Baroclinic Effect on Modeling Deep Flow in Brown Passage, BC, Canada

Journal of Marine Science and Engineering

Article Baroclinic Effect on Modeling Deep Flow in Brown Passage, BC, Canada

Yuehua Lin *, David B. Fissel, Todd Mudge and Keath Borg

ASL Environmental Sciences Inc., #1-6703 Rajpur Place, Victoria, BC V8M 1Z5, Canada; dﬁ[email protected] (D.B.F.); [email protected] (T.M.); [email protected] (K.B.) * Correspondence: [email protected]; Tel.: +1-250-656-0177 (ext. 146)

Received: 4 August 2018; Accepted: 8 October 2018; Published: 12 October 2018

Abstract: Brown Passage is a deep (up to 200 m) ocean channel connecting the western offshore waters of Hecate Strait and Dixon Entrance on the Pacific continental shelf with the eastern inland waters of Chatham Sound in Northern British Columbia, Canada. A high-resolution 3D finite difference hydrodynamic model, COastal CIRculation and SEDiment transport Model (COCIRM-SED), was developed in 2010 and 2013 to determine the tidal and wind-driven currents of this area. The barotropic model results for ocean currents were found to be in reasonably good agreement with the historical ocean current observations at near-surface and middle depth available for Brown Passage. Operated from October 2014 to April 2015, the first modern oceanographic measurement program in Brown Passage found surprisingly strong near-bottom currents (the 99th percentile current speed reaches 53 cm/s at 196 m). As a result, the COCIRM-SED model was modified and rerun, with the most important change incorporating water density/salinity fields as modeled variables. This change led to considerable improvements in the ability of the model to generate episodes of relatively strong currents in the bottom layers. The bottom intensification in ocean currents in Brown Passage is shown to be due to semi-diurnal internal tides, which were not previously included in the barotropic version of the 3D model. This finding for the near-bottom flow from the qualitative modeling study is important for applications of the potential sediment deposition and resuspension studies.

Keywords: Brown Passage; Chatham Sound; internal tides; circulation; numerical model; stratification; barotropic; baroclinic

1. Introduction Brown Passage is a deep (up to 200 m below chart datum, i.e., the reference level for depths used on a nautical chart) ocean channel connecting the western offshore waters of Hecate Strait and Dixon Entrance on the Paciﬁc continental shelf with the eastern inland waters of Chatham Sound in Northern British Columbia, Canada (Figure1). Where Chatham Sound is a semi-enclosed inland sea spanning a total distance of approximately 70 km from south to north and has width of 15–25 km with water depths generally less than 200 m [1]. On its western side, it is separated from the more exposed open waters of Dixon Entrance and Hecate Strait by several island groups separated by channels or passages. Among them the two largest and deepest passages are the eastward extension of Dixon Entrance to the north of Dundas Island; and Brown Passage in central Chatham Sound, which are the most important channels allowing the exchanges of water and wave energy with the larger water bodies to the west.

J. Mar. Sci. Eng. 2018, 6, 117; doi:10.3390/jmse6040117 www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2018, 6, 117 2 of 21 J. Mar. Sci. Eng. 2018, 6, x 2 of 21

FigureFigure 1.1.Location Location of Brownof Brown Passage Passage (in red) (in based red) onbased gridded on coastlinegridded datacoastline from griddeddata from bathymetry gridded databathymetry (retrieved data from (retrieved the website from of the the British websit Oceanographice of the British Data Centre: Oceanographic https://www.gebco.net/ Data Centre: data_and_products/gridded_bathymetry_data/https://www.gebco.net/data_and_products/gridded_bathymetry_data/).). The ocean currents in Chatham Sound are highly variable due to a combination of forcing by the The ocean currents in Chatham Sound are highly variable due to a combination of forcing by the large mean tidal range within this area, seasonally strong winds, and large peak freshwater discharges large mean tidal range within this area, seasonally strong winds, and large peak freshwater from the Skeena and Nass Rivers. Chatham Sound is characterized by lower salinity (~20 Practical discharges from the Skeena and Nass Rivers. Chatham Sound is characterized by lower salinity (~20 Salinity Unit (PSU)) near-surface waters on its eastern side, due to the Skeena River inﬂow to Southern Practical Salinity Unit (PSU)) near-surface waters on its eastern side, due to the Skeena River inflow Chatham Sound [1]. More saline waters present on the western side of the Chatham Sound result from to Southern Chatham Sound [1]. More saline waters present on the western side of the Chatham the exchange through Brown Passage and other connecting channels with the higher salinity waters of Sound result from the exchange through Brown Passage and other connecting channels with the Hecate Strait and Dixon Entrance. higher salinity waters of Hecate Strait and Dixon Entrance. Oceanographic research of this complex oceanic- and river-dominated inland waterway [2] is Oceanographic research of this complex oceanic- and river-dominated inland waterway [2] is being driven by industrial activities related to the expansion of the port of Prince Rupert (Figure1), being driven by industrial activities related to the expansion of the port of Prince Rupert (Figure 1), along with high levels of marine biological productivity and a very active regional ﬁshery in Chatham along with high levels of marine biological productivity and a very active regional fishery in Chatham Sound [3]. Recent research into this oceanic environment is motivated by studies of the possible use of Sound [3]. Recent research into this oceanic environment is motivated by studies of the possible use this area for disposal at sea of dredged sediments arising from expansion of marine terminals in and of this area for disposal at sea of dredged sediments arising from expansion of marine terminals in around the Prince Rupert harbor in Chatham Sound [2]. A better understanding of hydrodynamics and around the Prince Rupert harbor in Chatham Sound [2]. A better understanding of throughout the whole water column in Brown Passage is required, for the potential short-term sediment hydrodynamics throughout the whole water column in Brown Passage is required, for the potential transport and long-term resuspension processes with ocean currents. short-term sediment transport and long-term resuspension processes with ocean currents. The spatial extent of the surface expression of the sediment plume from the Skeena River was The spatial extent of the surface expression of the sediment plume from the Skeena River was derived using historical 30 m resolution LANDSAT imagery (available online from the US Geological derived using historical 30 m resolution LANDSAT imagery (available online from the US Geological Survey). The LANDSAT satellite, LANDSAT-8, which became operational in 2012–2013, has much Survey). The LANDSAT satellite, LANDSAT-8, which became operational in 2012–2013, has much better radiometric sensitivity (10× Landsat 7) which makes it more useful for water applications better radiometric sensitivity (10× Landsat 7) which makes it more useful for water applications involving subtle signals such as river plumes. One LANDSAT-8 scene, 28 August 2013 (Skeena River

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J. Mar. Sci. Eng. 2018, 6, x 3 of 21 involving subtle signals such as river plumes. One LANDSAT-8 scene, 28 August 2013 (Skeena River dischargedischarge ofof 665665 mm33/s) was was selected selected and and enhanced, enhanced, as as shown shown in Figure 22 (Figure(Figure 55 inin [ [1]).1]). TheThe moremore sensitivesensitive detectiondetection of thethe LANDSAT-8LANDSAT-8 satellitesatellite imageimage scenescene revealsreveals thatthat thethe SkeenaSkeena RiverRiver plumeplume isis detectabledetectable alongalong the the eastern eastern half half of Chatham of Chatham Sound Soun intod the into northern the northern half of Chatham half of Chatham Sound. However, Sound. commensurateHowever, commensurate with the relatively with the low relatively discharges, low thedischarges, Skeena River the Skeena plume River is conﬁned plume to is the confined estuarine to areathe estuarine with a secondary area with areaa secondary of enhanced area of turbidity enhanced levels turbidity in the levels area asin farthe northwestarea as far asnorthwest the Digby as Islandthe Digby (Figure Island1). (Figure 1).

