11

Modelling Bacterial Levels in Rivers to

the Coastby

Roger Falconer

Hydroenvironmental Research Centre,School of Engineering, Cardiff University

22

Hydroenvironmental Research Centre

33

• Prof. Roger FalconerHalcrow Professor of Water Management

• Dr. Binliang LinSenior Lecturer in Hydroinformatics

• Dr. Catherine Wilson Lecturer in Eco-Hydraulics

• Dr. Bettina Bockelmann-Evans Lecturer in Environmental Hydraulics

• 12 Research Associates and Students

• 3 Academic Research Visitors

Research Team

44

• Develop hydro-environmental models to predict hydrodynamic, solute, sediment and contaminant transport processes in river, estuarine and coastal waters

• Undertake laboratory model studies and assist in field monitoring programmes to improve accuracy of processes modelled

• Improve interfaces and output devices for wider use of hydro-environmental models

Research Objectives

55

Current Research• Hydro-environmental modelling

• River and floodplain integrated modelling

• Wetland and mangrove nutrient modelling

• Vegetation impact on riverine systems

• Sediment and bio-chemical interactions

• Coastal and estuarine hydrodynamics

• Computer model solution algorithms

66

Environmental Hydraulics Challenges

77

• River basin flood risk management

• River sedimentation and morphology

• River ecology and water resources

• Domestic, agricultural and industrial effluents - point and diffuse sources

• Surface and subsurface interactions

• Land use and catchment hydrology

Typical Challenges

88

Physical Models

99

Physical Models

ScalingExpensiveInflexible

Not PortableNot Adaptable

DisadvantagesDisadvantagesDisadvantages

1010

No scalingInexpensive

FlexiblePortable

Adaptable

AdvantagesAdvantagesAdvantages

Numerical Models

1111

Numerical Models

Hydrodynamic processesWater quality processes Sedimentary processes

Solution algorithmsBoundary data

UncertaintiesUncertaintiesUncertainties

1212

Solution Procedure

1313

Decay?

Dissipation

Production?

MassMomentum

Solutes(Pollutants,Sediments,

or Metals)

dx

dy

b. Main processes occurringin each grid square

Watershed

Open Boundary?

a. Typical grid representation for river - coastal basin

LandLand

1414

• Advective-diffusion equation (with source inputs, bed and/or surface fluxes, kinetic interactions and/or particle settling)

• Continuity equation (with source inputs)

• Momentum equations (with earth’s rotation, wind shear, bed shear and turbulence)

Flow Modelling

Solute Modelling

1515

Water Quality• Physical

− Suspended Solids− Turbidity− Temperature− Radio-activity

• Chemical− Dissolved Oxygen− Bio-chemical Oxygen Demand− Nitrogen− Phosphorous− Metals

• Biological− Pathogens− Algae

1616

Collaborative Studies with CREH

1717

General Project Aims• Develop empirical relationships for bacterial

indicator levels with flow, sedimentary and bio-chemical processes in river basins

• Acquire better model representation between bacterial indicator and nutrient levels with sediment transport processes in river basins

• Refine hydroenvironmental modelling tools to provide holistic approach to river basin management and legislative compliance

• Refine models using data from 3 UK sites

1818

1. Total die-off

2. Settlement

3. Decay in darkness

4. Irradiance with decay also related to SPM

5. pH die-off

6. Temperature die-off

1. 2. 3. 4. 5. 6.

ktot = ks + (kd + f(Io,SPM))f(pH) f(T)

• Bacterial decay known to depend upon many parameters such as:-

Bacterial Decay• Hydroenvironmental models tend to use

constant values for decay rate or T90:

k = constant or k = φ(Temp)

1919

• Depth reduces effect of sunlight on decay (increases T90 value)

Effect of water depth on die-off ([SS]=10mg/l)

0

10

20

30

40

50

60

0 500 1000

Irradiance at waters surface, Io (W/m2)

Dept

h av

erag

ed T

90 (h

ours

)

