mike burch - waterra bur… · best case 14.4 2,000 0.03 1,000 1.8 0.07 most likely case 24 27,000...

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CYANOBACTERIA: CATCHMENT AND RESERVOIR MANAGEMENT STRATEGIES TO REDUCE RISK OF CYANOBACTERIAL BLOOMS FOR DRINKING WATER PRODUCTION AND RECREATIONAL ACCESS Mike Burch Visiting A/Professor, Department of Ecology & Evolutionary Biology

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Page 1: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

CYANOBACTERIA: CATCHMENT AND RESERVOIR MANAGEMENT

STRATEGIES TO REDUCE RISK OF CYANOBACTERIAL BLOOMS FOR

DRINKING WATER PRODUCTION AND RECREATIONAL ACCESS

Mike BurchVisiting A/Professor, Department of Ecology & Evolutionary Biology

Page 2: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Outline of Presentation

Ecology of Cyanobacteria

• How and why do they grow?

• The importance of phosphorus

Control and management of cyanobacteria

In Catchments• Nutrients

In Reservoirs• Nutrients

• Managing stratification – aeration & mixing

Conclusions

Page 3: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

• Cyanobacteria are a global problem• $A 180 - 240 million cost per annum to Australian economy

• $US 2.2 - 4.6 billion cost per annum to U.S. economy

• For example: ~$A 1 million per annum, to manage in Happy Valley Reservoir, South Australian Water Corporation

• Eutrophication and Climate Change may enhance magnitude and frequency of blooms – but unknown

• Impacts on both water and wastewater storages and recreational and urban ornamental lakes

• Difficult and expensive to remove by drinking water treatment processes

• No suitable treatment options are available for wastewater storages and recreational lakes

Issues

Page 4: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

1. Cyanotoxins

2. Odours – geosmin, MIB

The Problem: Cyanobacteria and Water Quality

Page 5: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Why do cyanobacteria grow? Important Ingredients for growth

Nutrients (Nitrogen & Phosphorus)

From either the catchment or sediments

Phosphorus concentration generally determines the maximum biomass of the cyanobacterial population

Light

Quantity & quality of light has a role in determining the species composition and may limit growth rate

Cyanobacteria prefer shallow mixing relative to light penetration

• Mixing depth/stratification characteristics are important

• Access to light is enhanced by buoyancy regulation

Temperature

Optimum range for growth: ~18-27 oC

Page 6: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Risk Matrix for the likelihood of occurrence & growth of Cyanobacteria

Environmental factor

Susceptibility

Category –

Risk

History of

Cyanobacteria

(inoculum

present)

Water

Temperature

(oC)

Nutrients:

Total Phosphorus

(g/L)

Thermal

Stratification

Very Low Risk No <15 <10 No

Low Yes <15-20 <10 Infrequent

Moderate Yes 20-25 10-25 Occasional

High Yes >25 25-100 Frequent and

persistent

Very High (Poor) Yes >25 >100 Frequent and

persistent /

strong

Page 7: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

How important are nutrients?- context for cyanotoxins

• A simple model has been developed, based only upon phosphorus concentration to predict the levels of toxins and odours that could be produced in reservoirs

• This simple model can be used to estimate “worst case challenges”

Page 8: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

How it works

The model calculations:

Phosphorus concentration is used to derive Chlorophyll ayield which can be modified for the scenario selected

Chlorophyll a is then translated to cell numbers of Microcystisor Dolichospermum using published cell/chlorophyll quotas

Cellular content or ‘cell quotas’ for geosmin, saxitoxin and microcystin are applied to estimate the likely yield of the cyanobacterial metabolites under the chosen scenarios.