3 FigureFigure 2.2. EnhancedEnhanced LandsatLandsat 88 satellitesatellite imageimage forfor ((aa)) 2828 AugustAugust 20132013 (ebb(ebb flow, flow, under under 665 665 m m/s3/s riverriver 3 dischargedischarge fromfrom the the Skeena Skeena River) River) and and (b )(b 5) April 5 April 2015 2015 (flood (flood flow, flow, under under 200 m 200/s m river3/s river discharge discharge from thefrom Skeena the Skeena River). River).

TheThe pathwayspathways ofof freshwaterfreshwater from thethe SkeenaSkeena RiverRiver areare highlyhighly dependentdependent onon thethe SkeenaSkeena RiverRiver dischargedischarge valuesvalues [[4].4]. Under average discharges, aboutabout 70%70% ofof thethe freshwaterfreshwater dischargedischarge leavesleaves onon thethe easterneastern sideside ofof central central and and northern northern Chatham Chatham Sound, Sound, where where it merges it merges with with Nass Nass River River freshwater freshwater and exitsand exits via Dixon via Dixon Entrance. Entrance. Only 30%Only of 30% the freshwaterof the freshwater leaves Chatham leaves Chatham Sound through Sound thethrough southern the andsouthern central and passages, central withpassages, half of with this half being of by this the be waying onby thethe westway (e.g.,on the Brown west Passage,(e.g., Brown see FigurePassage,3). Duringsee Figure late 3). May During and earlylate May June and peak early discharges June peak (freshet) discharges of the (freshet) Skeena and of the Nass Skeena rivers, and the Nass freshwater rivers, leavesthe freshwater the Sound leaves via all the the Sound passages via all with the the passag greatestes with flux the through greatest Dundas flux through Passage Dundas (Figure1 Passage). Nass River(Figure discharge 1). Nass also River affects discharge Chatham also Sound affects salinity, Chatham but itsSound seasonal salinity, variability but its is seasonal very similar variability to Skeena is Riververy similar discharges, to Skeena except River during discharges, the fall season,except duri dueng to athe greater fall season, effect due from to precipitation. a greater effect During from freshet,precipitation. Nass River During water freshet, extends Nass as River far south water as extends Melville as Island far south (Figure as 1Melville). Due to Island the large (Figure mean 1). tidal Due rangeto the oflarge Chatham mean tidal Sound, range the of salinity, Chatham temperature, Sound, the and salinity, freshwater temperature, time series and at freshwater fixed locations time series were observedat fixed locations to exhibit were variability observed at tidalto exhibit periods. variabil Duringity at periods tidal periods. of unsteady During river periods discharges, of unsteady large cellsriver of discharges, relatively freshlarge watercells of are re dischargedlatively fresh into water the Sound are discharged from the Skeena into the River; Sound these from are the gradually Skeena dispersedRiver; these under are gradually the influence dispersed of the under large the tides, influe winds,nce of and the the large kinetic tides, and winds, potential and the energy kinetic of and the freshwaterpotential energy flows of themselves. the freshwater flows themselves.

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3 FigureFigure 3. 3.Surface Surface salinity salinity pattern pattern duringduring normalnormal river conditions conditions (under (under 700–1000 700–1000 m m3/s /sriver river discharge discharge fromfrom the the Skeena Skeena River), River), 10–19 10–19 August August 19481948 (Figure 6 in [4]). [4]).

HistoricalHistorical conductivity conductivity temperature temperature depthdepth (CTD) and and bottle bottle data data extracted extracted from from the the Department Department ofof Fisheries Fisheries and and Oceans Oceans (DFO) (DFO) database database (see (see http://www.pac.dfo-mpo.gc.ca/science/oceans/data- http://www.pac.dfo-mpo.gc.ca/science/oceans/data- donnees/index-eng.htmldonnees/index-eng.html)) forfor BritishBritish Columbia (BC) (BC) coastal coastal waters waters (from (from 183 183 sites) sites) were were examined examined for for ChathamChatham Sound Sound domain domain by by Lin Lin and and FisselFissel (2018)(2018) [[1].1]. Each Each CTD/bottle CTD/bottle site site provided provided a vertical a vertical profile proﬁle ofof the the temperature temperature and and salinity. salinity. DuringDuring the freshet season season of of the the Skeena Skeena River, River, i.e., i.e., June June to toAugust August (summer), Southern Chatham Sound features lower salinity (as low as 20 PSU) and a wide temperature

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(summer), Southern Chatham Sound features lower salinity (as low as 20 PSU) and a wide ◦ rangetemperature from 6 range to 15 fromC. During 6 to 15 non-freshet °C. During seasons non-freshet (winter: seasons December (winter: to February, December spring: to February, March tospring: May, andMarch fall: to September May, and to fall: November), September Southern to November), Chatham Southern Sound has Chatham lower salinity Sound (25has PSU) lower at ◦ ◦ ◦ surface,salinity (25 and PSU) temperature at surface, ranged and temperature only from ranged 7 to 8 Conly in winter,from 7 to 6 to8 °C 7 inC winter, in spring, 6 to and7 °C 8 in to spring, 10 C inand fall. 8 to Surface 10 °C salinityin fall. Surface is lower salinity than in is freshet lower (summer) than in freshet season. (summer) Water is mainlyseason. uniformWater is for mainly both temperatureuniform for both and salinitytemperature in Western and salinity Chatham in Sound,Western except Chatham during Sound, summer exce timept during (it might summer be affected time by(it limitedmight be data affected availability by limited as well). data However, availability direct as observations well). However, for ocean direct currents observations in Brown for Passage ocean arecurrents very rare.in Brown Ocean Passage current are data very were rare. collected Ocean curre in fallnt 1991 data at were the DFOcollected ocean in currentfall 1991 mooring at the DFO site (CP02)ocean current located mooring near the site regional (CP02) ocean located disposal near sitethe regional (Figure4 ).ocean disposal site (Figure 4).

Figure 4.4. AA map map of of water water depths depths in Brownin Brown Passage Passage (meters (meters below below chart datum)chart datum) and the and model the domain. model domain. The remainder of the paper is arranged as follows. A brief overview of the barotropic modeling is presentedThe remainder in Section of the2. The paper observational is arranged dataas follows. and analysis A brief areoverview presented of the in barotropic Section3. Section modeling4 presentsis presented the baroclinicin Section modelling2. The observational and the comparison data and betweenanalysis are model presented results andin Section observations 3. Section near 4 thepresents bottom. the Thebaroclinic ﬁnal section modelling is a summary and the comparis and conclusion.on between model results and observations near the bottom. The final section is a summary and conclusion.

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2. Previous Modeling Studies The circulation of the larger areas of the BC north coast, adjoining Chatham Sound, including Queen Charlotte Sound, Hecate Strait, and Dixon Entrance, has been studied through numerical modeling methods. Hannah et al. (1991) described the wind-driven (no tides), depth-averaged circulation in Queen Charlotte Sound and Hecate Strait [5]. Ballantyne et al. (1996) used a 3D finite element model to compute the buoyancy-driven flows, as well as the barotropic tides of the BC north coast [6]. The tidal currents of the BC north coast have also been modeled by Flather (1987) [7] for the northeast Pacific Ocean; Foreman et al. (1993) [8] for the barotropic tide in the BC north coast; Cummins and Oey (1997) [9] for the barotropic and baroclinic tides of the BC north coast; and Foreman et al. (2000) [10] for assimilating satellite altimeter observations into a barotropic tidal model over the northeast Pacific Ocean. Brown Passage was included in the much larger model BC north coast model domains, but the availability and validity of the model circulation results for Brown Passage were compromised by the poor spatial resolution (e.g., coarser than 1 km in the horizontal). A much higher spatial resolution 3D finite difference numerical model, COastal CIRculation and SEDiment transport Model (COCIRM-SED; [11–14]), was developed by Jiang and Fissel in 2012 [2]. This model was applied to determine the tidal and wind-driven currents in Brown Passage and used to simulate the transport and deposition of sediments released from disposal at sea activities. COCIRM-SED is a highly integrated model, consisting of five submodules, including circulation, wave, multisize sediment transport, morphodynamics, and water quality. The model can be operated on either an integrated or an individual module basis. In the barotropic modeling of Brown Passage [2], the COCIRM-SED model was operated over a numerical model domain for the full area of Brown Passage, with a total area of 20.7 km by 29 km (Figure4). A horizontal grid size resolution of 100 m by 100 m was used for the model area. In the vertical, the model used 22 sigma-layers with higher resolutions realized near the surface and bottom. The depths of model layers are computed as (Sigma-layer thickness) × (Total water depth) = ∆σH. The digital bathymetric data set, in the format of Universal Transverse Mercator (UTM) Easting, UTM Northing, and seabed elevation relative to chart datum, was gridded to provide suitable representation of the water depths in the model. The model was forced by tidal height elevations spanning four open boundaries and by surface winds. The four model open boundaries consist of the four adjoining sides of Brown Passage (Figure4). The forcing at the four open boundaries are limited to tidal elevations and do not include wind forced flows. Tidal elevations at these four open boundaries were derived from 7 major tidal height constituents (O1, P1, K1, N2, M2, S2, K2) using the DFO standard tidal prediction program [15]. The tidal constituents for the reference Qlawdzeet Anchorage, port of Prince Rupert, and Lawyer Islands, were obtained from Canadian Hydrographic Service of DFO (Table1). Coriolis force was also activated.