Z=0.2m

Z=0.3m

Z=0.5m

Z=0.75m

Z=1.2m

Z=1.8m

Z=2.9m

Z=4.5m

Bacterial Decay

2020

Bacterial Decay• Suspended solids reduce effect of sunlight

on decay (increase T90 value) Effect of suspended solids on die-off

(Z=1m)

0

10

20

30

40

50

60

0 500 1000

Irradiance at waters surface, Io (W/m2)

Dept

h av

erag

ed T

90 (h

ours

)

[SS]=0.5 mg/l

[SS]=1 mg/l

[SS]=2 mg/l

[SS]=4 mg/l

[SS]=8 mg/l

[SS]=16 mg/l

[SS]=32 mg/l

[SS]=64 mg/l

2121

• Darkness to sunlight leads to increase in decay rate (reduction in T90 value)

1

10

100

1000

1 10 100 1000 10000Sunlight strength (Irradiance) W/m2

Faec

al C

olifo

rm T

90 (h

ours

)

Pommepuy et al. (1992),seawater.

Auer and Niehaus (1993),hypereutrophic lake.

Evison (1989), cleanfreshwater, 15 degC.

Evison (1989), cleanseawater, 15 degC.

Bellair et al., (1977), seawater18.5-26 degC

Sarikaya and Saatchi (1987),waste ponds, 25-30 degC.

Sarikaya et al. (1987), wasteponds, 26-31 degC.

Sarikaya et al. (1987), batchstudy, 24-27 degC.

Bacterial Decay

2222

Enteric Bacteria Fluxes• Bacteria in river and estuarine waters

primarily exist in two forms:Free-living bacteria moving with currents Adsorbed bacteria may beattached to surface of sediment particles and moves with sediments

• Adsorbed bacteria moving with sediments may be deposited on bed and subsequently re-suspended or desorbed to water column

• Free-living and adsorbed bacteria undergo decay processes - which are highly dynamic

2323

Enteric bacteria

water columnWastewater outfallsCatchment runoffWater birds

input

AdvectionDiffusion/dispersion

outputOverall reduction

Die-off

Deposition

Sediment re-suspension

Enteric Bacteria Fluxes

2424

Cardiff Bay

2525

Cardiff Bay Study

2626

grid cell size

50m x 50m

3-D Numerical Model

10 15 20 25 30 35 40 45 50 55 60

10 15 20 25 30 35 40 45 50 55 60

40

45

50

55

60

65

70

75

80

40

45

50

55

60

65

70

75

80

-8m

-6m

-4m

-2m

0m

2m

4m

6m

8m

10m

12m

14m

Queen AlexandraDock

RiverEly Depth

RiverTaff

BARRAGE

2727

Tracer Calibration

2828

Field MeasurementsMarch 2002, characterising

cold, overcast conditionsJuly 2002, characterising

hot, sunny conditions

2929

Monitoring Sites

3030

Measured Data• River discharges measured continuously at

upstream flow gauging stations

• Faecal coliforms and streptoccoci sampled daily at most sites by Harbour Authority

• Coliforms and streptococci measured hourly in day-light during field monitoring period

• Sunlight intensity measured hourly over Bay and also with depth at several key sites

• Temperature, pH and DO etc. also monitored

3131

0

700

07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00

07:00 19:00

Light Intensity

coun

ts/1

00m

l

100

Faecal ColiformFaecal Streptococci

Bacteriological measurements : Eastern Dock SiteBacteriological measurements : Eastern Dock SiteBacterial Decay

3232

Time

0102030405060708090

100

08:30 10:30 12:30 14:30 16:30 18:30

Rad

iatio

n in

put (

x 10

µm

ol/m

2/s)

Surface0.1 m0.5 m1.0 m1.5 m2.0 m2.5 m3.0 m3.5 m

Light variation with depth : Eastern Dock SiteLight variation with depth : Eastern Dock SiteBacterial Decay

3333

0.1

1

10

100

1000

11-Sep-88

30-Mar-89

16-Oct-89

04-May-90

20-Nov-90

08-Jun-91

25-Dec-91

12-Jul-92

28-Jan-93

16-Aug-93

T90

hour

s

1

10

100

1000

10000

100000

FC c

fu/1

00m

l

3 day running average T90 (hours) 5 day running average FC (cfu/100ml)

