ECASA modelling workshop, Dunstaffnage Laboratory, Oban 26-27 January 2006 14 – University of Venice

ECASA modelling workshop, Dunstaffnage Laboratory, Oban

26-27 January 2006

14 – University of Venice

outline

1) BRNS (sediment remineralization) model;

2) Tapes philippinarum model;

3) Sparus aurata model;

4) Off-shore mussel farming in the Adriatic sea ecological model;

BRNS: Biogeochemical Reaction Network Simulator (Regnier et al., 2002)

Biogeochemical reactions:1. degradation of the organic matter;2. re-oxidation of the degradation product;3. acid-base equilibria;4. precipitation and dissolution processes.

Model description

Transport processes:1. Advection;2. Diffusion (including bioturbation).

Model designed for local scale (A)

t)β,,f(z

Dz

vt 2

2

cccc

Deep sediment

Surficial sediment

Water columnTempOC flux

Model description – governing equation

State of implementation

A WEB interface automatically generates the FORTRAN code (.exe version available) RTM group Utrecht University (NL).

Model parameters:1. Reaction-specific parameters (e.g. reaction rate coefficients, apparent equilibrium constants & limiting concentrations of electron acceptors);

2. Site-specific parameters (parameters characterizing the depositional environment).

Two factors determine the succession of degradation processes:1. The ΔG0

W of the different processes;2. The concentration of electron acceptors.

On this basis, 4 different microbial-mediated processes were selected for the Venice lagoon environment:1. Aerobic degradation;2. Nitrate reduction;3. Sulphate reduction.

Model application to the Venice lagoon **

State of implementation – Venice lagoon

** PhD thesis Antonio Petrizzo, University of Venice


name phase

Organic matter conc. solid

Oxygen conc. liquid

Nitrate conc. liquid

Sulphate conc. liquid

Ammonia conc. liquid

Phosphates conc. liquid

Sulphides conc. liquid

Carbonates conc. liquid

pH liquid

Adsorbed ammonia conc. solid

Adsorbed phosphates conc. solid

Selected state variables for the Venice lagoon environment

St. 2B

St. 9B


Available field data: Sediment profiles in stations 2B and 9B, June and November 2001 (ARTISTA MAV-CVN, 2003).

Initial conditions: measured profiles in June 2001Concentrations of adsorbed ammonia and phosphate were recalculated from experimental data, using the respective partition equilibrium constants.

Boundary conditions: 1. Upper boundary: water quality data at the sediment-water interface were collected nearby st. 2B and 9B from MAV-CVN, within the MELa1 monitoring program.Organic matter flux to the sediment was estimated from the TOC data.2. Lower boundary:A null gradient condition was imposed


Model calibration:

Two site-specific parameters were estimated:

Organic matter degradation rate;

Bioturbation coefficient.

Remaining parameters were determined according to

Van Cappellen and Wang (1996) and Boudreau (1996).


A simplex algorithm was implemented, in order to find the minimum of the cost function,

2~

, ,

( )( )

x t j

y y pOF p

j = Ammonia, Phosphates, Organic Carbon concentrations

Venice lagoon – preliminary results, model calibration

KO2

Organic matter degradation constant

1.8 y-1 St.9B

2.0 y-1 (Van Cappellen and Wang, 1996)

Db0Bioturbation coefficient

15.2 cm2 y-1 St. 9B

0.5 - 18 cm2 y-1 (CVN, 2000)

Venice lagoon – preliminary results

Corg

%

cm

1 .2 1.4 1.6 1.8 2.0

1

3

5

7

9

11

13

15

N-NH4

mgN/l

cm

0 3 6 9 12 15

1

3

5

7

9

11

13

15

P-PO 4

mgP/l

cm

0 2 4 6 8 10

1

3

5

7

9

11

13

15

I.C . M O D Novem bre O BS N ovem bre

station9B

0

(0)dC

F Ddz

Estimation of fluxes at the interface

Nitrate

Ammonia Phosphate

N itra to - S taz . B 9

mg-N

/m2 /d

giu nov-80

-60

-40

-20

0

20

40 A RT M od

A m m o n io - S ta z . B 9

mg-N

/m2 /d

giu nov-50

0

50

100

150

200

250 A RT M od Fo sfa to - S taz . B 9

mg-P

/m2 /d

giu nov0

3

6

9

12

15 A RT M od

station9B

outline

1) BRNS (sediment remineralization) model;

2) Tapes philippinarum model;

3) Sparus aurata model;

4) Off-shore mussel farming in the Adriatic sea ecological model;

Tapes philippinarum individual-based growth model (Solidoro et al. 2000)

The growth of the clam is the result of an energy budget, which is simulated using an ODE equation adapted from the original formulation proposed by Ursin (1967).

