DIIAA - Dipartimento di Ingegneria Idraulica ed Applicazioni Ambientali Università di Palermo...

DIIAA - Dipartimento di Ingegneria Idraulica ed Applicazioni AmbientaliUniversità di Palermo (Italia) www.idra.unipa.it

MWWD 2008 – 5th International Conferenceon Marine Waste Water Discharges and Coastal EnvironmentCavtat (Croatia), Oct. 27-31, 2008

Mirella Di Giovanni, Salvatore Nicosia, Enrico Napoli, Gaspare Viviani, Giuseppe Ciraolo

Interpreting and modelling field datafor wastewater dispersion into sea

through dimensional analysis

The area investigated: 25 measuring stations distributed over 1 km2 sea surface in front of the city

Di Giovanni et al., DIIAA Palermo (Italia)Di Giovanni et al., DIIAA Palermo (Italia) 2222

• Two survey campaigns• Two seasons• 1 reference point sited 3 km offshore

City of PalermoCity of Palermo

The urban area, source of the wastewater discharge- still raw at the time (year 2005)

Di Giovanni et al., DIIAA Palermo (Italia)Di Giovanni et al., DIIAA Palermo (Italia)33

• 200 000 inhabitants• drinking water supplied per capita= about 400 litres/day• Wastewater PDWF 1,5 m3/s discharged into sea by the outfall.

Among the outputs of the Department’s research: thematic maps as overall pictorial view of the seawater quality


3 5 7 0 0 0 35 8 0 0 0 3 5 9 0 0 0 3 6 00 0 0 3 6 1 0 0 0 3 6 2 00 0 3 6 3 0 0 0 3 6 4 0 00

4 2 1 8 00 0

4 2 1 9 00 0

4 2 2 0 00 0

4 2 2 1 00 0

4 2 2 2 00 0

1

2

3

4

5

6 7

9 1 0

1 1

1 2

1 3

1 4

1 5

1 6

1 7

1 8

1 9

2 0

2 1

2 2

2 32 4

2 5

3 7

3 7 .1

3 7 .2

3 7 .3

3 7 .4

3 7 .5

3 7 .6

3 7 .7

3 7 .8

3 7 .9

M a p p a d i S a lin it à

N o v e m b re 2 0 0 5 , 5 0 c m d i p ro f o n d ità

M e t o d o d i g r i d d in g : RA DI A L B A S IS F U NC T IO N

3 5 7 0 0 0 35 8 0 0 0 3 5 9 0 0 0 3 6 00 0 0 3 6 1 0 0 0 3 6 2 00 0 3 6 3 0 0 0 3 6 4 0 00

4 2 1 8 00 0

4 2 1 9 00 0

4 2 2 0 00 0

4 2 2 1 00 0

4 2 2 2 00 0

1

2

3

4

5

6 7

9 1 0

1 1

1 2

1 3

1 4

1 5

1 6

1 7

1 8

1 9

2 0

2 1

2 2

2 32 4

2 5

3 7

3 7 .1

3 7 .2

3 7 .3

3 7 .4

3 7 .5

3 7 .6

3 7 .7

3 7 .8

3 7 .9

M a p p a d i S a lin it à

N o v e m b re 2 0 0 5 , 5 0 c m d i p ro f o n d ità

M e t o d o d i g r i d d in g : RA DI A L B A S IS F U NC T IO N

357000 358000 359000 360000 361000 362000 363000 364000

4218000

4219000

4220000

4221000

4222000

1

2

3

5

6

9

11

12

18

21

22

25

0

1 0 0 0 0

2 0 0 0 0

3 0 0 0 0

4 0 0 0 0

5 0 0 0 0

Mappa n°2

M etodo di gridding: RAD IA L BAS IS FUNC TION

357000 358000 359000 360000 361000 362000 363000 364000

4218000

4219000

4220000

4221000

4222000

1

2

3

5

6

9

11

12

18

21

22

25

0

1 0 0 0 0

2 0 0 0 0

3 0 0 0 0

4 0 0 0 0

5 0 0 0 0

Mappa n°2

M etodo di gridding: RAD IA L BAS IS FUNC TIONthe Faecal Coliforms

distribution

the distribution of Salinity

The hydraulic behaviour of water discharged into sea: “plume” or “jet” at the issue. By definition…


In an unrestricted environment, at a certain distance from the outfall a jet eventually turns itself into a plume; the place where it happens depends on some features characterizing the discharge.

Near the outfall, the behavior of jets and plumes is controlled only by the initial conditions such as velocity and geometric features.

a simple jet is driven into the marine environment by the initial value of its momentum at the outfall only;

a simple plume, instead, has no initial momentum, but moves into sea due to its tendency to buoyancy.

The physical quantities playing a role in jet dynamics are assumed to be 5:

1) A, the cross-sectional area of the jet;2) u, the time-averaged jet velocity in the axial

direction;3) , the density of the fluid discharged; 4) q, volume per unit time or volume flux of the jet;5) m, the specific momentum flux.

