreement is adequate to allow the Local Model to be run. Even though there is general agreement in the data, it would be desirable to calibrate the tidal characteristics of the Regional Model to improve the tidal boundary conditions provided to the Local Model.

Sea Surface Temperature

Figure 3-2 shows a satellite image of ocean surface temperature around Haida Gwaii, from 06:00, July 24, 1994 (Cretney et al. 2002). Sea surface temperature as computed by H3D is shown in Figure 3-3 for comparison. The 3-km H3D model was initialized on July 1, 1994, from historical temperature and salinity data held by the Ocean Productivity Group (Fisheries and Oceans Canada 2010), and the temperature in the top metre of water was extracted at 06:00, July 24, 1994, to match the time of satellite image.

The model reproduces large-scale features observed in the satellite image, including:

• colder water along the western coast of Haida Gwaii • warmer water along the eastern coast of Haida Gwaii • colder water at the coast of Banks Island • a cool eddy to the south of Cape St. James • a cool eddy off the tip of Rose Spit • a broad eddy to the northwest of Cape St. James

The model inputs were: initial temperature and salinity conditions from interpolated CTD data; 46 river inflows; eight tidal components specified along the boundary; winds from 33 stations; and meteorological data from the Sandspit station. Air temperatures from Sandspit were reduced by 2°C, to reflect the likely cooler air found over the water surface, compared with the over-land temperature at Sandspit airport. Subsequent modelling should make use of the air temperature sensors on the meteorological buoys in CHD.

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Currents

Current meters were moored in the Haida Gwaii region for periods of two to eight months between 1982 and 1995 (Cretney et al. 2002), recording current velocities every 15 or 30 minutes at fixed locations. The 3-km H3D model was set up to run for July and August 1990, and the modelled currents were extracted for comparison with the current meter measurements. Figure 3-4 shows time-series of current velocities at a location near Cape St. James, comparing modelled and observed currents. The time-series shows good agreement between observed and modelled currents with respect to phase, but H3D over-predicts velocities. At other locations, H3D currents tend to be slower than the observed, but on average, the agreement is sufficient to allow the Local Model to be run. The agreement could be improved through various adjustments to the model, but will always be limited by the availability of boundary data along the open sea boundaries.

Drifters

In July and August 1990, as well as in other years, over 60 drifters were released in South Hecate Strait, each equipped with a Loran-C positioning system. The drifters recorded their positions every 30 minutes. Surface current velocities were computed from these data, and compared against surface currents predicted by H3D in the same locations. Figure 3-5 presents a comparison of drifter velocity against modelled surface currents for one of the drifters, C90.i36. H3D surface velocity compares very well with this drifter, as shown in Figure 3-5 but not all comparisons are as good.

3.1.2 Validation of the Local Model

Tides

Figure 3-6 shows a co-amplitude co-phase plot of the M2 tidal component as computed by the 400-m grid Local Model, and Table 3-2 provides comparison of the model with tide gauge data.

Table 3-2 Comparison of Observed and Modelled Harmonic Constants: M2

Location

Observed Modelled Difference A

(cm) g (°)

A (cm)

g (°)

A (cm)

g (°)

Black Islands 155.1 26.0 167.8 29.8 12.7 3.8 Kemano Bay 172.5 26.6 199.5 32.4 27.0 5.8 Kitkatla Islands 188.0 32.0 199.6 33.7 11.6 1.7 Hartley Bay 158.8 23.0 173.7 29.2 14.9 6.2 Smithers Island 141.2 23.6 153.4 25.1 12.1 1.5 Larsen Island 176.4 29.0 192.4 33.2 16.0 4.2 McKenney Island 137.8 23.2 147.5 25.7 9.7 2.5 Kitimat 165.0 25.9 185.2 30.8 20.2 4.9 NOTES: A – amplitude g – phase

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The patterns compare well with published co-tidal charts (Godin 1980) in a qualitative sense. However, the model over-predicts amplitudes by a fairly large amount, likely attributable to errors in the grid schematization and bathymetry, and to a smaller extent to errors in water level boundary condition data from the Regional Model.

3.1.3 Validation against ASL Observations in 2005 As part of the Northern Gateway study, ASL Environmental Services Ltd. (ASL) installed moored acoustic Doppler current profiler (ADCP) current meters at four locations, shown in Figure 3-7 for the period from September 15, 2005, to January 5, 2006. Data were recovered from three of these moorings: Site 1 near the Kitimat Terminal; Site 2 in Douglas Channel, and Site 4 in Caamaño Sound. Velocity data from these moorings served as the basis for validating the Local Model. However, the wind data from the Kitimat Eurocan Pulp and Paper Co. site were only available up to November 2, 2005. Thus, the validation period extends from September 15 to November 2, 2005. When the complete Kitimat Eurocan wind data become available, the validation could be extended to the end of December 2005.

Temperature and Salinity

Temperature and salinity profiles were measured during deployment and recovery of the current meters. Currently, comparisons with equivalent model profiles can be made for the deployment period only. These are shown in Figure 3-8 for the three sites. At the Kitimat Terminal, Site 1, modelled and observed salinity agree well at depth, but the agreement near the surface is not as good. Specifically, the model has higher salinities in the top 10 m, and shows less stratification and more vertical mixing in the top 10 m. Also plotted is a profile from the Dobrocky report (Webster 1980), showing the water column structure on October 11, 1977. This profile agrees better with the model, although distinct from the ASL profile; it shows more vertical mixing than the model. These discrepancies are counterintuitive in that the actual river flow during the time of the ASL profiles and for two weeks preceding is lower than the monthly averages used in the H3D simulation. It is also apparent from comparing these profiles that the model resolution should have been better in the depth range between 10 and 20 m.

At Site 2, the bottom values also agree well, but the surface values do not agree as well. Model vertical mixing appears to be too small, so that a relatively strong pycnocline (a layer, zone, or gradient of changing density, especially a thin layer of ocean water with a density that increases rapidly with depth) develops at about 15 m depth.

At Site 4, a similar level of agreement continues, and there is still stratification from freshwater at this relatively shallow and exposed site, despite the intense wind mixing that occurs here.



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Currents

A validation against currents at the three sites is presented in terms of stick plots and comparisons of harmonic constants from model and observed data. Figures 3-9 to 3-14 show stick plots for both modelled and observed data at Sites 1, 2, and 4. Model results are only available for the period September 15 to November 3, 2005 due to available data from the Kitimat Eurocan meteorological station.

Modelled currents at Site 1, near the Kitimat Terminal, reproduce some features in the observed currents, but miss others, as shown in Figures 3-9 and 3-10. Both model and observations agree that currents at 9 m are relatively energetic, and that currents at 15 m are considerably weaker, and then increase in magnitude at greater depths. The difficulty with validations at the head of the inlet is that currents there have several forcing functions, such as the Kitimat River, that are spatially variable, but adequate spatial information is lacking. For example, the Kitimat River has a broad distributary delta, but which channels are the most active is not known. Another complicating factor is the counter-clockwise eddying structure found in Kitimat Arm as the flow from the Kitimat River is forced back upstream on a rising tide. This eddy also derives energy from the freshwater flow out of Kildala Arm, the strength of which is not known. Consequently, the model may be broadly correct in terms of reproducing the circulation at the top end of Kitimat Arm, but on a point by point basis, it is not ideal.

