This document discusses biological contamination of coastal bathing waters. It notes that contamination is often from fecal matter and lists various pathogens that can be present, including viruses, protozoa, bacteria, and parasites. Testing all possible pathogens is impractical, so indicator bacteria like E. coli and intestinal enterococci are used instead as they are fast, inexpensive alternatives. The EU Bathing Water Directive classifies waters based on these indicators. The Smart Coasts project aims to better understand sources of pollution to allow more bathing waters to meet standards and retain their "Blue Flag" designation for tourism through modeling, monitoring, and public information tools.

1. Smart Coasts = Sustainable
Communities

2. Biological contamination of bathing
waters is often faecal in origin
Viral
Adenovirus
Adenovirus Symptoms include:
• Pneumonia
Protozoa and Trematodes • Gastroenteritis
Cryptosporidium • Diarrhoea
Giardia • Fever
Trematode worm • Nausea
• Death
Giardia
Bacteria
Campylobacter
E. coli
Leptospira
Leptospira

3. Not practical to test for all pathogens
• Time consuming
• Expensive
• Not possible for some (due to e.g., detection limit)
Intestinal Bacteria as Water Quality Indicators
• Inexpensive and fast alternative for faecal pathogens
• Can be quantified allowing limits to be set
• Regulatory standards for shellfish areas and recreational waters
• Is standardized under ISO
Faecal Indicator Bacteria (FIB)
E. coli, Intestinal Enterococci

4. The EU revised Bathing Water Directive uses FIB to
classify bathing waters into: Excellent, Good, Sufficient, Poor
It is more stringent than previous EU Bathing Water Directive
Current bathing waters will be down graded if no action is taken.

5. In addition to EU Directives: the
voluntary world-wide Blue Flag status
for Beaches and Marinas.
http://www.blueflag.org/
Dependent on:
• ENVIRONMENTAL
EDUCATION AND
INFORMATION
• WATER QUALITY (includes
‘Excellent’ for FIB)
• ENVIRONMENTAL
MANAGEMENT
• SAFETY AND SERVICES
Is an essential element for the
success of tourist destinations
Severe economic loss if Blue Flag
status is lost

6. Discounting of 15% of samples in a reporting period is allowed
Designated coastal and inland bathing waters: retrospective classification based on the
Irish Bathing Water Regulations (S.I. 79 of 2008), using the compliance data for the bathing
season 2007 to 2010. Classifications are shown without and with discounting.
Assessment Discounting Total Poor Sufficient Good Excellent
period category no. no. (%) no. (%) no. (%) no. (%)
yr/2007-2010 No discounting 131 10 (8) 14 (11) 23 (18) 84 (65)
With discounting 131 4 (4) 2 (2) 16 (13) 109 (84)
B. Masterson
Discounting results in an overall increase in bathing water classification
DEFRA estimates a £1.4 billion costs saving with discounting in the UK

7. Discounting dependent on
• Short-term pollution
• Source identified
• Predictable
• Public warned
• Measures are in place to reduce or eliminate causes
Smart Coasts project aims to address these issues to allow
discounting
• Deploy techniques including microbial source tracking to identify
sources of pollution
• Develop interim, black box and deterministic models
• Develop ICT technology to inform the public

8. The Smart Coasts Partnership

9. UCD interim model
Aimed at providing a short term solution to discounting
• Retrospective rainfall, hydrometric and microbial compliance
data in Ireland
• Regression and scatter plot analysis to predict FIB levels
Database construction using data obtained from EPA, OPW, Met Eireann,
Bathing water profiles to select catchments, gauges and identify types of
pollution.

