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  • MODELLING THE IMPACT OF FINFISH AQUACULTURE ON SEDIMENT

    BIOGEOCHEMISTRY Daniele Brigolin, University of Venice

    ECEM 2007, Trieste November 27-30

    Pastres Roberto University of Venice, Italy

    EU FP6 ECASA project www.ecasa.org.uk

    Chris Cromey, T.D. Nickell SAMS, Oban, Scotland (UK)

    D.R. Aguilera, Pierre Regnier University of Utrecht, The Netherlands

  • Outline

    • Impacts of finfish farming on the sediment geochemistry;

    • Description of the model;

    • Study site and field data description;

    • Results of model calibration;

    • Response of model output to the establishment of a new salmon farm;

    • Perspectives.

  • Finfish farming impacts on the sediment

    Potential impacts on the sediment (e.g. Hargrave et al., 1997; Pearson & Black, 2000)

    currents

    Wasted food

    sedimentation

    burial

    Oxic and anoxic mineralization

    Faeces

    S=, NH4+, DIP

     Increase in the superficial OC concentration

     Decrease of the oxygen penetration depth

     Increase in dissolved nutrient concentrations

     Increase in S= concentrations

     Changes in macrofaunal community

    Changes in the fluxes at the sediment-water interface

    Changes in the chemical properties of the sediments provide a measure of the impact caused by the fish farm which is integrated over time.

    Benthic impacts are proportional to:

    Exposure of the site (currents);

    Husbandry practices (feeding strategy and quality of the food)

  • Modelling the impacts of finfish farming on the sediments

    OC flux reaching the sediment-water interface

    Biotic indexes (ITI, AMBI)

    Simple geochemical indicators (TOC)

    Current approach

    OC flux reaching the sediment-water interface

    Ecological indexes

    Approach proposed in this work

    More complex geochemical indicators (e.g. NH4+, S=, O2..)

  • Conceptual model: Deposition + Early diagenesis

    WATER COLUMN

    Food wastage and Faeces production

    Deposition model (DEPOMODTM)

    Organic carbon flux

    Current velocity

    O2 demand, nutrient fluxes

    EDM: Early Diagenetic ModelEDM: Early Diagenetic Model (developed in BRNS(developed in BRNSTM TM environment)environment)

    Sediment temperatureSEDIMENT

    DEPOMOD – particle tracking model (Cromey et al., 2002 Aquaculture)

    (validated for Scottish sealochs)

  • Objectives of this work

    1) evaluating the applicability of a Reactive-Transport Model of early diagenesis (EDM) in combination with the DEPOMOD;

    2) testing DEPOMOD+EDM integrated model at sites which are exposed to high organic carbon fluxes from aquaculture activities, under transient conditions.

    The potential use of the integrated model is discussed in relation to benthic biogeochemical indicators for cost- effective EIA and monitoring practices.

  • Surficial sediment

    layer

    Deep sediment layer

    Water column

    Temp. Fluxes:

    OC, Fe(III), Mn(IV)

    Lower boundary condition: null gradient

    t: time z: depth ΣR variation in the concentration due to biogeochemical processes DB diffusion coefficient ω : sedimentation rate φ: sediment porosity.

    The modeller specifies the fluxes at the upper boundary for the solid species, and the concentrations for the dissolved speciesConcentr.:

    O2, NH4+, HPO42-, NO3-, SO42-, Mn2+, Fe2+

    ( ) ( ) ( ) ( )( )t,,CR z CD

    zz C

    t C

    s sBss βϕϕωϕϕ −+

      

    ∂ −∂

    ∂ ∂+

    ∂ −∂−=

    ∂ −∂ 1111

    ( ) ( )t,,CR z

    Cln/D z CD

    zz C

    t C

    w wmwBww βϕϕϕϕϕ ωϕ +

      

     ∂ −∂+

    ∂ ∂

    ∂ ∂+

    ∂ ∂−=

    ∂ ∂ 21

    Organic matter degradation and early diagenesis processes: conceptual model

  • Surficial sediment

    layer

    Deep sediment layer

    Water column

    Temp. Fluxes:

    OC, Fe(III), Mn(IV)

    Lower boundary condition: null gradient

    t: time z: depth ΣR variation in the concentration due to biogeochemical processes DB diffusion coefficient ω : sedimentation rate φ: sediment porosity.