Di Giovanni et al., DIIAA Palermo Di Giovanni et al., DIIAA Palermo (Italia)(Italia) 66

What does specific stand for in this context? ()

A 6th quantity is purposely defined at this stage:

6) , the specific buoyancy flux.

() A physical quantity is called specific when its ordinary definition is modified dividing it by the fluid density, .

Di Giovanni et al., DIIAA Palermo Di Giovanni et al., DIIAA Palermo (Italia)(Italia) 77

So for instance we have a mass flux of the jet

and a specific mass flux, called also “volume flux”

which is nothing else than the familiar volumetric flow rate!

]TM[ -1 A

dAuq ]TM[ -1 A

dAuq

q [L3T-1]q [L3T-1]

Three relationships link together the factors of major importance For the mass flux of the jet, which is the mass of

fluid passing a jet cross section per unit time:

For the momentum flux, which is the amount of momentum passing a jet cross section per unit time:

For the buoyancy flux the buoyant or submerged weight of the fluid passing through a cross section per unit time:


]TM[ -1 A

dAuq ]TM[ -1 A

dAuq

]TL[M -22 A

dAum ]TL[M -22 A

dAum

]TL[M -3 A

dAug ]TL[M -3 A

dAug

The initial values of - specific mass flux or “volume flux” q; - specific momentum flux, m; - and specific buoyancy flux, …


… completely govern the dilution of round turbulent buoyant jets.

They are customarily written in capital letters: in order Q, M, and B.

These are therefore called the primary variables, although a name like issue or source variable would probably be not less appropriate.

Almost all of the properties of turbulent jets that are of importance to engineers can be deduced…

Di Giovanni et al., DIIAA Palermo Di Giovanni et al., DIIAA Palermo (Italia)(Italia)

1010

…through simple dimensional reasoning involving the just defined variables + empirical data.

CASE A- SIMPLE JET

A simple jet is perfectly characterized by the so-called characteristic length scale, lQ defined as

LTL

TL

M

QlQ

2/124

13 L

TL

TL

M

QlQ

2/124

13

The quantity lQ appears - or can be put in evidence - in most of the relevant hydro-dynamical parameters.

Example: the jet mean axial velocity, um , depends on Q, M, and the ratio of the distance from the outfall (z) to the characteristic length scale lQ


-

Qm

l

zf

M

Qu -

Qm

l

zf

M

Qu

muQ

lQ

2

1 MQ

lQ 2

2

2Ql

z3

axis velocity um

spec. momentum flux M

length scale lQ

volume flux Q

The same procedure could be applied e.g. with the aim to find a relationship for …

the volume flux q at any distance along the trajectory, or

the mean concentration C of a substance of interest (tracer).

CASE B- SIMPLE PLUME

The demonstration just made can equally be applied to a simple plume, provided that the typical length scale is re-defined herein as:

L

TL

TL

B

MlM

2/134

3/4244/3 L

TL

TL

B

MlM

2/134

3/4244/3


Using this definition…


1313

… the jet mean axial velocity cannot but depend on the specific buoyancy flux; the distance from outfall; and the viscosity (kinematic).In symbols:

- 3 2

3

Bz

fB

zum -

3 23

Bz

fB

zum

Summary of analytical solutions for simple jets and plumes

Para_meter

Measure units

Analytical solutions for simple jets

Analytical solutions for simple plumes


mu

mC

q

1TL

3LM

13 TL

z

l

M

Qu

Qm 7

z

l

C

C Qm 64,50

Ql

z

Q

q 25,0

37,4z

Bum

3/53/115,0 zBq

3/53/1

1,9

zBY

Cm

The basis for an analytical model, summarized


In order to simulate the sewage dilution in seawater, it is therefore possible to calibrate and apply an analytical model based on

1)equations coming from dimensional analysis 2)the statement of the discharge behaviour + local

environment parameters, and 3)the discharge geometrical factors at the issue.

This is the classical theory of diffusion of jets and plumes in the receiving water body.


Ground Level

Sea Level

Bottom

Ground Level

Sea Level

Bottom

Ground Level

Sea Level

Bottom

Ground Level

Sea Level

Bottom

Q = 1,5 m3/s; ED = 4 · HR = 2,73 m

Figure 1: aerial view of the study area with the indication of the outfall (a) and details nearby the outfall (b)

““PPoorrttaa FFeelliiccee”” OOUUTTFFAALLLL

(b) (a)

The study area with the outfall (a) and some details nearby (b)

The study area with the outfall (a) and some details nearby (b)

Outfall confi_ guration and

discharge data

The primary variables for the sewer outfall

Predicting the wastewater dilution into the marine environment

In this case study, the initial value of momentum was very low ( 410 N), so it was possible to define the discharge as a simple plume.

“primary variables”: Q, M,

B

Outfall shape, rate of flow

etc.

Definitions

The water behaviour: jet or

plume?