The situation improves considerably at Site 2 (Figures 3-11 and 3-12). Here the agreement is very good throughout the water column, except at a depth of 151 m, where model and observations are 180 degrees out of phase. That is, the internal tide at this depth has not been reproduced well. At Site 4 (Figures 3-13 and 3-14), currents are considerably more variable than at the other two sites, although not particularly large in magnitude. Generally, periods of stronger and weaker currents are similar between model and observed data.


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Figures 3-15 to 3-17 compare the modelled tidal harmonic constants with the observed data. Two constants have been chosen: the mean, Z0; and M2, the dominant lunar semi-diurnal tide. At Site 1, the modelled Z0 and M2 amplitudes are mirror images around the vertical axis: both are very large in the top 10 to 20 m and smaller and vertically uniform below that depth. The observed values are similar, but the observed Z0 reverses direction at approximately 15 m depth. However, the observed Z0 is very small, so its vertical variation may not be particularly significant. The phase of M2 shows a similar pattern in both model and observed data, its value decreasing with depth, but the phase difference between model and observed data at depths between 15 and 40 m is up to 40 degrees. For reference, the density profile is plotted in the rightmost panel, showing the close coupling between the vertical structure of the density and the vertical structure of the tidal constants, the signature of an internal tide.

Overall, modelled and observed data at Site 2 show good agreement, although the model fails to capture an upstream flow at depths between about 40 and 70 m. The M2 phase agreement is quite good.

At Site 4, the Z0 fields agree well, but the M2 phase and amplitude have some disagreement. The observed amplitude at 6 m depth is 25 cm/s, whereas only 4 m deeper at 10 m, the amplitude is 15 cm/s, and the phase has reversed by 180 degrees. The observed phase then reversed by 180 degrees at 19 m. These phase reversals do not appear to be supported by the density structure, so there are indications that currents here are extremely complex.

Currents are influenced by river inflows, winds, stratification and bathymetry. In principle, these are all present in the H3D modelling. However, there are discrepancies between the modelled and measured currents. The most likely reason for these discrepancies is that the temperature and salinity fields were likely not fully in balance at mid-depth, and needed a longer spin-up time. However, the general agreement at the shallow current meters is good, especially at Site 2. Also, because oil slick modelling includes a wind leeway factor, the impact of any errors in the modelled water velocities will be considerably reduced in the oil spill simulations.

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Comparison of Modelled and Observed Winds: January and July, 2004


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3.1.4 Validation of Kinematic Wind Model Assessing the accuracy of the wind model is difficult because of the limited amount of data with which to compare it. However, two important criteria are met:

• The flow field is steered very well by the topography; this is certainly the most common behaviour of winds in the valleys and fjords characterizing Douglas Channel and Caamaño Sound.

• The model reproduces winds at the input locations, as shown in Figure 3-18, comparing wind time-series generated by the model and as observed at MSC stations, for January and July, 2004, the year of the stochastic simulations.

3.2 Oil Spill Model The oil spill model is used to determine the fate of spilled oil and condensate at the specific example spill locations. The oil spill model used surface current data obtained from the hydrodynamic model (with inputs from the kinematic wind model) along with hydrocarbon weathering data to predict the behaviour and movement of hydrocarbons. Example spill locations and associated volumes were selected to represent spills where there could be environmental effects for a range of components of the marine and human environments.

3.2.1 Spill Examples

3.2.1.1 Kitimat Terminal

Two spill examples at the Kitimat Terminal were examined, one for the case of a spill of diluted bitumen and the other for a condensate spill, both in the summer, based on oceanographic and weather conditions representative for the season. The chemical and physical properties of bitumen and condensate were assumed to represent the range of properties of hydrocarbons proposed for transport at the terminal.

A hypothetical 250 m3 spill of diluted bitumen from a loading tanker is considered under inflow wind and current conditions during summer. A 250 m3 spill of condensate unloading at the terminal under inflow conditions during summer is also considered. Volumes were derived through the Quantitative Risk Assessment (QRA) process (DNV 2010) and provide a theoretical calculation of the maximum discharge because of a loading arm and containment boom failure during transfer operations, while loading (oil) or unloading (condensate) a tanker at the marine terminal.

3.2.1.2 Emilia Island

This location is chosen based on its proximity to sensitive environmental features (i.e., Foch-Gilttoyees Park and Protected Area; Stair Creek Conservancy). This example considered a 10,000 m3 spill of light synthetic light oil in Douglas Channel just south of Emilia Island, during February, as a result of vessel grounding. The release from the vessel is assumed to last 13 hours, with a higher percentage of the total spill released immediately, and slower release over the subsequent 12 hours (i.e., likely pathway of the synthetic crude without a boom in place). This spill example illustrates the unmitigated (i.e., no response actions) fate of the spilled synthetic light oil over three days.


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3.2.1.3 Principe Channel

This spill example simulates a 10,000 m3 spill of diluted bitumen midway along Principe Channel, off

Anger Island, in July, as a result of vessel grounding. It is assumed the bitumen is released over a period of 13 hours, with much of it released immediately and the remainder being slowly released over the next 12 hours. This segment of Principe Channel is a relatively narrow stretch ranging from 2- to 3-km wide, with chartered depths in excess of 100 m.

3.2.1.4 Wright Sound

This spill example concerns a 36,000 m3 spill of diluted bitumen in Wright Sound, midway between Promise Island and Gil Island, in July, as a result of a vessel collision. It is assumed that two compartments on a VLCC are ruptured, despite the double hull configuration, and that all the diluted bitumen in the two compartments eventually drains entirely. The spill pathway model assumes the diluted bitumen is released over a period of 13 hours, with most of it released immediately, and the rest more slowly over the next 12 hours.

3.2.1.5 Ness Rock in Caamaño Sound

This example simulates a spill of 10,000 m3 of diluted bitumen in Caamaño Sound in February as a result of a tanker grounding on Ness Rock. It is assumed the bitumen is spilled over a period of 13 hours, with approximately 20% being released within the first hour and the remainder being slowly released over the next 12 hours. Strong southeast winds predominate during the winter months in southern Hecate Strait. Modelled current speeds are 3 to 120 cm/s for the assumed conditions, and are dominated by wind forces.

Caamaño Sound is located in southern Hecate Strait, an area exposed to strong winter storms. During successive winter storms, high seas and swells, combined with strong crosswinds and currents, create difficult navigational conditions in Caamaño Sound. Caamaño Sound provides direct access to Queen Charlotte Sound and the open sea for vessels coming from Douglas Channel via Wright Sound, Lewis Passage, Squally Channel and Campania Sound. Caamaño Sound has a minimum width of 2.5 nautical miles.