Page 9: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Predicted concentrations of cyanobacteria and their metabolites

Reservoir

condition

with regard

to nutrient

status

Total

Phosphorus

μg L-1

Scenario

chosen:

Based upon

assumptions

about

growth and

cell quotas of

toxins and

odours

Soluble

Phosphorus

μg L-1

Microcystis

aeruginosa

cells mL-1

Microcystin

toxin

intracellular

μg L-1

Dolichosp

ermum

circinalis

cells mL-1

Geosmin

dissolved

ng L-1

Saxitoxin

μg L-1

(total)

Lower

nutrient

level

40

Best Case 14.4 2,000 0.03 1,000 1.8 0.07

Most Likely

Case

24 27,000 1.15 13,000 96 0.9

Worst Case 32 44,000 12.8 44,400 720 2.9

Current

nutrient

level

80

Best Case 28.8 4,000 0.06 2,000 3.6 0.13

Most Likely

Case

48 53,000 2.3 27,000 192 1.8

Worst Case 64 89,000 25.6 88,900 1440 5.9

Higher

nutrient

level

160

Best Case 57.6 8,000 0.12 4,000 7.2 0.26

Most Likely

Case

96 107,000 4.6 53,000 384 3.5

Worst Case 128 356,000 51.2 177,800 2880 11.7

Page 10: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Predicted concentrations of cyanobacteria and their metabolites

Reservoir

condition

with regard

to nutrient

status

Total

Phosphorus

μg L-1

Scenario

chosen:

Based upon

assumptions

about

growth and

cell quotas of

toxins and

odours

Soluble

Phosphorus

μg L-1

Microcystis

aeruginosa

cells mL-1

Microcystin

toxin

intracellular

μg L-1

Dolichosp

ermum

circinalis

cells mL-1

Geosmin

dissolved

ng L-1

Saxitoxin

μg L-1

(total)

Lower

nutrient

level

40

Best Case 14.4 2,000 0.03 1,000 1.8 0.07

Most Likely

Case

24 27,000 1.15 13,000 96 0.9

Worst Case 32 44,000 12.8 44,400 720 2.9

Current

nutrient

level

80

Best Case 28.8 4,000 0.06 2,000 3.6 0.13

Most Likely

Case

48 53,000 2.3 27,000 192 1.8

Worst Case 64 89,000 25.6 88,900 1440 5.9

Higher

nutrient

level

160

Best Case 57.6 8,000 0.12 4,000 7.2 0.26

Most Likely

Case

96 107,000 4.6 53,000 384 3.5

Worst Case 128 356,000 51.2 177,800 2880 11.7

Page 11: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

What it Means

Even at relatively low concentrations of phosphorus the potential toxin and odour levels are still quite high

This suggests it is very difficult or impossible to reduce and control nutrients in the reservoir to a level that is low enough to manage toxin & odour issues

In reality, the actual magnitude of the risk over a season is determined by:

• the period of time that favourable growth conditions persist

• the carrying capacity of the reservoir (the total algal biomass that the physico-chemical conditions that the reservoir will support) and

• the types and effectiveness of management actions that can be implemented

Page 12: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Setting Phosphorus Targets

Triggers Based on Scientific Literature

• There is a large amount of published information on the relationship between nutrients, specifically phosphorus and the growth of algae in lakes.

• Several early studies from the 1960’s & 70’s established a clear relationship between Total-P and chlorophyll, as a measure of algal biomass in temperate lakes

• An important study specifically predicting cyanobacterial occurrence and dominance based upon Total-P is by Downing et al (2001)

• This study evaluated data from 99 lakes of the temperate zone and included 269 observations in the data.

• The lakes were from around the world, however there was predominance of sites in the northern hemisphere.

The University of Adelaide Slide 12

Page 13: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Setting Phosphorus Targets

Triggers Based on Scientific Literature

The study found that the risk of cyanobacterial dominance to be correlated to the TP- concentration as follows:

• 0 - <0.030 mg/L TP: 0-10% risk of cyanobacterial dominance

• 0.030 - 0.070 mg/L TP: 40% risk

• >0.10 mg/L TP: ca. 80% risk

The University of Adelaide Slide 13

Page 14: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

▪ Physical Control

▪ External

▪ Chemical Control

▪ Non-Chemical Control

▪ Biological Control

▪ Internal

▪ Nutrient Control

▪ Selective off-take

▪ Mixing - Destratification

▪ Dilution to decrease retention time

▪ Algaecides

▪ Aeration & mixing

▪ Oxygenation (hypolimnetic)

▪ Sediment “capping” with P-bindingagents e.g. Modified clay, Lime, Alum

▪ Biomanipulation

▪ Viruses, bacteria, exotic algae

▪ Catchment management

▪ Novel Technology (e.g. ultrasound)