……

Once defined the behaviour of the fluid discharged into the sea…

… under the assumption of Gaussian distribution of concentration across the plume axis

it was possible to calculate the value of the most important variables characterizing the plume, such as

velocity, buoyancy and concentration of any tracer released within

wastewater,

aiming at predicting the dilution. Salinity - a conservative tracer - was chosen as

indicator for calculations.

Di Giovanni et al., DIIAA Palermo (Italia)Di Giovanni et al., DIIAA Palermo (Italia)

)2/ Tbx

m eCC

The calculations, 1

Local salinity value in the plume weighted average between the wastewater and the seawater entrained.

The plume we are dealing with originates from a surface port; thus the formula for the rate of flow becomes

where:

- the cross section A is replaced by the product of distance from plume axis, x, times the sea depth, H;

- bu is the spreading coefficient, the parameter typical of the Gaussian concentration distribution.

A

dAuq A

dAuq

)2/ Tbx

m eCC

)2/ Tbx

m eCC

)2/ Tbx

m eCC

)2/ Tbx

m eCC

)

nx

nx

ubx dxeuHq m 2


The calculations, 2

For the spreading coefficient empirical studies suggest to use the relationship

The solution of the integral above, then, yields q(z,x):

After these steps, salinity can be calculated at any point of measure:

)2/ Tbx

m eCC

)2/ Tbx

m eCC

)2/ Tbx

m eCC

)2/ Tbx

m eCC

107,0zub

) ) ) Qxzq

xzqSxzS seacalc

,

,,


) ) ) ) )

zb

xerfzbzuxzHxzq

uum ,, ) ) ) ) )

zb

xerfzbzuxzHxzq

uum ,,

Flow chart of the calculations


INPUTINPUT

OUTPUTOUTPUT

Outfall geometric featuresOutfall geometric features Discharged flow

Discharged flowMeasures stations

Measures stations

Equivalent diameterEquivalent diameter

Primary VariablesPrimary Variables

Distance from outfallDistance from outfall

Plume featuresPlume features

Seawater entrainedSeawater entrained

Calculated SALINITY

Calculated SALINITY

Table 2: comparison between measured and calculated values of

salinity

Figure 1: a planar view of the measuring stations which this study is based on

“Porta Felice” OUTFALL

Table 2: comparison between measured and calculated values of

salinity

Figure 1: a planar view of the measuring stations which this study is based on

“Porta Felice” OUTFALL

Verifying the results


Point ID number

Sal., meas.

Sal., calc.

% (calc – meas)

Comments

1 37,57 37,53 - 0,11 Underestimated clean seawater

income

2 37,66 37,71 0,13Underestimated

other wastewater volumes entering

into the area

5 37,41 37,72 0,83

9 37,53 37,72 0,51

Comparing the salinity distributions

357000 358000 359000 360000

4219000

4220000

4221000

4222000

1

2

3

4

5

6 7

9 10

11

12

13

25

3 7

3 7 . 1

3 7 . 2

3 7 . 3

3 7 . 4

3 7 . 5

3 7 . 6

3 7 . 7

3 7 . 8

3 7 . 9

M appa di Salin ità : va lori teoric i

Porta F

elice

357000 358000 359000 360000

4219000

4220000

4221000

4222000

1

2

3

4

5

6 7

9 10

11

12

13

25

3 7

3 7 . 1

3 7 . 2

3 7 . 3

3 7 . 4

3 7 . 5

3 7 . 6

3 7 . 7

3 7 . 8

3 7 . 9

Porta F

elice

Mappa di Salinità: valori m isurati in situ

(a) (b)

SURFER® maps of calculated values (a) against measured (b)

Apparently the measures were affected by a) currentsb) associated overlapping of surface water other than sewagewhich these calculations cannot take into account. ()

river mouth

Surface water circulation around the outfall

The map shows the strength and direction of measured currents.

The directions of currents in the zone seems to create a “short circuit”, driving seawater in a clockwise direction.

river mouth

Concluding remarks


This study aimed at: predicting the dilution of wastewater discharged on-shore into the sea, calculating the value of salinity as an indicator; making a comparison calculated values / experimental data gathered with a survey cruise. The model predicted plume effects ranging not farther than 200 meters from the coast. In fact, salinity values lower than the sea were measured as far as 350 meters away. The currents pattern suggest that the differences between predicted and experimental salinity can be ascribed to the overlapping of other sources of contamination, such as the adjacent harbours and the near mouth of a small river. Due to its simple structure, this analytical model cannot actually deal with multi-source phenomena.

Acknowledgements


The Municipality (Comune di Palermo, Ufficio per il Centro Storico) encouraged the Authors’ University Department in planning this research and provided financial support for its development. Its contribution is gratefully acknowledged.

DIIAA - Dipartimento di Ingegneria Idraulica ed Applicazioni Ambientali Università di Palermo...

Documents

Transcript of DIIAA - Dipartimento di Ingegneria Idraulica ed Applicazioni Ambientali Università di Palermo...