10. Legend
Bathing water
quality in 2010
Good
Sufficient
Poor
Hydrometric gauges
Active
Inactive
Rainfall stations
River catchments
Lady’s Bay, Co. Donegal

11. UCD Interim model
A correlation between rainfall and indicator bacteria exists
Limited prediction of short term pollution for discounting

12. Data analysis shows that
rainfall is not the only
parameter affecting
microbial counts.
Bray Beach
Other factors need to
be taken into account to
develop a robust
predictive model of
short-term water
pollution

13. The Dargle Catchment and Bray Beach as a ‘test bed’
The Dargle catchment is
instrumented to measure
waterflow in Dargle and
tributaries
Rain gauges and weather
stations are installed
Sensors are dynamically
linked, and telemetry send
to UCD
Hydrodynamic model of
Dargle catchment and a
near shore model are being
built
ICT to develop real-time
public information system

14. Impacts of near shore events
• Wind
• Tide
• Sunshine
• Currents
Discharge of the Dargle into the Irish Sea
at Bray beach
Other impacts
• Rainfall in catchment
• Outfalls (storm overflows)
• Rivers entering bathing water
• Agricultural/human/wild life
activities in catchment area (s)

15. Deployment of a large field and laboratory team to sample the
dargle catchment during rainfall events and to do near shore and
beach sampling.
Hydrological data: salinity and temperature profile of water
column, water flow, currents and turbidity.
Microbiological data: E. coli, intestinal enterococci and microbial
source tracking analysis.

16. Effects of weather events on
Water quality parameters in the
Dargle catchment

17. Linking of catchment model(s) with near-shore hydrodynamic and
water quality models
N
*
High
Water
Flood
Water Surface Elevation (m)
at Ringsend

18. To understand the contamination in bathing waters one has to
understand the catchment.
Ecological status: Green > blue > red (Source: Environmental Source: Ordnance Survey Ireland
Protection Agency)
Validated robust markers for human, bovine, gull, porcine, ovine, dog
and equine faecal pollution

19. FIB profile of the Dargle Catchment
1e+6 1e+6
1e+5 1e+5
1e+4 1e+4
MPN/100 ml
MPN/100 ml
1e+3 1e+3
1e+2 1e+2
1e+1 1e+1
1e+0 1e+0
N
0
1
2
3
H
1
2
CU
R
O
R
N
0
1
2
3
H
1
2
CU
R
O
R
G
G
G
G
G
G
G
G
G
G
G
G
SW
CG
KG
CB
CS
SW
CG
KG
CB
CS
DR
DR
DR
DR
KM
KM
G
DR
DR
DR
DR
KM
KM
G
E. coli Enterococcus
Pristine, Powers Not so pristine (WWTP)
Court Waterfall

20. Application of qualitative markers in Dargle catchment
Bars represent
percentage of samples
testing positive over a 2
year period
Pollution matches land use
Some sites have mixed
pollution
Indication of sewage
misconnections

21. Quantitative real-time PCR allows accurate
determination of contribution of type of pollution
• Diffuse agricultural pollution
• Point source human pollution
1e+9 1e+9
1e+8 1e+8
1e+7 1e+7
1e+6 1e+6
gc/100 mL
gc/100 mL
1e+5 1e+5
1e+4 1e+4
1e+3 1e+3
1e+2 1e+2
1e+1 1e+1
G0 RG1 RG2 O G3 H G1 G2 R N U R
G0 RG1 RG2 O G3 H G1 G2 R N U R
DR CS DR KG KM CB SW GC GC CB SW GC
D D KM DR D D CS DR KG KM KM GC
Human qPCR Ruminant qPCR

22. Our experience so far suggests that less
than half the Irish bathing waters would
‘benefit’ from black box ‘Interim Model’
discounting alone.
Interim model is being refined
Deterministic, process based modelling
based on hydrological and microbiological
data is underway
Modelling tools will be designed to be
generic and transferable

23. University College Dublin Aberystwyth University
Wim Meijer
David Kay
Bartholomew Masterson
Mark Wyer
John O’Sullivan
Paula Hopkins
Greg O’Hare
Michael Bruen
Rem Collier
Joanne Chadwick
Miriam Alonso
Elisenda Ballesté i Pau
Zeinab Bedri
Diana Carvalho e Ferreira
Aisling Corkery
Louise Deering For further information:
Katalin Demeter www.smartcoasts.eu
Brian Dolan
Paul Hynds
Moises Sanchez Garcia
Olga Zlydareva
And ten very enthusiastic
summer students from
UCC, TCD and UCD