Management of Cyanobacteria: Control Options

Page 15: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

▪ Physical Control

▪ External

▪ Chemical Control

▪ Non-Chemical Control

▪ Biological Control

▪ Internal

▪ Nutrient Control

▪ Selective off-take

▪ Mixing - Destratification

▪ Dilution to decrease retention time

▪ Algaecides

▪ Aeration & mixing

▪ Oxygenation (hypolimnetic)

▪ Sediment “capping” with P-bindingagents e.g. Modified clay, Lime, Alum

▪ Biomanipulation

▪ Viruses, bacteria, exotic algae

▪ Catchment management

▪ Novel Technology (e.g. ultrasound)

Management of Cyanobacteria: Control Options

Page 16: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Managing Nutrients

External Sources

Options are available to reduce nutrients in the catchment:

• Removing point sources to streams (WWTP, Agriculture)

• On the land - Improving capture in the catchment

• In the stream - weirs, sedimentation basins & wetlands

Page 17: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Nutrients & Biomass: External sources (catchment)Example from Myponga Reservoir

In this reservoir the nutrient load in winter determines the phytoplankton carrying capacity (maximum biomass) in the following summer

Nutrient inputsDominated by winter rainfall events

High load = high flow * high concentrations

Consequently nutrient loading and seasonal algal biomass is affected by inter-annual rainfall variability

Page 18: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Myponga Reservoir: Annual Inflow Volume (1978-2000: 22 years)

0

4000

8000

12000

16000

20000

19

78

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

19

98

20

00

Year

To

tal

ye

arl

y i

nfl

ow

(M

L)

Page 19: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Myponga Reservoir: Inflow vs. Mean Summer Algal Biomass

4

6

8

10

12

14

16

18

20

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Total yearly inflow (ML)

Mean

Ch

la D

ec-M

ay (

mg

L-1

)

Series1

Series2

Page 20: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Intercepting Nutrients: Sedimentation Basins & Wetlands

Page 21: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Managing Nutrients

Internal Sources

Options to stop internal release of nutrients from sediments:

• Oxygenate the sediments by mixing or direct air or oxygen injection

• Sediment capping agents – Alum, Lime, Modified clays

Page 22: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

The Importance of Stratification: Growth & Nutrient Supply

P PN NP

N

Nutrients fromcatchment

Page 23: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Reducing sediment nutrient release – Aeration

Page 24: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Reducing sediment nutrient release with capping agents - Alum, Lime, Modified Clay

Principle: Remove + prevent release

• Strip the phosphorus from the water

• Sediment it to the bottom

• Bind it to make it unavailable for algal growth

Page 25: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Sediments

Sediments Dose (g/core)

Thickness(mm)

Lanthanum-modified clay

1(406 g m-2)

2

Alum 0.2 (81.2 g m-2)

10Loosely packed

CaCO3 1(406 g m-2)

2

Sediment capping experiment

Page 26: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Alum

• Alum has been widely used for phosphorus removal in lakes (Cooke et al. 2005). It is the most common flocculation agent which binds with FRP in the lake water, even under anoxic conditions, and settles to the lakebed.

• Alum sulphate may decrease pH in waters with low buffering capacity, which leads to solubilization and problems of toxicity.

Page 27: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Lime: Calcium Carbonate (CaCO3)

• Limestone

• crushed and finely ground

• Surface coverage: 1.3 m2g-1;

• mean particle diameter, 3500 µm

• Produces calcium phosphate

• hydroxyapatite (Ca5(PO4)3(OH), HAP)

Page 28: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Lanthanum-modified clay

The mechanism of P-removal by Lanthanum-modified clay involves the reaction of phosphate anions with La, leading to formation of a single insoluble species of lanthanum phosphate, or rhabdophane

Page 30: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Lanthanum-modified clay

Advantages & Issues

• The lanthanum–phosphate complex is known to be highly insoluble and able to form even when present in low concentrations and at low pHvalues.

• However depending upon the concentration and application rates, lanthanum can be toxic to some aquatic life

Page 31: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Observations - Suggestions

• Controlling nutrient release from sediments is not an ideal substitute for a reduction in the external nutrient load in the catchment

• All P-binding agents will be ineffective when they are buried by fresh sediment deposits

• Repeat & on-going treatment may be required.

• These treatments may require large amounts of chemicals

• A combination of treatments may be successful.