    The modeller specifies the fluxes at the upper boundary for the solid species, and the concentrations for the dissolved speciesConcentr.:

    O2, NH4+, HPO42-, NO3-, SO42-, Mn2+, Fe2+

    ( ) ( ) ( ) ( )( )t,,CR z CD

    zz C

    t C

    s sBss βϕϕωϕϕ −+

      

    ∂ −∂

    ∂ ∂+

    ∂ −∂−=

    ∂ −∂ 1111

    ( ) ( )t,,CR z

    Cln/D z CD

    zz C

    t C

    w wmwBww βϕϕϕϕϕ ωϕ +

      

     ∂ −∂+

    ∂ ∂

    ∂ ∂+

    ∂ ∂−=

    ∂ ∂ 21

    Organic matter degradation and early diagenesis processes: conceptual model

    Operator splitting method Implicit Numerical scheme

    Regnier et al. (2002) Appl. Math. Model.

  • Organic Matter

    Organic matter Degradation

    redox reactions

    Electron acceptors: O2, NO3-, Fe(III) Mn(IV), SO42-

    Re-oxidation reactions

    Reduced compounds Fe2+, Mn2+, NH4+, S=

    Electron acceptors O2, Fe(III),

    Mn(IV)

    FeS & Carbonates Precipitations

    Carbonates equilibria

    Fluxes of NH4+, O2, DIP

    BRNS Early diagenesis model Reaction network: Primary & Secondary reactions

    Sediment Water Interface

  • A purposely-designed field campaign was carried out in August 2006, in order to apply the integrated model

    The fish-farm was moved to the actual site in Feb 2006

    Study site – Loch Creran, West coast of Scotland

  • Study site – Loch Creran, West coast of Scotland

    3 stations : 10m and 40m from the cages, and control;

    3 replicates per station using a megacorer (Φ =100 mm);

    Analysis were performed at each 1 cm on the top 10 cm + surnatant waters.

    Parameters sampled:

    - Porosity; - Organic Carbon in the sediment; - Fe2+ and Mn2+ in pore waters; - NH4+ and HPO42- in pore waters; - SO42- in pore waters.

  • Application of the model at Loch Creran - methodology

    Step 1: the Early Diagenesis Model (EDM) was calibrated, by comparing the steady-state model outputs with the field data collected at station BC (control);

    Step 2: the DEPOMOD was run, in order to obtain a prediction of the farm originated Organic Carbon flux at stations B10 and B40;

    Step 3: organic carbon fluxes predicted by DEPOMOD are added to the background OC fluxes, moving the EDM from a steady-state to a transient-state;

    Step 4: transient profiles predicted by the model are compared with a set of sediment chemistry data purposely collected at stations B10 and B40.

  • Step 1, results: EDM calibration – station Bc

    - All the parameters of the model were fixed on the basis of literature references;

    - The fluxes of solids OC, Fe(III) and Mn(IV) at the upper boundary were calibrated by minimizing a goal function which quantifies the deviation between model predictions and field data.

    0 1 2 3 4 OC [%]

    0

    5

    10

    de pt

    h [c

    m ]

    a

    0 100 200 300 400 NH+4 [µ mol L-1]

    0

    5

    10

    de pt

    h [c

    m ]

    b

    0 40 80 DIP [µ mol L

    -1]

    0

    5

    10

    de pt

    h [c

    m ]

    c

    0 20 40 SO4 [mmol L-1]

    0

    5

    10

    de pt

    h [c

    m ]

    d

    0 40 80 120 160 200 Fe2+ [µ mol L-1]

    0

    5

    10

    de pt

    h [c

    m ]

    e

    0 40 80 120 Mn2+ [µ mol L-1]

    0

    5

    10

    de pt

    h [c

    m ]

    f

  • Step 2: DEPOMOD output – organic carbon flux at the S.W.I.

    500

    1000

    1500

    2000

    Salmon cages Sampling stations

    g C m-2 yr-1

    B40 B10

    50m

    50 m 500

    1000

    1500

    2000

    Salmon cages Sampling stations

    g C m-2 yr-1

    B40 B10

    500

    1000

    1500

    2000

    Salmon cages Sampling stations

    g C m-2 yr-1

    B40 B10

    50m

    50 m

    At the time of the survey, the fish-farm has been operating for 6 months.

    Production: 1500 tonn y-1

    6 x 22m Φ circular net cages reaching 14m depth

    5% of feed waste was assumed;

    Farm details:

  • Step 3: EDM transient simulation

    OC (food+faeces) flux at Station B10

    Depomod output

    These fluxes were added on the top of the background OC flux, which was estimated by calibrating the EDM.

    This additional OC flux was imposed for 6 months (age of the farm), perturbing the steady-state profiles and driving the model to a transient-state.

  • Step 4. EDM model output vs field data at station B10

    - Due to the mineralization of elevated quantities of fish farm-derived labile organic matter, nutrient concentrations at station B10 are greatly enhanced compared with the non-impacted station BC, reaching valu

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