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To the Formation of Ichthyoplankton Assemblages Along the Eastern English Channel French Coast: Numerical Approach

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Title: To the Formation of Ichthyoplankton Assemblages Along the Eastern English Channel French Coast: Numerical Approach


1
To the Formation of Ichthyoplankton Assemblages
Along the Eastern English Channel French Coast
Numerical Approach
  • Alexei Senchev
  • UMR 8013 ELICO
  • Université du Littoral - Côte d'Opale
  • Wimereux, France
  • alexei.sentchev_at_mren2.univ-littoral.fr

Konstantin Korotenko P.P. Shirshov Institute of
Oceanology Moscow, Russia kkoroten_at_hotmail.com
2
Acknowledgement
A. Grioche, X. Harlay, P. Koubbi UMR 8013
ELICO Ichtyoécologie Marine Université du
Littoral - Côte d'Opale Wimereux, France
3
Outline
  • Motivation
  • Biological and hydrological situations
  • Problem definition
  • Model description
  • Numerical experiments
  • Particle and larvae migration
  • Conclusions

4
Motivation
  • Environmental problems caused by the increase of
    pollutant discharge into natural waters require
    complex studies of physical processes of mixing
    and dilution, biological and mathematical
    modeling, data acquisition via remote sensing and
    in situ measurements. In this context,
    development of a multi-functional
    hydrodynamic/transport model which allows to
    perform fully prognostic computations of coastal
    water circulation and it application to
    environmental problems is an important task.

5
Region
  • Strong tidal and storm activity
  • Complex bottom topography
  • Important river discharge
  • Zones
  • Offshore
  • Near-shore
  • Dover Strait
  • Hydrological front

6
Hydrological situation
Surface salinity April 11-13, 1995
Surface salinity Mai 2-5, 1995
Temperature profiles (April, 11-13)
Salinity profiles
7
Biological situation
Pleuronectes flesus larvae distribution for each
development stage and survey (Ind. / 100 m3.
Normalized) (Grioche, Koubbi, Sautour, 1997)
Initial conditions Eggs (April, 11-13)
Larvae stage 2 (one week later)
Larvae stage 3 (two weeks later)
Larvae stage 3 (tree weeks later Mai, 3-6)
8
Biological situationPleuronectes flesus larval
transfer fromthe spawning grounds to the
nurseries
9
Problem
How strong is the influence of hydrodynamics on
the larvae migration? Can we identify
relationships between tidal motions, wind forcing
and P.flesus larvae drift?
Method
Numerical modeling
10
Tracer
11
Approach
  • Combined use of
  • 2D finite element tidal model
  • 3D Princeton Ocean Model
  • Particle transport model

12
Particle transport model
(Korotenko, JMS, 1999)
Input velocity diffusivity coefficients water
density
Method random walk in the horizontal random
buoyancy in the vertical
Output 3D particle displacement
13
Circulation model
  • Princeton Ocean Model (POM)
  • Blumberg, Melor (1977-87), Mellor (1996)
  • 3-D
  • Primitive equation, time-dependent
  • Sigma coordinate
  • Prognostic temperature and salinity fields
  • Free surface
  • k-kl turbulent closure scheme
  • 2?2 km regular grid
  • Real bottom topography
  • Forcing
  • Tidal forcing
  • Wind forcing
  • Fresh water discharge

14
Data assimilation
Assimilation technique
Tidal Model
  • Finite-Element Tidal Model
  • (Le Provost, Poncet, IJNME, 1978)
  • 2D
  • Spectral
  • Barotropic shallow water equation
  • Quadratic parameterisation of bottom friction
  • Depth depended grid ranging from 0.5 to 5 km
  • Real bottom topography
  • Tidal forcing at the open boundaries
  • Numerical solution for individual tidal
    constituents

Augmented Lagrangian function method (Sentchev,
Yaremchuk, CSR, 1999) Observations 13 sea
level observations 1039 tidal current velocity
ellipses Control variables 65 boundary
conditions Results Optimized boundary
conditions for individual tidal constituents
15
Numerical experiments
Surface salinity
Salinity at 5 m
Sea surface elevation and surface velocity after
10 days run
16
Features of Tidal Turbulence
  • 1. Bottom-friction-generated
  • 2. Spatial and temporal inhomogenuity
  • 3. Strong horizontal intermittency along the
    French coast
  • 4. Suppressed in river discharging areas

17
Concentration Evolution
Spatial distribution of particles as a function
of time (0, 1, 2, 3 weeks ) expressed in terms of
concentration (nb. of particles in a unit
column) The implemented complex numerical
approach allowed predicting larvae assemblage in
the Eastern English Channel
18
Conclusions
  • I. A use of the coupled flow/transport
    modeling is a powerful tool to study tracer
    dispersion.
  • II. Numerical experiments conducted in the
    eastern English Channel revealed the following
    features of tracer dynamics
  • ? The joint effect of tidal motions and river
    discharge gives rise to local concentrations of
    particles in the frontal zone. Particles -
    initially homogeneously distributed .
  • ? Turbulent diffusion is the second factor
    contributing to particle concentration in the
    vicinity of the front. In areas with low
    turbulence, suppressed by fresh water discharge,
    vertical mixing is considerably reduced.
    Particles continue to move in the upper layer and
    are blocked by the fresh water discharge in
    their movement toward the French coast.
  • ? Effect of the bottom topography on the
    tracer dynamics has been recognized.
  • III. Experiments with particles representing
    P.flesus larvae provided the following results
  • ? The coupled flow/transport model reproduced
    the major features of the larvae migration under
    the influence of different forcing terms.
  • ? Combined effect of tidal motions (M2
    constituent) and river discharge creates
    favorable conditions for larvae drift toward the
    French coast. Introducing of the mean sea level
    and more tidal constituents generates a steady
    larvae drift to the North along the coast.
  • IV. Residence times of water for three specific
    zones were estimated for the case without wind
    forcing. There were found to be equal to 5
    days for waters in the Strait of Dover 7 days
    for offshore waters 14 days for near-shore
    waters. Wind events can affect these
    estimations.
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