Page 32: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Physical Control

by….

• Mixing & Aeration to disrupt stratification and stability

• This allows for cells to mix down out of the light

Page 33: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

What can we do about stratification?

Artificial destratification

• Bubble-plume aerators

• Surface-mounted mechanical mixers

Aims

• mix reservoir to limit the light available to cyanobacteria

• oxygenate the deep layers (hypolimnion) to reduce release of nutrients and metals from sediment

Page 34: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Mixing by Aeration

Air Diffuser

Water Entering the

Plume

Intrusion

Surface Heating In Shallow Water

Page 35: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Surface-Mounted Mechanical

Mixers - Downflow Type

Myponga Reservoir, South Australia

Page 36: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Intrusion

Surface-Mounted Mixers: Desired effect on Cyanobacteria

Page 37: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Conclusions - Aerators

The Aerator used at Myponga Reservoir was effective:

• Achieved destratification & controlled Fe & Mn

• Reduced cyanobacterial growth to some extent but not summer surface blooms

The Surface Mixers

• Can contribute to reducing Dolichospermum numbers

• Can only have a significant impact if the flow rate is >> 5 m3s-1

• The mixers may have a limited zone of influence and poor circulation effect

• Required high maintenance (of the early experimental design) relative to aerators

Page 38: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Conclusions – Nutrients & Mixing

Control of nutrient inputs is an important target• Maximum summer biomass is determined by the nutrient load

Artificial destratification with aerators & mixers can influence the light climate and reduce cyanobacterial total population size • Can suppress some of the internal nutrient load (deep reservoirs)

To manage cyanobacteria in a given reservoir need to understand the conditions that favour or limit growth• Water Chemistry

• Hydrodynamics

Page 39: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Conclusions - General

It is impossible to eliminate cyanobacteria completely, but management interventions can reduce the intensity and frequency of blooms. In addition, controlling growth can reduce the occurrence & magnitude of cyanotoxins, tastes and odours

• Nutrients: Catchment management is important as the maximum size of cyanobacterial biomass is determined by nutrient load

Reduction in the internal load nutrient load by sediment treatment is a short-term technique

• Algaecides: Can control cyanobacteria in the short term however they may have adverse environmental effects

• Destratification: Aerators and mixers can influence the light climate and reduce cyanobacterial total population size and reduce the internal nutrient load - but they are only likely to be effective in deep reservoirs

• Ultrasound: The application of ultrasound for cyanobacterial control remains under question because of the limited number of both validated field and pilot tests and the feasibility of commercial devices for use in larger water bodies.

• Biomanipulation: Biological approaches – supporting zooplankton grazing by managing fish or supporting re-colonisation of shallow areas of a water body with macrophytes requires extensive local biological knowledge and may only work at lower phosphorus levels

• Monitoring: It is important to study your reservoir and understand the conditions that both favour and limit cyanobacterial growth including Chemistry, Temperature structure, & Hydrodynamics

Page 40: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Water Research Australia Water Research FoundationSouth Australian Water CorporationAustralian Water Quality CentreCRC for Water Quality & Treatment

Prof Justin BrookesDr Peter HobsonDr Sandy DicksonMr Peter BakerDr Leon van der LindenDr Rudi RegelDr David Lewis Professor Chris ChowMs Renate Velzeboer Dr Dennis SteffensenProf Tsair-Fuh Lin

Acknowledgements

Page 41: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Stage 1 – Ongoing Stage 2 – next 3-6 months Stage 3 – next 18 months Stage 4 – next 36 months

WaterAR#1123/WRF#4912: Developing Guidance for Evaluation of Harmful Algal Blooms, project link: https://www.waterra.com.au/project-details/252

Technology readiness level for an info bank via WRF (Only data collection, no trials):• Algal bloom early warning systems, &• Mitigation technologies

Example of ranking colour coded tables:

Events:• 2nd April 2020 utility focus virtual

meeting: Presentations by “Research team from US, CA & AU” + “Selected Australian utilities” + virtual workshop to document experiences and build opportunities

Team:

WaterRA project link: https://www.waterra.com.au/research/current-opportunities/2020/protocols-for-algal-bloom-management-technology-performance-and-optimisation-assessments/

Creation of protocols for scientific assessment/trial of algal bloom management technologies (pilot & full scale): Monitoring, growth control, lysis & mitigation, etc.