The rate of energy assimilation depends on water temperature and increases linearly with the concentration and energy content of food particles, up to a threshold, which depends on the dry weight.

Respiration depends on water temperature and on dry weight.

Model description

Model state variables are dry weight, wd, wet weight, ww, and length, L, of the clam.

Model description

wrTmaxw/

wgFgTmaxww w)t(Tfrw)t(Ff)t(TfG

dt

dw 32

3Laww

pwd wbw

Anabolic term Catabolic term

The parameters Gwmax and rwmax represent respectively the maximum growth rate and the maximum respiration rate

Wd and L are recalculated from ww, by means of isometric and allometric relations


CODE/NUMERICAL METHODS: model equation was numerically solved by meansof a 4th order Runge-Kutta scheme (Press et al., 1987);The model is coded in FORTRAN77;A Visual Basic user friendly interface is being developed;

FORCING DATA: time series of water temperature and POC/ phytoplankton


PARAMETERS

model was calibrated stepwise, using, in sequence, three differemt sets of field data:

1) the respiration rate as a function of water temperature, was estimated from the oxygen consumption data published by Goulletquer et al. (1989);

2) the maximum anabolism and the effect of temperature on the anabolic term was estimated on the basis of a set of length measurements taken in the Sacca di Goro (Rossi, 1996);

3) the filtration rate at the optimal temperature was estimated using a set of filtration rate data performed using specimens collected in the lagoon of Venice (Nesto, 1997).

0 35 118 177 254 277 319 381 429 524 577 638 713 846

simulation day

0

5

10

15

20

Wet

Wei

ght

[g]

p red icted observed

Examples of model scientific testing

The model was tested agains a set of water temperature, phytoplankton and Wet Weight data collected in the lagoon of Marano (Northern Adriatic Sea)

Solidoro, C., Pastres, R., Melaku Canu, D., Pellizzato, M., Rossi, R., 2000. Modelling the growth of Tapes philippinarum in Northern Adriatic lagoons, Marine Ecology Progess Series 199, 137-148.

In the framework of the ECASA project, Tapes philippinarum growth model could be tested on field data collected in Ria Formosa by participant 10 IMAR.

Plans for use in ECASA

Thank you

22 2 4 4 2

23 2 4 4 2 2

2 24 2 4 4 2

22 4 4 4

2 3

2

4 2 4 72

5 5 5 52

22 2 2

22 2

( ) (x

OM xO yH xCO yNH zHPO zH xH O

x yOM xNO H xCO yNH zHPO zH xN xH O

x x y xOM xSO H xCO yNH zHPO zH xHS xH O

x xOM yH CO yNH zHPO zH CH

OM CH O NH

3 4) ( )y zH PO

4 2 3 2

22 4

22 2 4

4 2 2 2

24 4 2 2 3

2 2

2

2 2

2

2

NH O NO H H O

HS O SO H

H S O SO H

CH O CO H O

CH SO CO H S HCO

Es: Modello implementato in laguna di Venezia

Reazioni di mineralizzazione della materia organica

Reazioni di riossidazione dei prodotti di degradazione

4

3 2 2

23 3

2

3 24 4

24 2 4

3

H HCO CO H O

CO H HCO

H HS H S

PO H HPO

HPO H H PO

NH H NH

4 4

2 4 2 4

2 24 4

3 34 4

NH NH

H PO H PO

HPO HPO

PO PO

Reazioni acido - base Reazioni di adsorbimento

Reazioni di equilibrio

Documents

ECASA modelling workshop, Dunstaffnage Laboratory, Oban 26-27 January 2006 14 – University of Venice