Table 1. Tidal constituents at tide gauge stations used for model open boundary conditions.

Qlawdzeet Anchorage Tide Gauge Prince Rupert (#9354) Lawyer Islands (#9312) (#9315) Tidal Amplitude Amplitude Amplitude Phase (deg) Phase (deg) Phase (deg) Constituents (m) (m) (m) Z0 369.00 0.00 387.09 0.0 387.09 0.00 O1 30.78 129.80 31.25 132.46 31.25 132.44 P1 15.36 136.60 16.06 135.84 16.06 135.82 K1 49.38 139.60 51.44 139.48 51.44 139.46 N2 34.53 14.40 39.52 14.9 39.52 14.87 M2 183.82 34.90 195.65 35.79 195.65 35.76 S2 57.79 56.70 64.45 59.26 64.45 59.23 K2 16.82 48.50 17.38 50.65 17.38 50.62 J. Mar. Sci. Eng. 2018, 6, 117 7 of 21

This model run involved both tidal forcing at the open boundaries and surface wind forcing using J. Mar. Sci. Eng. 2018, 6, x 7 of 21 measured hourly winds at the Prince Rupert airport weather station for the same period. As shown in Figurewind5a, speeds the dominant are from wind the south directions to southeast. in terms Wind of frequency forcing is of applied occurrence as a space-uniform and higher wind but speedstime- arevarying from the value south on to the southeast. model grids. Wind forcing is applied as a space-uniform but time-varying value on the modelThe grids. model was initially tested with a calibration run. Various physical parameters, mainly bottomThe model drag coefficient was initially and horizontal tested with and avertical calibration eddy diffusivity run. Various coefficients physical, as parameters, well as major mainly tidal bottomconstituent drag coefficient phases, were and repetiti horizontalvely andadjusted vertical to achieve eddy diffusivity optimal agreement coefficients, with as wellthe observations as major tidal constituentand physically phases, reasonable were repetitively flow patterns adjusted in Brown to achieve Passage. optimal The Smagorinsky agreement with eddy the parameterization observations and physically[16] was reasonable used for horizontal flow patterns diffusivity in Brown with Passage.coefficient The C = Smagorinsky 0.08. The background eddy parameterization vertical diffusion [16 ] wasand used viscosity for horizontal were set diffusivityto 10−6 m2/swith with coefficienta MY2.5 (MellorC = 0.08. and The Yamada) background [17] turbulence vertical diffusionclosure. The and viscositybottom were roughness set to 10 parameter−6 m2/s withwas set a MY2.5 to 0.001 (Mellor m with and a value Yamada) of 0.015 [17 ]for turbulence the bottom closure. drag coefficient. The bottom roughnessReaders parameterare referred was to set Jiang to 0.001 and mFissel with a(2011) value [2] of 0.015for more for the details bottom on dragthe coefficient.model setup Readers and aredevelopment. referred to Jiang and Fissel (2011) [2] for more details on the model setup and development.

FigureFigure 5. Compass5. Compass rose rose plots plots for for wind wind speed speedand and directiondirection distributions measured measured at at (a ()a Prince) Prince Rupert Rupert AirportAirport and and (b )(b Lucy) Lucy Island Island (see (see Figure Figure1). 1). The The wind wind datasets datasets werewere obtainedobtained from from the the Meteorological Meteorological ServiceService of Canada,of Canada, Environment Environment and and Climate Climate Change Change Canada.Canada.

TheThe model model was was operated operated for for a a 17-day-long 17-day-long fallfall periodperiod (5–22 October 1991) 1991) and and compared compared with with oceanocean current current data data at at the the DFO DFO current current meter meter mooring mooring sitesite located to to the the southeast southeast of of Melville Melville Island Island (Figure(Figure4). The4). The model model results results for for ocean ocean currents currents were were found found toto bebe inin reasonably good good agreement agreement with with thethe two two sets sets of ocean of ocean current current observations observations at 15 at m 15 (Figure m (Figure6) and 6) 98 and m (Figure 98 m 7(Figure), notably, 7), thenotably, similarity the of thesimilarity large tidal of the currents large tidal of 6–12currents September, of 6–12 Sept andember, the good and agreement the good agreement in the tidal in currentthe tidal directions current especiallydirections at 15especially m depth at of 15 the m modeldepth of results the model with resu the datalts with available the data for availabl Browne Passagefor Brown [2 ].Passage A statistical [2]. analysisA statistical of the analysis verification of the model verification results model shows results that shows the correlation that the correlation coefficients coefficients between between modeled andmodeled measured and current measured speeds current and speeds directions and directions are greater are thangreater 0.5 than near 0.5 the near surface. the surface. Relatively Relatively weak correlationweak correlation with a coefficient with a coefficient at about at 0.4about occurs 0.4 occurs for the for verification the verification case case at 98 at m98 depth.m depth. Readers Readers are referredare referred to Jiang to andJiang Fissel and Fissel (2011) (2011) [2] for [2] more for more details details on the on modelthe model calibration calibration and and verification. verification. Based on the generally favorable model verification results, it was concluded that the circulation Based on the generally favorable model verification results, it was concluded that the circulation module was reasonably well validated and is, thus, suitable for simulating disposal sediment module was reasonably well validated and is, thus, suitable for simulating disposal sediment transport transport and fate in Brown Passage. Based on these results, Brown Passage was thought to be and fate in Brown Passage. Based on these results, Brown Passage was thought to be generally well generally well mixed through the middle and lower parts of the water column. mixed through the middle and lower parts of the water column.

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Figure 6. Modeled and measured results of current (a) speeds and (b) directions located at the Figure 6. a b Figurehistorical Modeled6. oceanModeled current and and measured mooring measured results site results marked of current of in current Figu ( )re speeds 4( fora) speedsnear-surface and ( and) directions ( oceanb) directions currents located located at at 15 the m historical depth.at the oceanhistoricalAs currentFigure ocean 4 mooring in [2]. current site mooring marked site in Figure marked4 for in Figu near-surfacere 4 for near-surface ocean currents ocean at currents 15 m depth. at 15 As m Figuredepth. 4 in [As2]. Figure 4 in [2].

FigureFigure 7. Modeled7. Modeled and and measured measured results results of current of current (a) speeds (a) speeds and (b and) directions (b) directions located located at the historical at the oceanFigurehistorical current 7. oceanModeled mooring current and site mooringmeasured marked site in results Figuremarked of4 for incurrent Figu oceanre (4a currents )for speeds ocean at andcurrents 98 m(b depth.) directions at 98 Asm depth. Figure located As 5 inFigureat [ 2the]. historical5 in [2]. ocean current mooring site marked in Figure 4 for ocean currents at 98 m depth. As Figure 5 in [2].