3.2.1.6 Butterworth Rocks in North Hecate Strait

This example simulates 10,000 m3of synthetic light oil in north Hecate Strait in July, as a result of a tanker grounding at Butterworth Rocks. It is assumed the oil is spilled over a period of 13 hours, with approximately 20% being released within the first hour and the remainder being slowly released over the next 12 hours. The example is based on typical summer environmental conditions for north Hecate Strait and Butterworth Rocks is close to the Northern Approach. West of Butterworth Rocks, Hecate Strait is 5.5 km wide with charted depths of 36 to 100 m. Butterworth Rocks is approximately 9 km south of the pilot boarding area.

Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning Technical Data Report Section 4: Model Results

2011 Page 4-1

4 Model Results Hydrodynamic model predictions related to surface currents are presented in Section 4.1. These results were used as inputs to the oil spill model, which in turn are used to estimate the most likely spill pathway at each of the example locations. As described in Section 2.2, these example locations are used to estimate the mass balances of hydrocarbons among the different environmental compartments following a spill. These mass balance results are presented in Section 4.2.

4.1 Hydrodynamic Model The factors influencing surface currents are predominantly estuarine circulation (river plumes, eddies and a strong persistent seaward set to surface currents), winds, (barotropic) tides and internal tides. These factors are discussed in the following sections.

4.1.1 River Inflow Effects

4.1.1.1 River Plumes

In agreement with many of the studies of river plumes, there is a tendency for the river outflows to turn to the right (in the Northern Hemisphere) on exiting the individual rivers. Simulations for several rivers in the modelled area exhibit this classical river plume behaviour.

Freshwater discharges are tidally modulated; this is known to occur in other systems such as, for example, the Fraser River Plume (Giovando and Tabata 1970; Tabata 1972; Cordes 1977; Stronach 1977; Stronach 1981; Royer 1983), the Columbia River Plume and Rhine region of freshwater influence (Simpson and Souza 1995; de Boer et al. 2005). On the flooding tide, the river outflows are blocked whereas on the ebb tide, freshwater is released in pulses. They have a tendency to turn to the right on discharging from their respective river mouths and therefore, tend to flow preferentially in the direction with the coast on their right. Other processes, primarily winds and tidal currents, also serve to deflect these river plumes.

A particularly interesting feature in the numerical simulations is the anti-clockwise (often referred to as cyclonic) eddy within Kitimat Arm. This is different from the river plumes that develop downstream at the mouths from Gilttoyees Inlet, Foch Lagoon and Kitkiata Inlet, and is described further in the next section.

4.1.1.2 Cyclonic Eddy within Kitimat Arm

The region near the terminal, from Kitimat to Coste Island, illustrates a complex and somewhat unexpected circulation pattern, with a strong counter-clockwise (cyclonic) eddy developing between Bish Creek and the town of Kitimat. This eddy would have a large effect on oil slick movements. Therefore, it is informative to look at this eddy in some detail, to determine what might be causing it and to assess its validity.


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A series of hourly plots of surface current and salinity for July 14, 2004, has been prepared, and is presented in Appendix B, along with detailed descriptions. The figures include the predicted tide at Kitimat, and the observed winds at the Kitimat Eurocan site, for July 13 and 14, 2004. This eddy, which is strongest near the end of large flood tides, is shown in Figure 4-1 below.

It appears that there are several causes of this eddy:

• the flow out of Kildala Arm, which is likely the prime cause

• the Kitimat River and the geographic relationship it bears to Kitimat Arm

• the hydraulic control exerted by Minette Bay and the sand flats in front of it that lead to fast surface flows into the bay on a rising tide, which seem to draw water down the eastern side of Kitimat Arm

• the pinching of the channel at Clio Point

• the vorticity generated by shears across the main flows, from the Kitimat River and from Kildala Arm

• the internal Froude number, which characterizes the hydraulic behaviour of the two-layer system consisting of a 10-m thick upper brackish layer and a much deeper saline layer, is quite high. If a two-layer system is considered, with a density difference of 5 sigma-t units, and a layer thickness of 10 m, the internal wave speed is approximately 70 cm/s. The velocities shown in the current maps in Appendix B often approach this number, suggesting that the flow is near internal supercritical, and that nonlinear effects will be very important in this region. These nonlinear effects, arising from the advective terms in the equations of motion, are fed energy from both horizontal shears in the flow, and flow-deflecting features of the bathymetry.

• wind forcing, which may not cause the eddy, but undoubtedly affects it

Because the eddy generation process seems to be reasonable, primarily the counter-flow from the Kitimat River and from Kildala Arm, and these are both reasonably well-resolved, it seems reasonable to accept the eddy as being correctly represented by H3D. There is a well-documented similar eddying flow field at the head of Howe Sound, generated by the Squamish River inflow (Buckley 1977; Stronach et al. 1993b).

The influence of river flow is illustrated in Figure 4-2, which shows the mean surface current during the validation period. This velocity field is the effect of river flow, wind and tide. The most dominant and steady of these are river flow and the associated estuarine circulation because the freshwater must eventually make its way to the sea. A very persistent flow down Douglas Channel and Gardiner Canal is seen, which proceeds on out to Squally Channel, and is then lost in the more random and chaotic flow in Hecate Strait. On average, it is this current field which determines the fate of oil spilled in Douglas Channel, and it will always serve as a best first guess as to where an oil slick will be transported, particularly if augmented by knowledge of winds prevailing during the spill and subsequent times.


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4.1.2 Wind and Tidal Effects Re-examining the validation at CM1 in light of the above analysis, it becomes apparent that small shifts in the position of the plume and eddy will affect the current meter data. Higher resolution simulations would confirm this. However, it would appear from the above analysis that the essential elements in Kitimat Arm have been sufficiently captured to allow a detailed analysis of CM2.

Tidal effects were seen to be part of the eddy development for the region of the terminal. They will be examined further by reviewing the model results at the CM2 location. There is generally good agreement between model and observations at this location, so the discussion will be based on model results.

Figure 4-3 presents time-series of several variables at the CM2 location for a depth equivalent to the top layer of H3D. The top panel shows the observed current. Although there is considerable tidal energy, the tidal effects are largely obscured by the non-tidal flow, such as the period of fairly large inflow around September 18. The red vectors are the low-pass filtered equivalent of the surface currents at this site. A low-pass filter is a numerical procedure that acts on a time-series of values, and removes the high frequency oscillations. For example, low-passing a water level time-series could remove tidal oscillations, leaving only the low-passed sea level, which fluctuates slowly, in response to storm passages. The low-pass filter was selected to remove tidal frequency effects. There are 16 events, typically alternating between north-going and south-going, over the plotted 48-day time interval (i.e., each one lasts approximately three days). The second panel plots the wind data used by the model, and the low-pass filtered values. This time-series seems much more regular than the water velocity time-series, because it is the output of the kinematic wind model, so the direction is constrained by the topography, and can only assume one of two values: inflow; or outflow. There is a direct correlation between each wind event and the surface current. The wind inflow centred about September 19 leads to a current inflow at the same time, and the wind outflow on about September 23 leads to an outflow current, and so on. The relationship has a very important anisotropy, when there is a wind inflow, the current response is much less than the response when there is an outflow. The interaction of wind and estuarine effects is shown because estuarine flow dictates whether outflow will be stronger than inflows.

