Quantitative Description of Particle Dispersal over Irregular Coastlines

Tim Chaffey, Satoshi Mitarai, Dave Siegel

BACKGROUND• Topographic eddies may be important in determining habitat

connectivity– Eddies can retain larvae for time scales comparable with their PLD

• High local recruitment is observed in island wake eddies (e.g., Swearer et al, 1999)– But, such clear pattern will not be observed in coastal eddies where

currents are less persistent in direction (Graham & Largier, 1997) • Filament formation may be important in offshore transport of larvae

(Haidvogel, 1991)– Offshore filaments present an obstacle to nearshore settlement in

PLD. • Few notable studies (Largier, 2003)

– Geostrophic size & flow time scale considered

QuickTime™ and aCinepak decompressor

are needed to see this picture.

GOAL OF THIS STUDY• Use coastal 3-D physical model to investigate the wind driven circulation around

idealized irregularities in the coastline.• Estimate the role of coastal headland eddies on larval dispersal using idealized

ROMS simulations– Do headlands create a consistent connectivity or a stochastic connectivity? – Are the spatial scales of settlement similar to the straight coastline case (50

km)?– If there is a consistent connectivity, does it remain constant under different

wind regimes?– Is there a critical headland amplitude/width?– How important is headland spacing?– Describe the physics of filament formation and eddy recirculation around

headlands?• Can we develop theoretical relationships between headland size, wind forcing,

bathymetry and release-settlement relationship?– If we can develop theory, we can use this theory to predict release-settlement

relationships over realistic coastlines given wind, headland size, and bathymetry.

How this all comes together

1 - Collect CalCOFI data (SSH, temperature), bathymetry data, wind data from buoys.

2 - Initialized three-dimensional coastal circulation model (ROMS) with above data.

3 - Use 3D flow, 3D temperature, and SSH from model to compute flow statistics offline (Matlab).

4 - Use 3D flow from model to track particles offline (Matlab). We have ultimate flexibility in how we manipulate particles.

Model Setup • Wind field from buoy measurements

– Wind field sum of a mean and perturbation component

– July wind field (upwelling period)• Pressure gradient quantified using dynamic

height data from CalCOFI July ship track survey. – Pressure gradient rotated to along the coast

line inside the 500 m isobath Domain: 288 km Cross-shore, 256 km Alongshore

• Bathymetry - 0 m to 500 m offshore• Irregular coastline (headland) created using a

Gaussian function

HEADLAND DESIGN• Gaussian-shape headland in idealized

simulations– Three parameters

2. Width (w)(twice the std of Gaussian function)

1. Amplitude (a)

3. Domain size (d) = distance between headlands

a = 20 kmw = 20 kmd = 256 km

Variable Model Parameters

• Wind Field– Uniform - Wind field principal axis has uniform (N-S) direction over

domain– Alongshore - Wind field principal axis rotated to follow land inside

500 m isobath

• Pressure Gradient– Alongshore - Pressure gradient principal axis rotated to follow

land inside 500 m isobath

• Bathymetry – Compression - Distance from land to 500 m isobath compresses

near headland– Alongshore- Distance from land to 500 m isobath same at all

points.

Wind Field Rotation

Bathymetry - Compression of Isobaths at Headland

Bathymetry - Non-Compression of Isobaths at Headland

Notation for Cases Tested

BA - WUBA - WAAlongshore

BC - WUBC - WACompression

UniformAlongshore

Wind

Bathymetry

Particle Tracking

• 90,000 particles randomly released 10 km from land and in the upper 10 m, but with a uniform release distribution over 90 days.

• Particles locations updated every three hours.• Particles settle when within competency

window and 10 km of land.• Particles are treated as packets that can settle

multiple times.• Particle bouncing schemes vary

– Reflecting - particles are reflected off boundary – Non-reflecting - particles entering land are returned

to prior time step over water

Model Parameters

BA - WUBA - WAAlongshore

BC - WUBC - WACompression

UniformAlongshore

Wind

Bathymetry

Connectivity, Reflecting Condition (∆t = 3 hr)

BA-WA(1) BA-WA(2) BA-WA(3) Mean

Arrival Diagram - Reflecting Condition

BA-WA(1)

BA-WA(2)

BA-WA(3)

Settler Dispersal Kernel - Reflecting Condition

BA-WA(1) BA-WA(2) BA-WA(3) Mean

Connectivity, Non - Reflecting Condition (∆t = 3 hr)

BA-WA(1) BA-WA(2) BA-WA(3) Mean

Arrival Diagram - Non -Reflecting Condition

BA-WA(1)

BA-WA(2)

BA-WA(3)

Settler Dispersal Kernel - Non - Reflecting Condition

BA-WA(1) BA-WA(2) BA-WA(3) Mean

Nearshore Flow Structure BA-WA

Model Parameters

BA - WUBA - WAAlongshore

BC - WUBC - WACompression

UniformAlongshore

Wind

Bathymetry

Connectivity, Reflecting Condition (∆t = 3 hr)

BC - WU(1) BC - WU (2)

Arrival Diagram - Reflecting Condition

BC-WU (1)

BC-WU (2)

Settler Dispersal Kernel - Reflecting Condition

BC - WU(1) BC - WU (2)

Connectivity, Non-Reflecting Condition (∆t = 3 hr)

BC - WU(1) BC - WU (2)

Arrival Diagram - Non -Reflecting Condition

BC-WU (1)

BC-WU (2)

Settler Dispersal Kernel - Non-Reflecting Condition

BC - WU(1) BC - WU (2)

Nearshore Flow Structure BC-WU

Summary• Dispersal for the alongshore wind cases are

realistic while uniform wind cases are artificial.• For uniform wind cases, nearshore irregularities

in the flow create artificial particle accumulation on the wayward side of the headland

• A semi-annual pattern of dispersal is present in the alongshore wind case for both bathymetrys and both bouncing schemes.

• For alongshore wind cases, particle dispersal over 1.5 years has a uniform distribution.

Future Work• Experiment with alternative bouncing scheme to remove

artificial accumulation of particles• Compare time integrated temperature fields to CALCOFI

data to validate simulations• Investigate vertical velocity at fixed depth and mixed

layer depth to theoretical predications to validate simulations

• Collaborate with Bernardo Broitman (NCEAS) to assess the variation of isobathic distances with coastline

• Bridge the connections between headland size, flow structure, and dispersal. Time scales will be important!

Model Parameters

BA - WUBA - WAAlongshore

BC - WUBC - WACompression

UniformAlongshore

Wind

Bathymetry

Connectivity, Reflecting Condition (∆t = 3 hr)

BC-WA(1) BC-WA(2) BC-WA(3) Mean

Arrival Diagram - Reflecting Condition

BC-WA(1)

BC-WA(2)

BC-WA(3)

Settler Dispersal Kernel - Reflecting Condition

BC-WA(1) BC-WA(2) BC-WA(3) Mean

Connectivity, Non-Reflecting Condition (∆t = 3 hr)

BC-WA(1) BC-WA(2) BC-WA(3) Mean

Arrival Diagram - Non - Reflecting Condition

BC-WA(1)

BC-WA(2)

BC-WA(3)

Settler Dispersal Kernel - Non - Reflecting Condition

BC-WA(1) BC-WA(2) BC-WA(3) Mean

Nearshore Flow Structure

Mean Dispersal Statistics

• Mean alongshore distance - 35.9 km

• Standard deviation of alongshore - 56.1 km

• 11.5 % particles settle at least once

• Mean PLD of settling particles 25.2 days (competency window = 20 - 40 days)