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3.3. Near-Bottom Near-Bottom Current Current Measurements Measurements in in Brown Brown Passage Passage TheThe first first modern modern oceanographic oceanographic measurement measurement programprogram forfor the the near-bottom near-bottom currents currents in in Brown Brown PassagePassage waswas conducted from from mid- mid-OctoberOctober 2014 2014 to to April April 2015. 2015. The The measurements measurements were were made made at a atlocation a location in approximately in approximately 200 m 200 water m waterdepth within depth withina previously a previously used ocean used disposal ocean site disposal (Figure site 8). (FigureThe mooring8). The mooringconfiguration configuration was a tautline was a moor tautlineing mooringASL-DualCage ASL-DualCage frame supporting frame supporting an upward- an upward-lookinglooking acoustic acoustic Doppler Doppler current current profiler profiler (ADCP, (ADCP, 300 kHz) 300 kHz)to collect to collect current current data data through through the themajority majority of ofthe the water water column column and and a asingle single point point current current meter meter (Teledyne (Teledyne doppler volume sampler,sampler, DVS)DVS) mounted mounted to to tandem tandem PORT PORT acoustic acoustic releases releases to measureto measure currents currents within within the bottom the bottom 5 m. As5 m. well, As anwell, RBR an XR-420 RBR XR-420 CTD+Tu CTD+Tu instrument instrument was mounted was moun to theted DualCage to the DualCage to collect to temperature, collect temperature, salinity, andsalinity, turbidity and dataturbidity (Figure data9). (Figure It should 9). be It notedshould that be linenoted lengths that line and lengths heights and provided heights in provided this image in arethis only image approximate. are only approximate. The DVS stopped The DVS operating stopped on operating 9 March 2015,on 9 March about one2015, month about prior one tomonth the recoveryprior to the operations recovery due operations to an instrument due to an malfunction. instrument malfunction.

FigureFigure 8. 8.Study Study area area including including bathymetry bathymetry (contours (contours depths depths below below chart chart datum) datum) and and the the location location of of acousticacoustic Doppler Doppler current current proﬁler profiler (ADCP) (ADCP) measurements. measurements.

FullFull water water column column velocities velocities were were analyzed analyzed at at all all levels levels with with valid valid data data obtained obtained by by the the ADCP ADCP instrumentinstrument every every 15 15 min. min. InIn addition,addition, currentscurrents withwith 15-min15-min intervalsintervals atat aa single single water water depth depth were were derivedderived fromfrom thethe DVS DVS (doppler (doppler volume volume sampler) sampler) measurements. measurements. PlotsPlots ofof speedspeed andand directiondirection areare shownshown inin FigureFigure 10 10 for for the the full full water water column. column. TheThe baroclinicitybaroclinicity ofof thethe flowflow fieldfield was was established established especiallyespecially through through the the directional directional variability variability of near-bottom of near-bottom flows, whichflows, showswhich episodes shows ofepisodes relatively of strongrelatively currents strong in currents the bottom in the layers bottom (as redlayers colored (as red bottom colored areas bottom in Figure areas 10in b)Figure relative 10b) to relative those at to mid-depththose at mid-depth levels. levels.

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FigureFigureFigure 9. 9. 9.MooringMooring Mooring configuration. conﬁguration.configuration.

Figure 10. Daily vector average current (a) speed and (b) direction for the full water column. FigureFigure 10. 10. Daily Daily vector vector average average current current (a )( aspeed) speed and and (b ()b direction) direction for for the the full full water water column. column.

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The lowest current speedsspeeds werewere observedobserved inin thethe middlemiddle ofof thethe water column (133(133 m) rather than near thethe bottombottom ofof thethe waterwater column,column, asas isis moremore usuallyusually thethe case.case. TheThe measuredmeasured currentcurrent speedsspeeds atat mid-depth levelslevels are generallygenerally consistent with the historical DFO measurements atat a nearby location (see(see FigureFigure4 4)) at at 98 98 m m depth. depth. The The 99th 99th percentile percentile current current speed speed from from the the DFO DFO site site was was 32 32 cm/s cm/sas as comparedcompared toto aa valuevalue ofof 3838 cm/scm/s at at 98 98 m m measurement measurement depth in the ADCP program. Larger currentcurrent speeds speeds occur occur at near-bottomat near-bottom levels le withinvels within 25–30 m25–30 of the m seabed. of the Theseabed. 99th percentileThe 99th currentpercentile speed current is 36 speed cm/s is at 36 133 cm/s m water at 133 depth, m water increasing depth, increasing to 40 cm/s to at 40 181 cm/s m at depth 181 m and depth 53 cm/s and 53 at 196cm/s m at water 196 m depth, water about depth, 3.5 about m above 3.5 m the above seabed. the se Theabed. cumulative The cumulative distribution distribution function function (CDF) curves(CDF) forcurves both for observed both observed current speedcurrent time speed series time at theseries deepest at the ADCP deepest measurement ADCP measurement level (181 m)level and (181 at them) DVSand at measurement the DVS measurement level (196 m), level shown (196 in m), Figure shown 11, revealsin Figure that 11, the reveals largest that observed the largest current observed speeds arecurrent consistently speeds are higher consistently just above higher the seabed just above over th thosee seabed observed over those at 15 mobserved above inat the15 m water above column. in the Aswater well column. as the increased As well as speeds the increased of the currents speeds within of the 30 currents m of the within seabed, 30 the m ship-basedof the seabed, temperature the ship- andbased salinity temperature proﬁle measurementsand salinity profile revealed measuremen higher densitiests revealed due tohigher increased densities salinities due to in increased this deep boundarysalinities in layer this ofdeep the boundary water column. layer of the water column.

Figure 11.11. CurrentCurrent speeds speeds at at the the deepest ADCP measurement level (181 m) and at the DVSDVS measurement level (196(196 m).m). The vertical dash lineline marks 2525 cm/scm/s which is associated with 11% cumulativecumulative distributiondistribution functionfunction (CDF) (CDF) (89th (89th percentile) percentile) for for 181 181 m m depth depth and and 16% 16% (84th (84th percentile) percentile) for 196mfor 196m depth. depth.

The bottom-mounted CTD-derivedCTD-derived time series of temperaturetemperature andand salinitysalinity atat 7 m off thethe seabed ◦ showshow largelarge variationsvariations ofof upup toto 44 °CC (temperature)(temperature) andand 11 PSUPSU (salinity)(salinity) occurringoccurring episodicallyepisodically overover periodsperiods of days to weeks. weeks. Three Three groups groups of of CTD CTD casts casts were were completed completed during during the the deployment deployment on on15 15October October 2014, 2014, 27 27March March 2015, 2015, and and 18–19 18–19 April April 2015. 2015. There There were were multiple multiple profiles profiles collected collected each each day daywith with variability variability in association in association with different with different tidal phases. tidal phases. The cast-derived The cast-derived density density profiles profiles are shown are shownin Figure in Figure12. In fall 12. 2014, In fall the 2014, lower the half lower of halfthe water of the column water column is occupied is occupied by the bymore the saline more salinedeep water deep waterthan seen than in seen the in CTD the CTD casts. casts. The Thepotential potential reason reason is that is that higher higher salinity salinity waters waters from from Hecate Hecate Strait moved into Brown PassagePassage from thethe westwest duringduring thisthis period.period. To betterbetter examineexamine thethe waterwater structurestructure and the dynamics of the observed deep flowflow in BrownBrown Passage, a baroclinic hydrodynamic modeling studystudy waswas carriedcarried outout inin thethe nextnext section.section. The near-bottomnear-bottom currentscurrents areare observedobserved atat depthsdepths ofof 181181 mm andand 196196 mm belowbelow chartchart datum,datum, inin thethe measurements of two different instruments,instruments, the ADCPADCP and the DVS,DVS, soso thatthat thethe baroclinicbaroclinic signalssignals foundfound inin thesethese near-bottomnear-bottom currentscurrents areare notnot duedue toto thethe equipmentequipment itself.itself.