The third panel illustrates the water level fluctuations at the site, and the modelled and low-pass filtered salinity variations. The high-frequency (semi-diurnal) salinity variations have a considerable tidal component, reflecting the advection of the horizontal and vertical salinity gradients through the CM2 location by tidal currents (primarily in the up-inlet and down-inlet directions). However, no clear correlation is found between the spring-neap cycle and salinity variations. In contrast, the low-pass filtered salinities bear a similar strong relationship as the currents do to the low-pass wind field, reflecting the effect that the corresponding advective flow has on salinities at this point.

The fourth panel compares observed and harmonically-predicted currents. In general, prediction from harmonic constants is not particularly successful, even though the constants were computed from the same plotted period of time.


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The fifth panel quantifies this behaviour, plotting in blue the error in predicted velocity compared to the observed velocity, and in magenta the low-pass wind field. Once again, the effect of wind on the oceanography is shown to be considerable. However, equivalent winds on the September 18 event and the October 6 event do not lead to equivalent errors, indicating the complexity of surface currents in Douglas Channel. It is very clear that wind forcing is extremely important in determining surface currents, but the response is not always straightforward.

Figure 4-4 plots similar variables for layer 12 of the model, corresponding to a depth range, with respect to mean sea level, of 15 to 20 m. The top panel shows the observed current. Compared with Figure 4-3 for the top layer, it is clear that there is a large percentage of tidal energy at this depth. The change of velocity scales from Figure 4-3 should also be noted: currents at 10 to 15 m are approximately half the surface values. The low-passed flow is much smaller than at the surface as well, and does not show any strong correlation with the wind, shown in the second panel.

The third panel illustrates the water level fluctuations at the site, and the modelled and low-pass filtered salinity variations. The salinity variations are likely manifestations of internal waves. This type of wave is generated when fluid particles are displaced vertically as they flow over topographic features such as sills. Because of buoyant restoring forces, internal waves may be generated. Numerous studies have been carried out on topographically generated internal waves (Gill 1982; Pond and Pickard 1983; Baines 1995). Internal waves can have amplitudes of tens of metres within the water column, whereas at the sea surface minor amplitudes, in the order of centimetres, are observed.

Webster (1980) suggested that internal tides were generated by the sill in Douglas Channel. Internal tides have been studied in Northern British Columbia by Cummins and Oey (1997) and Crawford et al. (1998). Many studies on internal tide generation have been done in Knight Inlet (Farmer and Smith 1980a, 1980b; Webb and Pond 1986; Stacey and Pond 1992; Marsden and Greenwood 1994; Stacey et al. 1995; Yeremy and Stacey 1998). In contrast to the barotropic tide, internal tides have a small surface amplitude signature, but they have a large effect on the position of the isopycnals (lines on a map connecting points of equal atmospheric density) and the vertical structure of the velocity and can lead to enhanced surface currents. This is highlighted in the simple example of barotropic flow versus baroclinic (e.g., Figure 6.3 in Gill [1982]). Consequently, internal tides may have a large scale effect on a coastal system and can result in much larger surface currents than associated with the barotropic tide alone, as was noted when the harmonic constants for the model and the current meters were presented (Section 2.1.2). Whereas the barotropic tidal forcing is constant throughout the year, the internal tides are not. A seasonal modulation of the internal tides can result from changes in the strength of the stratification, related to changes in river discharge and to surface warming in summer and mixing in winter. Internal tides also introduce much shorter correlation scales than the barotropic tide and can cause surface current variations over short horizontal distances within a channel. However, as noted by Stacey et al. (1995), winds were the most important factor influencing surface currents in a detailed study of the internal tide in Knight Inlet. This observation is strongly borne out by the correlations noted between wind and surface currents in Figure 4-3.


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The fourth panel compares observed and harmonically-predicted currents. In contrast to the situation for surface currents, prediction from harmonic constants is relatively successful, at least when the constants were computed from the same plotted period of time.

The fifth panel examines the relationship between error in tidal predictions and wind forcing, plotting in blue the error in predicted velocity, and in magenta the low-pass wind field. Unlike the surface case, the low-pass wind is not well-correlated with the prediction errors. However, the low-passed currents, shown in the top panel, appear to be closely related to the errors in the tidal predictions. Thus, a more complex cause than local wind forcing is acting to disrupt the tidal currents. Determination of this more complex forcing is beyond the immediate goals of this report.

Figure 4-5 presents time-series of several variables at the CM2 location for layer 16, which represents the part of the water column between 200 m and the bottom. Continuing the trend from the surface to currents at 10 to15 m, at this depth, currents are very obviously tidal, as shown in the top panel and in the prediction errors shown in the bottom panel. Another factor of note is the relative smallness of the tidal salinity variations; near the bottom, internal tidal theory states that the amplitude of all internal tidal fluctuations decreases, and the modelled salinity time-series is in accord with that requirement. Another important phenomenon in Figure 4-5 is the decreasing modelled salinity over the plotted 48 days. The most likely explanation is that the spin-up of the model is progressing, and has not yet been completed.


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4.2 Oil Spill Model

Hydrocarbon mass balances (i.e., the distribution of hydrocarbons in the air, on the water surface, in the water column, and on shore) are determined at six example locations using the oil spill model. Results of these simulations are presented below and will be used for emergency response planning purposes, as demonstrated in Volume 7C and Volume 8C. All mass balance examples and associated trajectory displays are unmitigated.

4.2.1 Kitimat Terminal

4.2.1.1 Condensate

Spill Summary

An example spill of 250 m3 of condensate occurs at the Kitimat Terminal site in Kitimat Arm during the unloading of a tanker at 00:00 on June 24. The condensate is released over a period of 3 minutes and 40 seconds and the movement and fate of the spilled product are predicted over a 30 minute period. Specific summer wind and current conditions were chosen to represent inflow conditions.

Mass balance calculations assume that none of the hydrocarbons are contained or recovered. Thus, the modelling assumes the maximum credible hydrocarbon volumes that could interact with the environment. However, in the event of a spill, recovery, containment and booming around the tanker and exclusion booming to protect sensitive shoreline habitat would reduce the volume of hydrocarbons reaching the sensitive areas. Containment booms will be routinely used during loading all oil tankers. Therefore, in the event of a loading incident, mitigation would be in place to contain and recover oil at the Kitimat Terminal.

