1 Dynamics of nutrients in the Gdańsk Gulf; numerical simulations.

1

Dynamics of nutrients in the Gdańsk Gulf; numerical simulations.

Institute of Oceanology PAS, Sopot, Poland

Lidia Dzierzbicka-Głowacka

e-mail:[email protected] Institute of Oceanology PAS, Sopot, Poland

2


An one-dimensional ecosystem model is used to make a numerical investigation of nutrients dynamics in the Gdańsk Gulf.

The 1D - model consists of three submodels: a meteorological submodel for the physics

of the upper layer and a biological submodel, which also is driven by output from the physical submodel.

3


My philosophy is to make the model as simple as possible, so I model phytoplankton by only one state variable and is represented by the

carbon concentration.

The model is based on total inorganic nitrogen (NO3 + NO2 + NH4) and phosphate (PO4). The nutrient serves both as a trigger and as

a limiting agent for primary production.

The concept of the detrital pool at the bottom has been introduced to create a lag in remineralization of the majority of detritus and the eventual replenishment of the upper layer with nutrients.

This complex process is parameterised by assuming a net remineralization rate for bottom detritus .

The zooplankton has been introduced into the 1D – model as a biomass and is represented by the microzooplankton.

4


The phytoplankton standing stock, zooplankton and nutrient in the water column serve as time and depth dependents pools. Detritus is a time dependent pool at the bottom. All four pools are prognostic state variables. Bacteria are not explicitly simulated as prognostic variables. Their activity only appears implicitly in the parameterizations of the remineralization terms. Benthic detritus accumulates by sinking out of the water column. It is regenerated by bacterial action, and the resulting nutrient diffuses upwards by turbulent diffusion.

5


Meteorological submodel The meteorological component calculates the forcing functions for the physical oceanographic and biological components. Wind stress, global radiation and the heat balance at the sea surface are determined from standard meteorological data and hydrographic climatological data. Global radiation is calculated by application and adaptation of a radiation model, which is based on the radiation at the outer atmosphere and local cloudiness. The latent and sensible heat fluxes are calculated by so-called bulk formulae.

6

z

uK

zfv

t

uz (1)

z

vK

zfu

t

vz (2)

z

z eFcz

TK

zt

T

10

1 (3)


Physical submodel

I consider here the dynamics of the horizontally quasi-homogeneous upper layers of the ocean in terms of ocean boundary layer dynamics. Thus all horizontal gradients vanish. The Coriolis force is maintained to enable Ekman layer dynamics. Both velocities are affected by turbulent diffusion and Coriolis acceleration. The temperature changes are caused by turbulent heat diffusion and solar heating of the water column and the surface heat fluxes.

7


Biological submodel

The system of equations consists of four nonlinearly coupled partial differential equations of second order for phytoplankton, zooplankton and nutrient and one ordinary differential equation of first order for benthic detritus.

GRAMORRESPRE

Pzz z

PhytK

zz

Phytw

t

Phyt ( 4 )

PREDMETFECING

z

ZoopK

zt

Zoopz ( 5 )

NNNNin fN EXCREMIRELUPT

F

z

NutrK

zt

Nutr Nz

N ( 6 )

PPPPin fP EXCREMIRELUPT

F

z

NutrK

zt

Nutr Pz

P ( 7 )

REMDD HF

dt

DetrdP ( 8 )

8


Initial and boundary conditions The following initial and boundary conditions supplement equation system (4)-(8): the initial vertical distributions of phytoplankton {Phyt}, nutrient {Nutr}, zooplankton {Zoop} and detritus pool {Detr} are known:

HzzPhytzPhyt 00, 0

HzzZoopzZoop 0)(0, 0

HzzNutrzNutr NN 00, 0

HzzNutrzNutr PP 00, 0

HzDetrtDetr 00 0 (9)

9


The vertical gradient of phytoplankton, zooplankton and nutrient concentration flux are zero at the sea surface (z = 0):

0000

t,Phytw

z

t,zPhytKF z

zzP

0

,0

0

z

NzN z

tzNutrKF

N

0

,0

0

z

PzN z

tzNutrKF

P

0

,0

0

zzZ z

tzZoopKF (10)

10


However, the bottom flux condition for phytoplankton, nutrient and zooplankton is given as:

t,HPhytwHF zP (11)

REMD

,N

Hz

NzN g

z

tzNutrKHF

N

(12)

REMD

,P

Hz

PzN g

z

tzNutrKHF

P

0

0

zzZ z

t,zZoopKHF (13)

. This flux FP(H) enters the benthic detritus equation as a source term. The boundary condition (12) provides the mechanism of replenishing the water column with nutrient resulting from benthic remineralisation

11


N U M E R I C A L S I M U L A T I O N S

The aim is not generality but a description of a numerical investigation of nutrients dynamics in one example of a model. The temporal changes in distributions of a nutrients ( inorganic nitrogen, and phosphate), of phytoplankton carbon and of zooplankton are necessary outputs from the biological model.

The flow field and water temperature used as the inputs of the biological submodel were reproduced by the physical submodel.

12

Fig. 1. The map of the Gdańsk Gulf with the location of sampling stations.


The calculations were made for 180 days

(from March to August) for two stations

at Gdańsk Gulf (at station A, near the

Vistula river mouth, and at station B

located further to the open sea).

13


Fig. 2a. Simulated profiles of temperature at the stations A and B

14


Fig. 2b. Simulated of surface temperature at the stations A and B

15


Fig. 3. Simulated profiles and observed values of total inorganic nitrogen at the stations A and B

16


Fig. 4. Simulated profiles and observed values of phosphate at the A and B

17


Fig. 5. Simulated and mean observed values of total inorganic nitrogen and phosphorus in the upper layer at the stations A and B

total inorganic nitrogen phosphate

Renk (2000) obtained relationship of phosphate and total inorganic nitrogen in the euphotic layer in the southern Baltic Sea as P=0.072N+0.115. This equation suggests that in the vegetation season the P:N =1:14.1. In the Gdańsk Gulf in this period the N:P=10.8; but in the Gdańsk Deep is 6.5.

18


Fig. 6a. Simulated profiles of phytoplankton biomass at the stations A and B

19


Fig. 6b. Simulated and observed values of phytoplankton at the surface sea at the stations A and B

C/Chl-a = 34 mgC (mgChl)-1

20


Fig. 7a. Simulated profiles of zooplankton biomass at the stations A and B

21


Fig. 7b. Simulated and observed values of depth integrated of zooplankton at the stations A and B

gC/gw.w. = 0.05

22


Fig. 8. Phytoplankton and zooplankton biomass at the stations A and B

23


C O N C L U S I O N

The results of the numerical simulations described here is in good agreement with the mean observed values. The difference in the {Nutr} between the simulated and

observed values in the upper layer is equal to c. 1 mmol m-3 for inorganic nitrogen and c. 0.1 mmol m-3 for phosphate.

However, the difference in the {Phyt} between the modelled and mean observed values is equal to 0.5-1.3 mgChl m-3

and depend on the month for which the calculations were made. Comparing the zooplankton biomass

from the calculated and mean experimental data the present results indicate that the difference in the {Zoop}

at these stations is equal to 100 mgC m-2.

The 1D – model can be utilized for numerical investigations of nutrient distributions and phytoplankton and zooplankton biomass.

24


Lidia Dzierzbicka-Głowacka

e-mail:[email protected] Institute of Oceanology PAS, Sopot, Poland

Thank you for attention

1 Dynamics of nutrients in the Gdańsk Gulf; numerical simulations.

Documents

Transcript of 1 Dynamics of nutrients in the Gdańsk Gulf; numerical simulations.