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FigureFigure 12. 12.Density Density proﬁles profiles as as measured measured byby CTD casts casts during during the the three three periods. periods.

4. Baroclinic4. Baroclinic Modeling Modeling Study Study for for Deep Deep Flow Flow in in BrownBrown Passage Passage

4.1. Model4.1. Model Setup Setup The 3DThe hydrodynamic 3D hydrodynamic model model COCIRM-SED COCIRM-SED used in in this this study study is isbased based on onJiang Jiang and andFissel Fissel [2] [2] usingusing the same the same model model domain domain (Figure (Figure4) 4) and and resolution resolution inin both the the horizontal horizontal (100 (100 m) m)and and the thevertical vertical (22 sigma(22 sigma layers layers with with higher higher resolutions resolutions realized realized near near the surface surface and and bottom). bottom). The The model model was wasforced forced at tidalat heighttidal height elevations elevations spanning spanning four four open open boundaries, boundaries, and and by by local local surface surface winds winds (the (the remote remote wind effectwind is not effect considered). is not considered). The surface The wind surface data wind (applied data (applied to model to model grids atgrids each at timeeach time step step as a as uniform a valueuniform in space) value are in obtained space) are from obtained the Lucy from Island the Lucy marine Island weather marine station weather (Figure station5 b),(Figure operated 5b), by operated by Environment Canada. Lucy Island winds are more representative of over-water winds Environment Canada. Lucy Island winds are more representative of over-water winds for the entire for the entire region of study, compared with the overland Prince Rupert Airport winds. However, regionthis of would study, not compared produce witha substant the overlandial difference Prince in the Rupert deep flow Airport simulation winds. in However, this study. this would not produce aIn substantial the previous difference modeling in studies, the deep the flowwater simulation column in the inthis Brown study. Passage was assumed to be Inwell the mixed previous and modelinguniform, essentially studies, thebarotropic, water columnresulting in in the minimal Brown flows Passage at the was bottom, assumed with to be well mixedcurrent and directions uniform, as a essentially typical tidal barotropic, ellipse. In th resultingis study,in the minimal inputs to flows the 3D at theCOCIRM-SED bottom, with model current directionswere asmodified a typical by tidalintroducing ellipse. density In this study,stratificati theon inputs due to to the 3Dvertical COCIRM-SED changes of modelsalinity were modified(temperature by introducing effect is secondary) density stratification within the wate duer column. to the verticalThese data changes were derived of salinity from (temperatureCTD cast effectdata is secondary) acquired in within Brown thePassage, water as column. discussed These above. data The were October derived salinity from profiles CTD are cast selected data acquired for in Browninitializing Passage, the model as discussed run (horizontally above. The uniform) October and salinityto provide profiles the open are boundary selected conditions for initializing from the November to December 2014. The selection of the October salinity profiles, rather than March, is to model run (horizontally uniform) and to provide the open boundary conditions from November to incorporate the higher saline water and associated stronger stratification in the study area. DecemberThe 2014. following The selection boundary of conditions the October are salinityused. At profiles, lateral solid rather (or closed) than March, boundaries, is toincorporate the normal the higherflow, saline tangential water andstress, associated and normal stronger fluxes of stratification potential temperature in the study and area. salinity are set to zero (free Theslip followingand insulating boundary boundary conditions conditions). are used.Along At the lateral model solid open (or boundaries, closed) boundaries, the normal the flow, normal flow,temperature, tangential stress, and salinity and normal fields ar fluxese adjusted of potential using a temperaturemethod similar and to salinitythe adaptive are setopen to boundary zero (free slip and insulatingconditions. boundary It first uses conditions). an explicit Orlanski Along the radiation model opencondition boundaries, [18] to determine the normal whether flow, the temperature, open and salinityboundary fields is passive are adjusted (outward using propagation) a method or acti similarve (inward to the propagation). adaptive open If the boundary open boundary conditions. is It firstpassive, uses an the explicit model prognostic Orlanski radiationvariables are condition radiated [outward18] to determine to allow any whether perturbation the open generated boundary inside the model domain to propagate outward as freely as possible. If the open boundary is active, is passive (outward propagation) or active (inward propagation). If the open boundary is passive, the model variables (salinity) at the open boundary are nudged to the CTD profiles (October 2014) at the model prognostic variables are radiated outward to allow any perturbation generated inside the each sigma level with a relaxation time scale of 2 days updated as follows for each time step: model domain to propagate outward as freely as possible. If the open boundary is active, the model , , , , variables (salinity) at the open boundary𝑆 are𝑆 nudged ∆𝑡𝜖𝑆 to the𝑆 CTD , profiles (October 2014) at each(1) sigma level with a relaxation time scale of 2 days updated as follows for each time step:

i,k i,k î,k i,k St+1 = St + ∆te(St − St ), (1) J. Mar. Sci. Eng. 2018, 6, 117 13 of 21 where the hat denotes observed salinity, k is the layer number, k is the interface number at open boundaries, and ε is the relaxation time scale. At inner model grid points, relaxation is not to be performed, and the model predicted variables (salinity) are purely prognostic. It should be noted that although the model can prognostically simulate the dynamics introduced by the water stratification in Brown Passage, the variability of lower frequency (e.g., the seasonal î,k changes) is limited in the model, due to the referential salinity (St ) used in Equation 1 being set to be constant (in time) along the open boundaries. In order to reproduce the seasonal variability in the baroclinic fields, variable time series of stratification along the open boundaries needs to be applied; measurements of stratification at the open boundaries is not available, and so cannot be included in this preliminary numerical model study.

4.2. Model Performance A model run was carried out for Brown Passage and recently acquired ADCP/DVS current data were used for comparison. After a 3-day spin-up period (based on the development of total kinetic energy in the system) starting at rest, the model was integrated from 1 November to 31 December 2014. Model results were saved every 1.5 h for analysis. Table2 provides a summary of the modeled and observed ocean current speed statistics from 1 November to 31 December 2014, showing the percentile exceedance levels at 99%, 95%, 75%, 25%, and 5%. The model output agrees closely with the observations up to the 75% percentile. At the 95% percentile speed, the model underestimates the currents at 21 m depth by 0.06 m/s, but the unusually large currents at near-bottom depths of 181 m and 196 m are well modeled, being slightly overestimated by 0.04 m/s or greater. At the 99% percentile speed, the model signiﬁcantly underestimates the 21 m depth currents by 0.1 m/s but, again, the near-bottom currents at 196 m are within 0.03 m/s of the observed value. This demonstrates the model to be performing satisfactory for the purpose of this study, providing conservative results for the current speed estimates in the deeper portions of the water column.