Approximately 62 m3 of condensate is stranded almost immediately adjacent to the north of the terminal

along a 500 m section of shoreline. The area affected reaches a maximum of 0.31 km2 about 17 minutes after the start of the spill as spreading and transport is balanced by evaporation and dispersion. Winds and currents transport condensate a maximum of 700 m north and east of the terminal. After 30 minutes, all condensate on the water or on the surface of the adjacent shorelines has completely evaporated and dispersed. Condensate that penetrates into permeable beach sediments would evaporate or disperse within two tidal cycles (25 hours).

Winds and Currents

Wind during the 30-minute period blows from the south-southwest at a speed of 9 m/s. The arrows in Figure 4-6 indicate the wind speed according to the scale on the left-hand side and point in the direction the wind is blowing towards. Wind blowing over the water surface generates waves that mix part of the spilled product on the water surface into the upper water column. Wind blowing over the water also generates surface currents that transport floating product. In this region the currents are driven by the combination of tides, fresh water input, and winds. This example spill is assumed to occur during a flood tide. Modelled current speeds are in the range of 5 to 40 cm/s for the assumed conditions.


Page 4-12 2011

Figure 4-6 Wind Speed and Direction for Kitimat Terminal ̶ Condensate Spill

Mass Balance

Table 4-1 lists the mass balance of the spilled condensate over a 30 minute period. The table lists the volume of product predicted to be present within each of the four environments at the indicated time. Condensate is less dense than water so it floats on the water surface. Condensate on the water surface spreads and light-end hydrocarbons (most volatile components) evaporate to the atmosphere. Wind blowing over the water generates waves and mixes the condensate into the upper water column. Condensate that reaches the shoreline can become stranded ashore, where it continues to evaporate or disperse.

Table 4-1 Condensate Mass Balance at Kitimat Terminal

Minutes After Spill

Water Surface (m3)

Ashore (m3)

Evaporated (m3)

Water Column (m3)

5 161 62 18 9 10 96 48 71 35 15 46 37 111 56 20 14 34 124 78 25 0 33 127 90 30 0 32 128 90 The mass balance graph (Figure 4-7) shows the distribution of the spilled condensate over each of the four environments throughout the 30-minute period. Initially most of the condensate is on the water surface and shore adjacent to the terminal. Evaporation begins immediately resulting in approximately 52% volume loss by 30 minutes. The only shoreline contact occurs adjacent to the terminal almost immediately. After 25 minutes no surface product remains and approximately 12% of the spilled volume is ashore. Approximately 38% of the condensate is naturally dispersed into the water column. Appendix C, Figure C-1 shows the pathway of the example condensate spill, unmitigated.

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Figure 4-7 Condensate Mass Balance for Kitimat Terminal

4.2.1.2 Diluted Bitumen

Spill Summary

An example spill of 250 m3 of diluted bitumen occurs at the Kitimat Terminal site in Kitimat Arm during the loading of a tanker at 00:00 on June 24. The diluted bitumen is released over a period of 3 minutes and 40 seconds and the movement and fate of the spilled product are predicted over a 12-hour period. Specific summer wind and current conditions were chosen to represent inflow conditions.

Approximately 65 m3 of oil is stranded almost immediately along a 500 m section of shoreline adjacent to the north side of the terminal. Over the first 4 hours the winds and currents transport oil north and east towards the Kitamaat Village shore. Diluted bitumen first reaches the eastern shore of the Arm at Kitamaat Village approximately 3 hours after the release, making contact along a1.5 km section of shoreline. By the end of hour 4, diluted bitumen has stranded from the marina north of Kitamaat Village to the southern marina at the end of Haisla Avenue, with a total affected shoreline of 2.5 km. No bitumen remains on the water surface after 10 hours.

Summer 250 m3 Condensate Mass Balance

Uncontained Spill

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Winds and Currents

Wind during the 12-hour period blows from the south-southwest at speeds varying from 4 to 12 m/s. The arrows in Figure 4-8 indicate the wind speed according to the scale on the left-hand side and point in the direction the wind is blowing towards. Wind blowing over the water surface generates waves that mix part of the spilled product on the water surface into the upper water column. Wind blowing over the water also generates surface currents that transport floating product. In this region the currents are driven by the combination of tides, fresh water input, and winds. This example spill is assumed to occur during a flood tide, with a counter clockwise gyre in upper Kitimat Arm favouring transport towards the eastern shore. Modelled current speeds are in the range of 5 to 40 cm/s for the assumed conditions.

Figure 4-8 Wind Speed and Direction for Kitimat Terminal ̶ Diluted Bitumen Spill

Mass Balance

Table 4-2 lists the mass balance of the spilled diluted bitumen over a 10 hour period. The table lists the volume of product predicted to be present within each of the four environments at the indicated time. The fresh diluted bitumen is less dense than water so it floats on the water surface. Diluted bitumen on the water surface spreads and light-end hydrocarbons (most volatile components) evaporate to the atmosphere. Wind blowing over the water generates waves and mixes the diluted bitumen into the upper water column. Diluted bitumen that reaches the shoreline can become stranded ashore.

Table 4-2 Diluted Bitumen Mass Balance for Kitimat Terminal

Hours After Spill

Water Surface (m3)

Ashore (m3)

Evaporated (m3)

Water Column (m3)

1 173 68 6 3 2 168 68 10 4 3 49 184 11 6 4 8 225 11 6 5 6 226 12 6 6 4 228 12 6

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Table 4-2 Diluted Bitumen Mass Balance for Kitimat Terminal (cont’d)

Hours After Spill

Water Surface(m3)

Ashore (m3)

Evaporated (m3)

Water Column(m3)

7 3 229 12 6 8 1 231 12 6 9 0 232 12 6 10 0 232 12 6 The mass balance graph (Figure 4-9) shows the distribution of the spilled bitumen over each of the four environments throughout the 12-hour period. Initially most of the oil is on the water surface and shore adjacent to the terminal. Evaporation begins immediately resulting in approximately 5% volume loss by 12 hours. The first shoreline contact occurs adjacent to the terminal almost immediately. The second shoreline contact occurs towards the end of hour 3 and by the end of hour 10 no surface product remains and approximately 93% of the spilled volume is ashore. Approximately 2% of the oil is naturally dispersed into the water column. Appendix C, Figures C-2 to C-5 show the pathway of the example diluted bitumen spill, unmitigated.

Figure 4-9 Diluted Bitumen Mass Balance for Kitimat Terminal

Summer 250 m3 Diluted Bitumen Mass Balance

Uncontained Spill

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4.2.2 Emilia Island

Spill Summary

An example spill of 10,000 m3of Syncrude synthetic light oil occurs at Emilia Island due to grounding of a SUEZMAX tanker at 00:00 on February 2. The oil is released over a period of 13 hours, with a higher rate in the first hour than the subsequent 12 hours, and the movement and fate of the spilled product are tracked over a 3 day period. The date and time of the example incident were selected so that the wind and currents would be representative of the characteristic winter outflow conditions in Douglas Channel.