Die-off Found to be Seasonal

3434

Artificial Neural Networks

Input LayerHidden Layer

Output LayerInpu

t Var

iabl

es

Output

1,1w1,2w

1x

2x1w

2w0w

+

1+

∑=

=N

iijij xwF

1, xe

xf−+

=1

1)(Sigmoid Equation

Back propagation Algorithm

3535

K K KT d S= +

Dynamic Decay Rate

( )[ ] sunlight for ratedecay conditionsdark for ratedecay

tIfKK

S

d

===

629.0236.063.2

givesdataofanalysisANN

IK T +=

3636

Millennium Stadium

3737

Varying day/night TVarying day/night T9090 values values -- 4 pm releaserelease

70,000

45,000

60,000

30,000

20,000

10,000

0

Faecal Coliform

counts/100ml

Model Simulation

3838

70,000

45,000

60,000

30,000

20,000

10,000

0

Faecal Coliform

counts/100ml

Varying day/night TVarying day/night T9090 values values -- 4 am releasereleaseModel Simulation

3939

River Ribble and Fylde Coast, U.K.

4040

Fylde Coast

London

Blackpool

LythamSt Anne’s

Ribble Estuary

River Wyre

Southport

Fleetwood

Compliance point

4141

Blackpool

Lytham St Annes

River Ribble

River DouglasRibble Estuary

River Wyre

Bathing water

Pumping station

Treatment works

Key

Southport

Water Assets• £500 million

invested from 1993 – 1996

• 3 major sewage treatment works

• 5 pumping stations with storm outfalls along coast

4242

Background• Failure to meet EU Bathing Water standards

• Storm sewers and sewage works discharging into rivers and coast thought to be cause

• Combined storm water and sewer overflows discharge into water courses and rivers

• Field surveys undertaken to establish inputs and failure levels at compliance points− Surveys unable to provide definitive conclusions − Data did not allow for impact of proposed capital

improvement works to be assessed

4343

BWD 76/160/EEC

4444

Coliform Sources

Creature

Faecal production (g per day)

E. coliper g

faeces

E. coliload (per

day)

Human 150 1.3x107 1.9x109

Cow 23600 2.3x105 5.4x109

Hog 2700 3.3x106 8.9x109

Sheep 1130 1.6x107 1.8x1010

Ducks 336 3.3x107 1.1x1010

Turkeys 448 3.0x105 1.3x108

Chickens 182 1.3x106 2.4x108

Gulls 15 1.3x108 2.0x109

4545

Objectives• Develop hydroenvironmental modelling tool

• Quantify impact of sewage inputs into Ribblebasin on coastal bathing water quality

• Investigate influence of various parameters such as wind, tidal range, river discharge, etc

• Allow for continuous and intermittent inputs

• Incorporate diffuse source inputs and new boundary inputs as data become available

• Propose management strategies for basin

4646

Project Strategy

Integrated modelling approach Integrated modelling approach -- predicting predicting microbiological water quality indicatorsmicrobiological water quality indicators

Coastal ModellingCoastal Modelling River ModellingRiver Modelling CSO ModellingCSO Modelling

4747

Study AreaTidal limit for rivers Ribble, Darwen and Douglas Seaward boundary close to 25m contour in Irish SeaNarrow rivers feed into wide estuary and coastal zone−Riverine boundary limit < 10m−Coastal boundary limit > 40km

Many effluent discharges occur along river reachesComplex hydrodynamic processes along river basin

4848

Linked 3/2-D and 1-D Models

326000 330000 334000 338000 342000 346000 350000 354000 358000 362000418000

422000

426000

430000

434000

7mile

3mile

Tarleton Lock

Bullnose

PenworthamBlue Bridge

Darwen Boundary

Douglas River

Ribble Boundary

Downstream Boundary

Measuring Water Elevation

Tide Survey

Measuring Discharge

4949

Estuary Bathymetry

405000

410000

415000

420000

425000

325000 330000 335000 340000 345000 350000

Bed elevation aboveOrdenance Datum (m)