Table 2. Summary of statistics for the modeled and observed current speeds for the maximum, median, and mean values from 1 November to 31 December 2014, showing the percentile exceedance levels. ) ◦

Depth Data (m) Net Direction ( Mean Speed (m/s) Median Speed (m/s) Maximum Speed (m/s) Vector Magnitude (m/s) 5th Percentile Speed (m/s) 99th Percentile Speed (m/s) 95th Percentile Speed (m/s) 75th Percentile Speed (m/s) 25th Percentile Speed (m/s)

OBS 0.64 0.19 0.21 0.54 0.42 0.28 0.12 0.06 0.04 122 21 MOD 0.52 0.17 0.19 0.44 0.36 0.24 0.12 0.06 0.07 170 OBS 0.58 0.13 0.16 0.51 0.35 0.21 0.09 0.03 0.07 119 77 MOD 0.43 0.14 0.16 0.39 0.30 0.21 0.10 0.04 0.08 174 OBS 0.55 0.13 0.15 0.40 0.32 0.21 0.09 0.03 0.08 141 133 MOD 0.50 0.10 0.14 0.42 0.35 0.19 0.07 0.03 0.08 157 OBS 0.52 0.12 0.14 0.42 0.33 0.19 0.08 0.03 0.05 83 181 MOD 0.55 0.12 0.15 0.48 0.41 0.23 0.07 0.03 0.08 108 OBS 0.66 0.12 0.16 0.57 0.42 0.21 0.08 0.03 0.08 44 196 MOD 0.63 0.13 0.17 0.54 0.46 0.26 0.07 0.03 0.09 89 J. Mar. Sci. Eng. 2018, 6, 117 14 of 21 J. Mar. Sci. Eng. 2018, 6, x 14 of 21

distribution as found by the barotropic run [2] as to the current speeds and directions (see Figure 6 First, the modeled and ADCP current results from surface to the middle depth at 21, 77, 133 m are and 7). The currents are typical of tidal channel flows, with flood flow directions ranging from 100 to examined (not shown here). Both the model and observed currents exhibited the similar distribution 150°, and ebb flow directions ranging from 250 to 300°. In the upper layers of the water column, the as found by the barotropic run [2] as to the current speeds and directions (see Figures6 and7). majority of current speeds are around 0.2 m/s, and there are only a few instances of flows above 0.3 The currents are typical of tidal channel flows, with flood flow directions ranging from 100 to 150◦, m/s. and ebb flow directions ranging from 250 to 300◦. In the upper layers of the water column, the majority In this study, we focus on investigating the strong baroclinic near-bottom flow regime. The of current speeds are around 0.2 m/s, and there are only a few instances of flows above 0.3 m/s. hourly modeled current fields were saved and extracted at the depths of 181 m and 196 m for In this study, we focus on investigating the strong baroclinic near-bottom flow regime. The hourly comparison. Time series of model-derived and observed current speeds and directions between 1 modeled current fields were saved and extracted at the depths of 181 m and 196 m for comparison. November and 31 December 2014 for the depth of 196 m are presented in Figure 13. The baroclinic Time series of model-derived and observed current speeds and directions between 1 November and model results for ocean currents near the seabed were found to be of similar magnitude to the strong 31 December 2014 for the depth of 196 m are presented in Figure 13. The baroclinic model results for observed currents, which is an important improvement from its previous barotropic version [2]. A ocean currents near the seabed were found to be of similar magnitude to the strong observed currents, statistical analysis of the baroclinic model results shows that the correlation coefficients between which is an important improvement from its previous barotropic version [2]. A statistical analysis of modeled and measured ADCP/DVS current speeds are somewhat weak (0.23) at 196 m. The weak the baroclinic model results shows that the correlation coefficients between modeled and measured correlation value is believed to be caused by the absence of variability of low frequency water density ADCP/DVS current speeds are somewhat weak (0.23) at 196 m. The weak correlation value is believed and subtidal currents through the open boundaries, which is not included in this qualitative study. to be caused by the absence of variability of low frequency water density and subtidal currents through For example, for the current speeds from 11 to 22 November, in which the model does not replicate the open boundaries, which is not included in this qualitative study. For example, for the current large near-bottom flows while, at other times, these large near-bottom flows are present in the model speeds from 11 to 22 November, in which the model does not replicate large near-bottom flows while, output. at other times, these large near-bottom flows are present in the model output.

FigureFigure 13.13. ModeledModeled andand measuredmeasured resultsresults locatedlocated atat thethe ADCP/DVSADCP/DVS oceanocean currentcurrent mooringmooring sitesite markedmarked inin FigureFigure8 8for for near-bottom near-bottom ocean ocean current current ( (aa)) speedsspeeds and and ( (bb)) directionsdirections at at the the depth depth of of 196 196 m.m.

FigureFigure 14 14 compares compares the the distribution distribution of model-derived of model-derived and observed and observed current speedscurrent and speeds directions and betweendirections 1 Novemberbetween 1 November and 31 December and 31 2014December for depths 2014 offor (a) depths 181 m of and (a) (b)181 196 m and m. Overall,(b) 196 m. the Overall, model resultsthe model follow results the observed follow the values observed and demonstratedvalues and demonstrated the two modes the in two the modes near-bottom in the ﬂownear-bottom regime. ◦ ◦ First,flow theregime. barotropic First, mode,the barotropic which is alongmode, the which isobath, is along with anthe orientation isobath, with of 120 an (ﬂooding)orientation and of 300120° (flooding) and 300° (ebbing). In this barotropic mode, near-bottom flood flow can reach 0.5 m/s at 181

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(ebbing).m and 196 In m, this which barotropic is stronger mode, than near-bottom the ebb flow. flood Second, flow can the reach newly 0.5 revealed m/s at 181baroclinic m and mode 196 m, is whichpointing is stronger to about than15° (down-slope, the ebb flow. see Second, Figure the 8) newlywhich revealedis associated baroclinic with the mode flood is flow. pointing The toreversed about ◦ 15up-slope(down-slope, flow (195°, see see Figure Figure8) which 8) is much is associated weaker, which with the indicates flood flow. that the The baroclinic reversed mode up-slope is mainly flow ◦ (195driven, see by Figure the flood8) is muchtides, weaker,i.e., the whichintrusion indicates of deep that higher the baroclinic saline water mode originating is mainly drivento the west by the of floodBrown tides, Passage i.e., the(i.e., intrusion Hecate Strait). of deep higher saline water originating to the west of Brown Passage (i.e., Hecate Strait).

Figure 14. Model results (blue dots) of near-bottom ocean current vectors between 1 November and Figure 14. Model results (blue dots) of near-bottom ocean current vectors between 1 November and 31 December 2014, compared with (a) ADCP data (red crosses) at 181 m and (b) DVS data (red crosses) 31 December 2014, compared with (a) ADCP data (red crosses) at 181 m and (b) DVS data (red crosses) at 196 m. at 196 m. Probability density functions of current speeds and directions derived from model results and observationsProbability between density 1 November functions andof current 31 December speeds 2014 and weredirections examined derived in Figure from model15. The results baroclinic and modelobservations well reproduced between 1 theNovember strong near-bottom and 31 December speeds, 2014 as wellwere as examined the primary in Figure directions. 15. The Only baroclinic slight variationsmodel well are reproduced noted between the strong the modeled near-bottom and observedspeeds, as near-bottom well as the primary currents. directions. At the near-bottom Only slight depthsvariations of 181 are and noted 196 between m, the model the modeled predicted and fewer obse mid-rangerved near-bottom currents betweencurrents. 0.1 At and the 0.2near-bottom m/s than indepths the observed of 181 and results. 196 m, The the percentage model predicted of currents fewer between mid-range 0.25 currents to 0.5 m/s between are slightly 0.1 and overestimated 0.2 m/s than (Figurein the observed 15a,b). Theresults. results The forpercentage the current of currents direction between comparison 0.25 to between 0.5 m/s are observed slightly andoverestimated modelled values(Figure are 15a,b). summarized The results in Figure for the 15 currentas well. dire Thection discrepancies comparison in thebetween modelled observed predictions and modelled are also generallyvalues are small. summarized As shown in inFigure Figure 15 15 asc,d, well. the The model discrepancies has slightly in less the frequent modelled northward predictions (330–360 are also◦ andgenerally 0–30◦ small.at 181 As m; shown 300–330 in◦ andFigure 0–30 15c,d,◦ at 196the model m) and has northeastward slightly less frequent near-bottom northward flows (50–110 (330–360°◦), butand overestimated 0–30° at 181 m; the 300–330° occurrence and of southeastward0–30° at 196 m) (110–170 and northeastward◦) near-bottom near-bottom flows. The modelflows predicted(50–110°), morebut overestimated northwestward the (250–310 occurrence◦) near-bottom of southeastw flowsard at the (110–170°) depth of 181near-bottom m (more typicallyflows. The tidal model with flowspredicted in opposite more northwestward direction) than (250–310°) the observations, near-bottom which flows can also at the be seendepth in of Figure 181 m14 (morea. typically tidalComparisons with flows in with opposite observations direction) for than the the same observations, period show which that the can model also be captured seen in Figure both the 14a. low frequencyComparisons and most with of the observations high frequency for the variability same period of theshow current that the speed model very captured well. For both the the lower low flowfrequency levels and relevant most to of the the application high frequency of modeling variability sediment of the transportcurrent speed andfate very from well. disposal For theat lower sea, theflow model levels has relevant the capacity to the application to generate of representative modeling sediment values transport and distributions and fate from of the disposal near-bottom at sea, currentsthe model for has speed the and capacity direction. to generate representative values and distributions of the near-bottom currents for speed and direction. 4.3. Discussion 4.3. Discussion To demonstrate the effect of the stratification on the deep flow in Brown Passage, a referential barotropicTo demonstrate simulation the for effect the exact of the same stratification period with on the the baroclinic deep flow model in Brown have Passage, been conducted, a referential by removingbarotropic the simulation salinity/density for the exact field fromsame the period modeled with variables.the baroclinic The differencemodel have of been the model-derived conducted, by near-bottomremoving the flow salinity/density was examined field in Figurefrom the 16 .modeled variables. The difference of the model-derived near-bottom flow was examined in Figure 16.