Over the first 8 hours the winds and currents transport oil south and west down Douglas Channel. Oil first reaches the northern shore of Douglas Channel approximately 8 hours after the release. By the end of hour 24, oil has stranded from the initial point of contact across from Grant Point on the southwest end of Maitland Island down to Kitkiata Inlet, with a total affected shoreline of 11.5 km. For the next 15 hours, some oil moves farther south down Douglas Channel, partially oiling the shoreline between Kitkiata Inlet and Kiskosh Inlet. At hour 40, estuarine currents from Kitkiata and Kiskosh Inlets transport some oil across Douglas Channel, impacting approximately 3 km on the southwest shore of Hawkesbury Island. No oil remains on the water surface after 57 hours.

Winds and Currents

Wind during the 6 day period blows from the northwest at speeds varying from 0 to 12 m/s. The “sticks” in Figure 4-10 indicate the wind speed according to the scale on the left-hand side and point in the direction the wind is blowing towards. Wind blowing over the water surface generates waves that mix part of the spilled product on the water surface into the upper water column. Wind blowing over the water also generates surface currents that transport floating product. In this region the currents are driven by the combination of tides, fresh water input, and winds. Modelled current speeds are in the range of 5 to 34 cm/s for the assumed conditions.

Figure 4-10 Wind Speed and Direction for Emilia Island

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Mass Balance

Table 4-3 lists the mass balance of the spilled synthetic light oil over a 3 day period. The table lists the volume (cubic metres) of product predicted to be present within each of the four environments at the indicated time. The fresh synthetic light oil is less dense than water so it floats on the water surface. Synthetic light oil on the water surface spreads and light-end hydrocarbons (most volatile components) evaporate to the atmosphere. Wind blowing over the water generates waves and mixes the oil into the upper water column. Synthetic light oil that reaches the shoreline can become stranded ashore.

Table 4-3 Syncrude Synthetic Light Oil Mass Balance for Emilia Island

Hours After Spill

Water Surface(m3)

Ashore (m3)

Evaporated (m3)

Water Column(m3)

4 3,117 0 430 315 6 3,873 0 658 616 12 5,297 450 1,414 2,029 18 2,197 2,667 1,875 3,261 24 705 3,579 2,013 3,703 48 39 3,754 2,153 4,054 72 0 3,757 2,166 4,077 The mass balance graph (Figure 4-11) shows the distribution of the spilled oil over each of the four environments throughout a 3 day period. Initially all of the oil is on the water surface. Evaporation begins immediately resulting in approximately 22% volume loss by 3 days. The first shoreline contact occurs at 8 hours. By the end of hour 72 no product remains on the surface and approximately 38% of the spilled volume is ashore. Approximately 40% of the oil is naturally dispersed into the water column. Figures C-6 to C-10 show the pathway of the example synthetic-oil spill, unmitigated.


Page 4-18 2011

Figure 4-11 Syncrude Synthetic Light Oil Mass Balance for Emilia Island

4.2.3 Principe Channel

Spill Summary

An example spill of 10,000 m3 (9,460 metric tonnes) of diluted bitumen occurs in Principe Channel due to grounding of a SUEZMAX tanker at 00:00 on July 2. The diluted bitumen is released over a period of 13 hours, with a higher rate in the first hour than the subsequent 12 hours, and the movement and fate of the spilled product are tracked over a 9 day period. The spill date and time were selected so that winds and tides would be typical of summer conditions in Principe Channel.

Over the first 8 hours the winds and currents transport oil north and east up Principe Channel. Bitumen first reaches Anger Island approximately 10 hours after the release. By the end of hour 24, diluted bitumen has stranded along 8 km of Anger Island, 17.5 km of Banks Island, and 2 to 3 km of shoreline on the southwest coast of McCauley Island. Over the next two days, the bulk of surface oil moves farther northwest up Principe Channel, oiling the southwest coast of McCauley Island and a total of 25 km of Banks Island. At the end of Day 4, a shift in winds transports the remaining surface oil to the southeast, further impacting Banks Island. No bitumen remains on the water surface after nine days.

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Winds and Currents

The “sticks” in Figure 4-12 indicate the wind speed according to the scale on the left-hand side and point in the direction the wind is blowing towards. Wind during the first 4 days blew from the southeast at speeds varying from 0 to 9 m/s. From days 5 to 8, winds were mainly from the northwest, with maximum speed of 5.7 m/s. Winds shifted back to the southeast between days 8 and 9. Wind blowing over the water surface generates waves that mix part of the spilled product on the water surface into the upper water column. Wind blowing over the water also generates surface currents that transport floating product. In this region the currents are driven by the combination of tides, fresh water input, and winds. Modelled current speeds are in the range of 5 to 27 cm/s for the assumed conditions.

Figure 4-12 Wind Speed and Direction for Principe Channel

Mass Balance

Table 4-4 lists the mass balance of the spilled diluted bitumen over a 9 day period. The table lists the volume (cubic metres) of product predicted to be present within each of the four environments at the indicated time. The fresh bitumen is less dense than water so it floats on the water surface. Diluted bitumen on the water surface spreads and light-end hydrocarbons (most volatile components) evaporate to the atmosphere. Wind blowing over the water generates waves and mixes the bitumen into the upper water column. Diluted bitumen that reaches the shoreline can become stranded ashore.

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Table 4-4 Diluted Bitumen Mass Balance for Principe Channel

Days After Spill

Water Surface (m3)

Ashore (m3)

Evaporated (m3)

Water Column (m3)

0.25 5,190 0 87 17 0.5 8,215 830 259 51 1 4,094 5,116 681 109 3 1,558 7,109 1,148 185 5 456 8,030 1,298 216 6 136 8,283 1,359 222 7 30 8,327 1,420 223 8 3 8,310 1,464 223 9 0 8,272 1,505 223 The mass balance graph (Figure 4-13) shows the distribution of the spilled diluted bitumen over each of the four environments throughout a 9 day period. Initially all of the oil is on the water surface. Evaporation begins immediately resulting in approximately 15% volume loss by 9 days. The first shoreline contact occurs at 10 hours. By the end of day 9 no surface product remains and approximately 83% of the spilled volume is ashore. Approximately 2% of the oil is naturally dispersed into the water column. Appendix C, Figures C-11 to C-16 show the pathway of the example diluted bitumen spill, unmitigated.

Figure 4-13 Diluted Bitumen Mass Balance for Principe Channel

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4.2.4 Wright Sound

Spill Summary

An example spill of 36,000 m3 of diluted bitumen occurs in Wright Sound due to a VLCC collision at 00:00 on July 2. The diluted bitumen is released over a period of 13 hours, with a higher rate in the first hour than the subsequent 12 hours, and the movement and fate of the spilled product are tracked over a 15 day period. The release date and time for this example were chosen so that the prevailing winds and currents would be representative of summer conditions: inflow winds opposing the seaward-directed estuarine flow at the surface.