< - 8.0-8.0 to –6.0-6.0 to –4.0-4.0 to –2.0-2.0 to 0.0 0.0 to 2.0

4.0 to 6.0 > 6.0

2.0 to 4.0

5050

1-D Model Setup

• 5 riverine reaches - each of length 50km

• 153 cross-sections included along rivers

• Interpolation between cross-sections to reduce effective spacing to 50m

• 922 interpolated cross-sections in total

• Discharges specified at upstream limit

• Diffuse source inputs along any node

FASTER (Flow And Solute Transport in Estuaries and Rivers)

5151

2-D Model Setup

• Developed by Water Research Centre (Iran) and used by HRC at Cardiff University

• Finite volume unstructured triangular mesh

• Higher order TVD scheme for advection

• Sub- and super-critical shallow water solver

• 17 water quality indicators included in model

• High quality animations and output included

HEMAT (Hydro-Environmental Modelling and Analysis Tool)

5252

• Bathymetric data obtained from:− LIDAR (Light Induced Direction And Range) − Sidescan sonar mounted on survey vessel− Admiralty chart used to compliment data

• Seaward boundary data provided by POL

• High grid resolution for estuarine basin

• Modelled tested extensively against field data

• Model used to predict coliforms and sediment

2-D Model DetailsHEMAT (Hydro-Environmental Modelling and Analysis Tool)

5353

Hydro-Environmental Modelling and Analysing

Tool - HEMAT

Water Research CentreWater Research CentreTehran Tehran -- IRANIRAN

Bristol Channel Application

Hydroenvironmental Hydroenvironmental Research Centre Research Centre -- CardiffCardiff

5454

Mesh Generator Interpolator Solver GUI Post-processor

Hydro-Environmental Modelling and Analysis Tool

5555

Mesh Generator Interpolator Solver GUI Post-processor

Hydro-Environmental Modelling and Analysis Tool

5656

Mesh Generator Interpolator Solver GUI Post-processor

Hydro-Environmental Modelling and Analysis Tool

5757Hydro-Environmental Modelling and Analysis Tool

Mesh Generator Interpolator Solver GUI Post-processor

5858

Grid Resolution in Estuary

5959

Simulation of Flooding - Drying

6060

Flow Calibration

53 54 55

Wat

er E

leva

tion

(m) Model

Measured

-4-3-2-10123456

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52

-0.5

0

0.5

1

1.5

2

2.5

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55

Tim e (hours)

Spee

d (m

/s)

Model

Measured

-500

50100150200250300350400

30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55

Tim e (hours)

Dire

ctio

n (d

eg)

Model

Measured

Time (hours)

Time (hours)

11 Milepost

3/12/98Emax=4.7%

Emin=1.9%

Emax=13.0%

Emin=9.7%

Emin=2.2%

6161

Ribble EstuaryModel Calibration

11 milepost

11 May 1999 Wet Weather Neap Tide

6262

19 May 1999 Dry Weather Spring Tide

Ribble EstuaryModel Calibration

11 milepost

6363

Predictions• Baseline scenario predicted for mean inputs

• Various flow, tide and wind conditions studied

• Impact of different waste water treatment strategies and inputs considered

• Diffuse source inputs included from field data

• River discharges and inputs from CSOs and water treatment works studied individually

• All key locations along rivers, estuary and bathing waters analysed for coliform levels

6464

Coliform Predictions

6565

Coliform Predictions

6666

Coliform Predictions

6767

Ribble EstuaryModel Predictions

11 milepost

6868

Conclusions

6969

• Computational models increasingly powerful tools for managing aquatic environment

• Hydroenvironmental models depend heavily upon field data and empirical relationships -increasingly requiring interdisciplinary team

• Hydroinformatics tools linked with hydro-environmental models offer scope for online approach to river basin management

• Considerable scope for improving models

General Comments

7070

Addendum

7171

“Acknowledging uncertainties in river basin management is a

strength, for which youwill not be thanked”

HRH The Princess RoyalHRH The Princess Royal

Cardiff University, 2002Cardiff University, 2002

7272

Thank You