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FigureFigure 15.15. ProbabilityProbability densitydensity functionfunctionof of currentcurrentspeeds speeds( (aa,b,b)) andand directionsdirections ( (cc,d,d)) derivedderived fromfrom modelmodel resultsresults (blue(blue lines)lines) andand observationsobservations (red(red lines)lines) betweenbetween 11 NovemberNovember andand 3131 DecemberDecember 2014,2014, atat ((aa,,cc)) 181181 m m and and ( b(b,d,d)) 196 196 m. m. As shown in Figure 16a, the referential barotropic model demonstrated a typical tidal flow As shown in Figure 16a, the referential barotropic model demonstrated a typical tidal flow pattern in the near-bottom flow regime, aligned with the direction of the isobath. It did not reproduce pattern in the near-bottom flow regime, aligned with the direction of the isobath. It did not reproduce the strong northeastward down-slope flow as found in the baroclinic model results (~0.6 m/s). the strong northeastward down-slope flow as found in the baroclinic model results (~0.6 m/s). The The barotropic flow also exhibited much weaker flooding flow with directions ranging from 90◦ to 130◦. barotropic flow also exhibited much weaker flooding flow with directions ranging from 90° to 130°. The probability density functions of near-bottom current speeds at 196 m (Figure 16b) indicate that the The probability density functions of near-bottom current speeds at 196 m (Figure 16b) indicate that barotropic model currents has a relatively narrow speed range. The barotropic model underestimated the barotropic model currents has a relatively narrow speed range. The barotropic model the near-bottom currents with speeds greater than 0.4 m/s or less than 0.1 m/s, compared with underestimated the near-bottom currents with speeds greater than 0.4 m/s or less than 0.1 m/s, the baroclinic model. As to the directional distribution of currents, the barotropic model has less compared with the baroclinic model. As to the directional distribution of currents, the barotropic frequent northeastward (0–30◦) and southeastward near-bottom flows (100–150◦), but overestimated model has less frequent northeastward (0–30°) and southeastward near-bottom flows (100–150°), but the occurrence of northwestward (310–360◦) near-bottom flows (Figure 16c). overestimated the occurrence of northwestward (310–360°) near-bottom flows (Figure 16c). Within the two current direction modes of the near-bottom flow as discussed in earlier sections, Within the two current direction modes of the near-bottom flow as discussed in earlier sections, the strong northward velocity component is found to be the main indicator of the near-bottom the strong northward velocity component is found to be the main indicator of the near-bottom baroclinic mode (0–50◦). Spectral analysis has been carried out on current speeds from DVS baroclinic mode (0–50°). Spectral analysis has been carried out on current speeds from DVS observations and model results from November to December 2014 at the deepest measurement observations and model results from November to December 2014 at the deepest measurement level level of 196 m. The power spectral density of the current time series at 196 m has been calculated, of 196 m. The power spectral density of the current time series at 196 m has been calculated, and is and is shown in Figure 17. The model results are comparable to observations. The energy of the shown in Figure 17. The model results are comparable to observations. The energy of the baroclinic baroclinic near-bottom flow is found to be the largest at the semi-diurnal tidal frequency (2 cycles per near-bottom flow is found to be the largest at the semi-diurnal tidal frequency (2 cycles per day) in day) in both model results and observations. Hence, the strong near-bottom flow is believed to be both model results and observations. Hence, the strong near-bottom flow is believed to be baroclinic baroclinic semi-diurnal tidal currents (i.e. internal tides). semi-diurnal tidal currents (i.e. internal tides).

J. Mar. Sci. Eng. 2018, 6, 117 17 of 21 J. Mar.J. Mar. Sci. Sci. Eng. Eng. 2018 2018, 6,, x6 , x 17 17of of21 21

FigureFigure 16.16. 16. ((a) )( Model-derivedaModel-derived) Model-derived near-bottom near-bottom oceanoc eanocean current current vectors vectors at at 196 196 m m from from referentialreferential referential barotropicbarotropic barotropic modelmodel results results (red (red crosses), crosses), compared compared with with baroclinic baroclinic modelmodel model results results (blue(blue (blue dots) dots) between between 1 November 1 November andand 31Dec DecemberDec 31st 31st 2014. 2014. 2014. Associated Associated Associated probability probability probability density density function function of ofofcurrent currentcurrent speeds speeds speeds (b ( b)( )band and) and directions directions directions ( c )( c) derivedderived from from thethe the barotropicbarotropic barotropic (blue(blue (blue lines)lines) lines) andand and baroclinicbaroclin baroclinic modelmodelic model resultsresults results (red(red (redlines) lines) lines)are are are also also also compared. compared. compared.

Figure 17. Power spectral density of northward ﬂow component (m/s) of the near-bottom ﬂow at Figure 17. Power spectral density of northward flow component (m/s) of the near-bottom flow at 196 196Figure m derived 17. Power from modelspectral results density (blue of northward line) and observations. flow component (m/s) of the near-bottom flow at 196 m mderived derived from from model model results results (blue (blue line) line) and and observations. observations.

However,However, at atthe the very very low low frequencies frequencies of ofless less th anthan 0.2 0.2 cycles cycles per per day, day, the the model model underestimates underestimates thethe power power spectrum spectrum by by comparison comparison with with observatio observations,ns, although although the the total total power power at atthese these very very low low

J. Mar. Sci. Eng. 2018, 6, 117 18 of 21

J. Mar. Sci. Eng. 2018, 6, x 18 of 21 However, at the very low frequencies of less than 0.2 cycles per day, the model underestimates thefrequencies power spectrum is considerably by comparison less than with those observations, of the semi-diurnal although frequency the total power band. atThe these variability very low of frequencieslower frequency is considerably (e.g., the seasonal less than changes) those of theof the semi-diurnal stratification, frequency especially band. for Thethe higher variability salinity of lowerwater frequency intrusion from (e.g., the the west seasonal (e.g., changes)Hecate Strait), of the is stratification, not directly represented especially for via the the higheropen boundary salinity waterconditions intrusion of this from version the west of the (e.g., model. Hecate Strait), is not directly represented via the open boundary conditionsTo further of this investigate version of the the model. dynamics driving the semi-diurnal tidal currents, time series of densityTo further anomalies investigate (time mean the dynamics removed) driving measured the semi-diurnal by the near-bottom tidal currents, CTD unit time (Figure series of 9) density during anomaliesthe whole (time measurement mean removed) program measured (later October by the near-bottom 2014 to early CTD March unit (Figure2015) is9) duringfiltered thewithin whole the measurementfrequency band program related (later to the October 9–15 h 2014 period to early(frequen Marchcy band 2015) covering is filtered the within semi-diurnal the frequency variations), band relatedas shown to thein Figure 9–15 h18. period It is clear (frequency that there band are coveringlow frequency the semi-diurnal variations of variations), bottom density, as shown which in is Figureassociated 18. It with is clear the that higher there saline are low water frequency intrusion variations from Hecate of bottom Strait. density, It is found which that is the associated semi-diurnal with thebaroclinic higher saline tides, wateras demonstrated intrusion from by the Hecate large Strait. amplitudes It is found of the that band the semi-diurnalfiltered density baroclinic anomalies, tides, is asdriven demonstrated by the low by frequency the large amplitudeshigh saline water of the intr bandusion filtered as seen density in the anomalies, November is and driven December by the low2014 frequencyperiod. high saline water intrusion as seen in the November and December 2014 period.