Over the first 15 hours persistent estuarine outflow, aided by ebbing tidal currents, transport oil south and west towards Fin Island. Diluted bitumen first reaches Fin Island approximately 8 hours after the release. As tidal currents reverse and winds from the south-southwest continue, bitumen is stranded on southern Farrant Island, northwestern Gil Island, and in the region of Hartley Bay north of the spill site between 13 and 24 hours after the spill. Ebbing tidal currents transport oil through Cridge and Lewis Passages but opposing winds keep most surface oil in Squally Channel between 24 and 48 hours after the spill. Bitumen also enters Hartley Bay and southern Grenville Channel approximately 35 hours after the spill. By the end of Day 3, oil spreads farther up Grenville Channel and enters Whale Channel. By Day 5, oil is stranded on Campania and Gil Islands and 204 kilometres of shoreline are affected. Starting on Day 5 the wind begins to reduce in velocity and change to a northerly direction, allowing the estuarine flow to carry some of the product out to open waters by way of Caamaño Sound. By Day 15, very little oil remains on the water surface or in the water column, about 76% is retained on the shore, and about 17% has evaporated.

Winds and Currents

Wind during the 15-day period blows mostly from the south-southwest at speeds varying from 0.5 to 10.5 m/s. For two brief periods on days 6-7 and 11-12 wind blows from the north. The “sticks” in Figure 4-14 indicate the wind speed according to the scale on the left-hand side and point in the direction the wind is blowing towards. Wind blowing over the water surface generates waves that mix part of the spilled product on the water surface into the upper water column. Wind blowing over the water also generates surface currents that transport floating product. In this region the currents are driven by the combination of tides, fresh water input, and winds. This example spill is assumed to occur at the end of a flood tide. Modelled current speeds are in the range of 2 to 26 cm/s for the assumed conditions.


Page 4-22 2011

Figure 4-14 Wind Speed and Direction for Wright Sound

Mass Balance

Table 4-5 lists the mass balance of the spilled diluted bitumen over a 15 day period. The table lists the volume (cubic metres) of product predicted to be present within each of the four environments at the indicated time. The fresh diluted bitumen is less dense than water so it floats on the water surface. Diluted bitumen on the water surface spreads and light-end hydrocarbons (most volatile components) evaporate to the atmosphere. Wind blowing over the water generates waves and mixes the diluted bitumen into the upper water column. Diluted bitumen that reaches the shoreline can become stranded ashore.

Table 4-5 Diluted Bitumen Mass Balance for Wright Sound

Days After Spill

Water Surface (m3)

Ashore (m3)

Evaporated (m3)

Water Column (m3)

1 25,460 7,250 2,814 476 2 18,611 12,790 3,714 885 3 16,228 14,494 4,057 1,221 4 11,933 18,175 4,398 1,494 5 9,761 19,883 4,648 1,708 6 7,567 21,587 4,974 1,872 7 5,920 22,860 5,218 2,002 8 3,200 25,332 5,385 2,083 9 2,208 26,064 5,600 2,128 10 1,545 26,504 5,793 2,158 11 989 26,925 5,910 2,176 12 413 27,399 6,001 2,187 13 323 27,392 6,093 2,192 14 281 27,356 6,167 2,196 15 196 27,372 6,233 2,199

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The mass balance graph (Figure 4-15) shows the distribution of the spilled bitumen over each of the four environments throughout the 15 day period. Initially the diluted bitumen is exclusively on the water surface. Evaporation begins immediately resulting in approximately 17% volume loss after 15 days. The first shoreline contact occurs at Fin Island 8 hours after the spill. By the end of day 15 less than 1% of the product remains on the water surface and approximately 76% of the spilled volume is ashore. Approximately 6% of the oil is naturally dispersed into the water column. Appendix C, Figures C-17 to C-23 show the pathway of the example diluted bitumen spill, unmitigated.

Figure 4-15 Diluted Bitumen Mass Balance for Wright Sound

4.2.5 Ness Rock in Caamaño Sound

Spill Summary

An example spill of 10,000 cubic metres (9,460 metric tonnes) of diluted bitumen occurs at Ness Rock due to grounding of a SUEZMAX tanker at 11:00 on February 7. The diluted bitumen is released over a period of 13 hours, with a higher rate in the first hour than the subsequent 12 hours, and the movement and fate of the spilled product are tracked over a 15 day period. The spill date and time were selected so that winds and tides would be typical of winter conditions in Hecate Strait.

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Page 4-24 2011

Over the first 22 hours, the winds and currents transport oil north and east towards Dewdney and Trutch Islands. Bitumen first reaches Dewdney Island approximately 22 hours after the release. By the end of Day 3, diluted bitumen has stranded along the western coastline of Dewdney and Trutch Islands, as well as the southern coast of Banks Island. By this time, the bitumen has split into two patches, with one portion moving north through Principe Channel, and the majority travelling up the west coast of Banks Island. At the end of Day 5, bitumen is stranded on the western coast of Pitt Island, and much of the southwest coast of Banks Island. After 15 days, bitumen has stranded on portions of the entire west coast of Banks Island.

Winds and Currents

The arrows in Figure 4-16 indicate the wind speed according to the scale on the left-hand side and point in the direction the wind is blowing towards. Wind during the first 5 days blew from the south to the southeast at speeds varying from 4.5 to 7.5 m/s. After a calmer period, southeast winds resumed, changing to the south from between days 7 and 13, with a maximum speed of 13.8 m/s. Calmer winds from the southeast prevailed until day 15. Wind blowing over the water surface generates waves that mix part of the spilled product on the water surface into the upper water column. Wind blowing over the water also generates surface currents that transport floating bitumen. In this region the currents are driven by the combination of tides, fresh water input, and winds. Modelled current speeds are in the range of 3 to 120 cm/s for the assumed conditions, and are dominated by wind forcing.

Figure 4-16 Wind Speed and Direction for Ness Rock

Mass Balance

Table 4-6 lists the mass balance of the spilled diluted bitumen over a 15 day period. The table lists the volume (cubic metres) of product predicted to be present within each of the four environments at the indicated time. The fresh bitumen is less dense than water so it floats on the water surface. Diluted bitumen on the water surface spreads and light-end hydrocarbons (most volatile components) evaporate to the atmosphere. Wind blowing over the water generates waves and mixes the bitumen into the upper water column. Diluted bitumen that reaches the shoreline can become stranded ashore.

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Table 4-6 Diluted Bitumen Mass Balance for Ness Rock

Days After Spill

Water Surface (m3)

Ashore (m3)

Evaporated (m3)

Water Column (m3)

0.25 5,049 0 10 13 0.5 8,783 0 32 35 1 9,798 10 94 98 3 785 8,628 360 227 5 342 8,802 600 256 15 42 8,365 1,311 282 The mass balance graph (Figure 4-17) shows the distribution of the spilled diluted bitumen over each of the four environments throughout a 15 day period. Initially all the bitumen is on the water surface. Evaporation begins immediately resulting in approximately 13% volume loss by 15 days. The first shoreline contact occurs at 22 hours. By the end of day 15 less than 0.5% of bitumen remains on the surface and approximately 84% of the spilled volume is ashore. Approximately 3% of bitumen is naturally dispersed into the water column. Appendix C, Figure C-24 to C-29 show the pathway of the example diluted bitumen spill, unmitigated.