Approach: • Collection of scientific literature to draft

protocols (WaterRA) using lessons learnt from “Stage 1” & 9 principals of WaterVal

• Creation of a protocol development group (subject matter experts) to review the protocols

• Selection of an independent accessor to validate these protocols (pilot/full trails)

• Dissemination of the outcome via paper publications & factsheets

Team: • Melbourne Water is engaged with

recommissioning Yan Yean pilot plant (from March 2020): Site for pilot protocol development/trials

• Seeking $80K sponsorship

IWN Technology Trial:

To trail an ultrasound tech buoy (new version with new frequencies to limit algal growth) using protocols developed and verified during “Stage 2”.

Team:

WaterRA, Melbourne Water & IWNproposal: Establish a training & tech-transfer hub at Melbourne Water Yan Yean pilot plant ($800K facility) for Australian operator training & innovative technology pilot trials

Training material includes but not limited to: • Protocols developed at Stage 2• WaterVal protocols • AOP (UV-Cl2, UV-H2O2, etc.) protocols &

set-up from WaterRA#3046/WRF#5050 project

• Testing facility for new technologies

Team & ongoing/proposed projects:

• WaterRA#4528 UNSW PhD student using Yan Yean pilot for T&O removal by GAC/BAC

• WaterRA#1136 Monash ARC EES Hub using the pilot to assess application of hydrogen economy based AOP

• WaterRA#1137 Monash ARC EES Hub using the pilot for assessment of an mobile RO emergency water treatment module

To approach for further collaborations:WSAA – AWA – WIOA; NSW water directorate –qldwater – Water New Zealand; Australian Water Partnership – The WRF (LIFT) – GWRC; ICE WaRM –International Water Centre; Isle Utilities – GHD –Jacobs

Focus on algal bloom management: WaterRA strategy to facilitate novel technology transfer into the water industry!

Page 42: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Stage 1 – Ongoing Stage 2 – next 3-6 months Stage 3 – next 18 months Stage 4 – next 36 months

WaterAR#1123/WRF#4912: Developing Guidance for Evaluation of Harmful Algal Blooms, project link: https://www.waterra.com.au/project-details/252

Technology readiness level for an info bank via WRF (Only data collection, no trials):• Algal bloom early warning systems, &• Mitigation technologies

Example of ranking colour coded tables:

Event:• 2nd April 2020 utility focus virtual

meeting: Presentations by “Research team from US, CA & AU” + “Selected Australian utilities” + virtual workshop to document experiences and build opportunities

Team:

WaterRA project link: https://www.waterra.com.au/research/current-opportunities/2020/protocols-for-algal-bloom-management-technology-performance-and-optimisation-assessments/

Creation of protocols for scientific assessment/trial of algal bloom management technologies (pilot & full scale): Monitoring, growth control, lysis & mitigation, etc.

Approach: • Collection of scientific literature to draft

protocols (WaterRA) using lessons learnt from “Stage 1” & 9 principals of WaterVal

• Creation of a protocol development group (subject matter experts) to review the protocols

• Selection of an independent accessor to validate these protocols (pilot/full trails)

• Dissemination of the outcome via paper publications & factsheets

Team:• Melbourne Water is engaged with

recommissioning Yan Yean pilot plant (from March 2020): Site for pilot protocol development/trials

• Seeking $80K sponsorship

IWN Technology Trial:

To trail an ultrasound tech buoy (new version with new frequencies to limit algal growth) using protocols developed and verified during “Stage 2”.

Team:

WaterRA, Melbourne Water & IWNproposal: Establish a training & tech-transfer hub at Melbourne Water Yan Yean pilot plant ($800K facility) for Australian operator training & innovative technology pilot trials

Training material includes but not limited to: • Protocols developed at Stage 2• WaterVal protocols • AOP (UV-Cl2, UV-H2O2, etc.) protocols &

set-up from WaterRA#3046/WRF#5050 project

• Testing facility for new technologies

Team & ongoing/proposed projects:

• WaterRA#4528 UNSW PhD student using Yan Yean pilot for T&O removal by GAC/BAC

• WaterRA#1136 Monash ARC EES Hub using the pilot to assess application of hydrogen economy based AOP

• WaterRA#1137 Monash ARC EES Hub using the pilot for assessment of an mobile RO emergency water treatment module

To approach for further collaborations:WSAA – AWA – WIOA; NSW water directorate –qldwater – Water New Zealand; Australian Water Partnership – The WRF (LIFT) – GWRC; ICE WaRM –International Water Centre; Isle Utilities – GHD –Jacobs

Focus on algal bloom management: WaterRA strategy to facilitate novel technology transfer into the water industry!