FigureFigure 18. 18.Time Time series series of of density density (Rho, (Rho, blue blue line) line) anomalies anomalies measured measured by by the the near-bottom near-bottom CTD CTD unit. unit. TheThe red red line line is is the the band band (9–15 (9–15 h) h) ﬁltered filtered result. result. With the higher salinity and more dense water intrusion in Brown Passage, there is the potential With the higher salinity and more dense water intrusion in Brown Passage, there is the potential for the semi-diurnal tidal currents to initiate internal waves/tides within the water column along the for the semi-diurnal tidal currents to initiate internal waves/tides within the water column along the bottom bathymetry where incident angles or seabed slopes near the critical angle. The Brunt–Väisälä bottom bathymetry where incident angles or seabed slopes near the critical angle. The Brunt–Väisälä frequency gives an initial insight into the possibility of creating internal waves/tides. The forcing of frequency gives an initial insight into the possibility of creating internal waves/tides. The forcing of the barotropic tide is also strong enough in Brown Passage to generate such internal tides so that the the barotropic tide is also strong enough in Brown Passage to generate such internal tides so that the M2 tidal constituent can be intensiﬁed as shown in both the observed and modeled bottom currents. M2 tidal constituent can be intensified as shown in both the observed and modeled bottom currents. To better understand the dynamics of the internal tides, additional analysis requiring more extensive To better understand the dynamics of the internal tides, additional analysis requiring more extensive observational data sets are required. observational data sets are required.

J. Mar. Sci. Eng. 2018, 6, 117 19 of 21

5. Summary and Conclusions Brown Passage is a deep (up to 200 m) ocean channel connecting the western offshore waters of Hecate Strait on the Pacific continental shelf with the eastern inland waters of Chatham Sound in Northern British Columbia, Canada. Recent research into this oceanic environment is motivated by studies of the possible use of this area for disposal at sea of dredged sediments arising from expansion of marine terminals in and around Prince Rupert Harbor in Chatham Sound. The ocean currents in Chatham Sound are highly variable due to a combination of forcing by the large tides within this area, winds, and large freshwater discharges from the Skeena and Nass Rivers. Chatham Sea is characterized by lower salinity near-surface waters on its eastern side due to the Skeena River inflow to Southern Chatham Sound [1]. More saline waters present on the western side of Chatham Sound result from the exchange through Brown Passage and other connecting channels with the higher salinity waters of Hecate Strait. A high-resolution 3D finite difference hydrodynamic model (COCIRM-SED) was developed to determine the tidal and wind-driven currents of this area [2], and then used to simulate the transport and deposition of sediments released from activities involving disposal at sea. The model results for ocean currents were found to be comparable with the two sets of ocean current observations at 15 and 98 m available for Brown Passage, obtained in 1991. Based on these results, Brown Passage was thought to be generally well mixed through the middle and lower parts of the water column. The first modern oceanographic measurement program carried out to directly determine the near-bottom currents raised questions about the adequacy of the model results for the near-bottom currents in Brown Passage. Using moored bottom instruments operated from October 2014 to April 2015, near-bottom ocean currents at 3.5 m height above seabed were measured, as well as ADCP/DVS-derived current profile data for currents throughout the full water column. CTD profile measurements were also obtained during the deployment and recovery of the bottom-mounted instruments. The measured near-bottom currents were found to be considerably higher than the previous model-derived near-bottom currents. As a result, the COCIRM-SED model was modified and rerun, with the most important change being the use of the observed October 2014 water column density profile in place of the previous barotropic modeling approach. This change led to considerable improvements in the ability of the model to generate episodes of relatively strong currents in the bottom layers, which are shown to be in reasonably good agreement for the near-bottom and deeper ocean currents with the 2014–2015 measurement program, (the 99th percentile current speed can reach 40 cm/s at 181 m depth and 53 cm/s at 196 m water depth). The inclusion of the resulting density stratification effects to previous oceanographic and sediment transport modeling [2] has improved the ability of the model to generate more realistic near-bottom currents, as shown by the comparison with observed currents at 181 m and 196 m. The power spectral density of the ocean currents has been calculated, and it is found that the energy of the baroclinic near-bottom flow is dominated by the semi-diurnal tidal frequency (2 cycles per day) in both model results and observations. Hence, the strong near-bottom flow is believed to be baroclinic semi-diurnal tidal currents (internal tides). It is suggested that the semi-diurnal baroclinic tides are influenced by the low frequency variations of the higher salinity/density water intrusions from Hecate Strait. The detailed mechanisms for generation of semi-diurnal internal tides within the study area requires additional analysis to identify potential source regions where the bathymetric bottom slope matches the vertical ocean density gradient in the form of the Brunt–Väisälä frequency. This finding is scientifically important to direct further numerical studies on the sediment resuspension from disposal at sea operations [19]. As indicated in Figure 17 (less than 0.2 cycles per day part), it should be noted that although the baroclinic model developed in this study can prognostically simulate the dynamics introduced by the water stratification in Brown Passage, the variability of lower frequency (e.g., the seasonal changes) of the stratification especially for the higher salinity water intrusion from the west (e.g., Hecate Strait) is not directly represented at the open boundary of the model. Beyond this qualitative study, the large-scale intrusions of higher density water entering Brown Passage need to be better represented J. Mar. Sci. Eng. 2018, 6, 117 20 of 21 in the baroclinic model, especially for the low frequency variations. Future work will require an expanded model domain to cover not only Brown Passage, but also the outer shelf waters of Hecate Strait and Dixon Entrance. A larger model domain would incorporate the low frequency variability of the higher salinity water intrusion into Brown Passage, which could be related to underlying physical mechanisms, such as remote wind fording. An unstructured grid model is proposed for the future numerical modeling study to allow detailed representation of the complex small-scale bathymetric features of Brown Passage while operating with a manageable number of total grid elements over the much expanded model domain, so as to keep the computational requirements for the model to manageable levels.

Author Contributions: The individual contributions of authors to this article consist of: Conceptualization, Y.L. and D.B.F.; Data Collection and its Preliminary Analysis, T.M. and K.B.; Model Development and Validation, Y.L. and D.B.F.; Formal Analysis, Y.L.; Writing—Original Draft Preparation, Y.L.; Writing—Review & Editing, D.B.F.; Project Administration, D.B.F. and T.M. Funding: The research presented in this article received no external funding. The 2014–2015 oceanographic measurements made in Brown Passage were funded by Pacific North West LNG through a contract between ASL Environmental Sciences Inc. and Stantec Consulting Ltd. Acknowledgments: The assistance of ASL Environmental Sciences Inc. personnel, James Bartlett, Matthew Stone, Ryan Clouston, and Jeremy Lawrence, who contributed to the collection and preliminary processing of the oceanographic data, is acknowledged. We also acknowledge the contributions of Jianhua Jiang, formerly at ASL and presently at Alberta Energy Regulator (AER) to the early model development. Conflicts of Interest: The authors declare no conflict of interest.

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