Figure 4-17 Diluted Bitumen Mass Balance for Ness Rock

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4.2.6 Butterworth Rocks in North Hecate Strait

Spill Summary

An example spill of 10,000 cubic metres (8,750 metric tonnes) of Syncrude synthetic light oil (SLO) occurs at Butterworth Rocks due to grounding of a SUEZMAX tanker at 0:00 on July 7. SLO is released over a period of 13 hours, with a higher rate in the first hour than the subsequent 12 hours, and the movement and fate of the spilled product are tracked over a 5 day period. The spill date and time were selected so that winds and tides would be typical of summer conditions in Hecate Strait.

Over the first 26 hours, the winds and currents transport oil east towards the Tree Nob Group just north of Stephens Island. SLO first reaches Stephens Island approximately 30 hours after the release. By the end of Day 2, SLO has stranded along the northern tip of Stephens Island, as well as the most of the Tree Nob Group. Higher winds during Day 3 transport some remaining SLO to the northwest, narrowly missing the Dundas Islands. At the end of Day 5, SLO is stranded on the entire Tree Nob Group, the northern coast of Stephens Island, and some islets off the south coast of Melville Island.

Winds and Currents

The arrows in Figure 4-18 indicate the wind speed according to the scale on the left-hand side and point in the direction the wind is blowing towards. Winds during the first 2 days are generally weak and blow mostly from the west at speeds varying from 2.0 to 5.4 m/s. During day 2, winds shift to the southeast and increase to 8.4 m/s during day 3. Calmer winds from the north then prevailed through day 5. Wind blowing over the water surface generates waves that mix part of the spilled product on the water surface into the upper water column. Wind blowing over the water also generates surface currents that transport floating SLO. In this region, the currents are driven by the combination of tides, fresh water input, and winds. Modelled current speeds are in the range of 2 to 92 cm/s for the assumed conditions, and are dominated by tidal forcing in Day 1 and 2, and then by winds in Day 3 and 4.

Figure 4-18 Wind Speed and Direction for Butterworth Rocks

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Mass Balance

Table 4-7 lists the mass balance of the spilled SLO over a 5day period. The table lists the volume (cubic metres) of product predicted to be present within each of the four environments at the indicated time. The fresh SLO is less dense than water so it floats on the water surface. SLO on the water surface spreads and light-end hydrocarbons (most volatile components) evaporate to the atmosphere. Wind blowing over the water generates waves and mixes the SLO into the upper water column. SLO that reaches the shoreline can become stranded ashore.

Table 4-7 Syncrude Synthetic Light Oil Mass Balance for Butterworth Rocks

Days After Spill

Water Surface (m3)

Ashore (m3)

Evaporated (m3)

Water Column (m3)

0.25 4,048 0 511 163 0.5 6,855 0 1,146 442 1 6,661 0 2,014 1,325 3 139 3,312 2,542 4,007 5 0 3,323 2,543 4,134 The mass balance graph (Figure 4-19) shows the distribution of the SLO over each of the four environments throughout a 5 day period. Initially all of the oil is on the water surface. Evaporation begins immediately resulting in approximately 25% volume loss by 5 days. The first shoreline contact occurs at 26 hours. By the end of Day 5 none of SLO remains on the surface and approximately 33% of the spilled volume is ashore. Approximately 41% of SLO is naturally dispersed into the water column by wave action. Figures C-30 to C-34 show the pathway of the example synthetic-oil spill, unmitigated.


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Figure 4-19 Syncrude Synthetic Light Oil Mass Balance for Butterworth Rocks

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Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning Technical Data Report Section 5: Summary and Recommendations

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5 Summary and Recommendations Season-specific simulations illustrated the effects of wind, estuarine flow and tides (the predominant factors influencing surface currents at the example spill locations) on spill behaviour. In almost all simulations, the most influential factor is the wind, which often blew from a fixed direction for several days at a time, driving the oil in a particular direction. The estuarine circulation gave a persistent outflow tendency to the movement of the slick, except in Principe Channel. Tides had an influence on the initial movement of the oil and on small-scale movement at tidal periods. For the selected spill examples, although simulated spills exhibited variability, there is a persistent seaward motion of spilled oil or condensate as a result of outflow winds in the winter and estuarine circulation in the summer. However, depending on wind and tide, smaller amounts of oil or condensate can also travel through the various side-channels connected to Douglas Channel.

The hydrodynamic model, used to estimate surface currents, calibrated well against water level and current meter observations but could be improved in the following ways:

• calibrating the reproduction of tidal water levels

• extending the number of input stations used for meteorological forcing

• ensuring that daily river flow values are used when available

• investigating the influence of forcing resulting from atmospheric pressure gradients

• improving the vertical resolution in the depth range of 15 to 25 m

• extending the spin-up process to a year-long period, before extracting data from the model

• calibrating the parameter specifying the ratio between vertical eddy diffusivity and vertical eddy viscosity

• incorporating a finer resolution grid for the spill simulations

The oil spill model provides simulations of the fate of spilled hydrocarbons at the example locations.

These simulations and subsequent mass balance predictions will be useful in developing response plans and in directing response efforts in the event of a spill. During actual response, modeling results are updated regularly as spill surveillance and tracking results are obtained. Modelling procedures could be readily adapted to provide real-time nowcasts (weather forecasts predicting the weather for a very short upcoming period, usually of a few hours) and forecasts for operational use in emergency response. In addition to collecting data for model calibration and validation, experiments in an operational model could be designed so that the errors in model predictions could be quantified, in a similar manner to strategies employed by the Canadian Coast Guard. The errors between observed and computed drift positions then become factors that are used to augment search areas. A similar process would be the next logical step for this model.

Hydrocarbon Mass Balance Estimates: Inputs for Spill Response Planning Technical Data Report Section 6: References

2011 Page 6-1

6 References

6.1 Literature Cited Arakawa, A. and V.R. Lamb. 1977. Computational design of the basic dynamic processes of the UCLA

general circulation model. Methods of Computational Physics, 16: 173−263.

ASL Environmental Sciences Inc. (ASL) 2010a. Marine Physical Environment Technical Data Report. Prepared for Northern Gateway Pipelines Inc. Calgary, AB.

ASL Environmental Sciences Inc. (ASL). 2010b. Weather and Oceanographic Conditions at Sites in the CCAA and in Queen Charlotte Sound, Hecate Strait and Dixon Entrance Technical Data Report. Prepared for Northern Gateway Pipelines Inc. Calgary, AB.

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