Page 43: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Stage 1 – Ongoing Stage 2 – next 3-6 months Stage 3 – next 18 months Stage 4 – next 36 months

WaterAR#1123/WRF#4912: Developing Guidance for Evaluation of Harmful Algal Blooms, project link: https://www.waterra.com.au/project-details/252

Technology readiness level for an info bank via WRF (Only data collection, no trials):• Algal bloom early warning systems, &• Mitigation technologies

Example of ranking colour coded tables:

Event:• 2nd April 2020 utility focus virtual

meeting: Presentations by “Research team from US, CA & AU” + “Selected Australian utilities” + virtual workshop to document experiences and build opportunities

Team:

WaterRA project link: https://www.waterra.com.au/research/current-opportunities/2020/protocols-for-algal-bloom-management-technology-performance-and-optimisation-assessments/

Creation of protocols for scientific assessment/trial of algal bloom management technologies (pilot & full scale): Monitoring, growth control, lysis & mitigation, etc.

Approach: • Collection of scientific literature to draft

protocols (WaterRA) using lessons learnt from “Stage 1” & 9 principals of WaterVal

• Creation of a protocol development group (subject matter experts) to review the protocols

• Selection of an independent accessor to validate these protocols (pilot/full trails)

• Dissemination of the outcome via paper publications & factsheets

Team: • Melbourne Water is engaged with

recommissioning Yan Yean pilot plant (from March 2020): Site for pilot protocol development/trials

• Seeking $80K sponsorship

IWN Technology Trial:

To trail an ultrasound tech buoy (new version with new frequencies to limit algal growth) using protocols developed and verified during “Stage 2”.

Team:

WaterRA, Melbourne Water & IWNproposal: Establish a training & tech-transfer hub at Melbourne Water Yan Yean pilot plant ($800K facility) for Australian operator training & innovative technology pilot trials

Training material includes but not limited to: • Protocols developed at Stage 2• WaterVal protocols • AOP (UV-Cl2, UV-H2O2, etc.) protocols &

set-up from WaterRA#3046/WRF#5050 project

• Testing facility for new technologies

Team & ongoing/proposed projects:

• WaterRA#4528 UNSW PhD student using Yan Yean pilot for T&O removal by GAC/BAC

• WaterRA#1136 Monash ARC EES Hub using the pilot to assess application of hydrogen economy based AOP

• WaterRA#1137 Monash ARC EES Hub using the pilot for assessment of an mobile RO emergency water treatment module

To approach for further collaborations:WSAA – AWA – WIOA; NSW water directorate –qldwater – Water New Zealand; Australian Water Partnership – The WRF (LIFT) – GWRC; ICE WaRM –International Water Centre; Isle Utilities – GHD –Jacobs

Focus on algal bloom management: WaterRA strategy to facilitate novel technology transfer into the water industry!

Page 44: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Stage 1 – Ongoing Stage 2 – next 3-6 months Stage 3 – next 18 months Stage 4 – next 36 months

WaterAR#1123/WRF#4912: Developing Guidance for Evaluation of Harmful Algal Blooms, project link: https://www.waterra.com.au/project-details/252

Technology readiness level for an info bank via WRF (Only data collection, no trials):• Algal bloom early warning systems, &• Mitigation technologies

Example of ranking colour coded tables:

Event:• 2nd April 2020 utility focus virtual

meeting: Presentations by “Research team from US, CA & AU” + “Selected Australian utilities” + virtual workshop to document experiences and build opportunities

Team:

WaterRA project link: https://www.waterra.com.au/research/current-opportunities/2020/protocols-for-algal-bloom-management-technology-performance-and-optimisation-assessments/

Creation of protocols for scientific assessment/trial of algal bloom management technologies (pilot & full scale): Monitoring, growth control, lysis & mitigation, etc.

Approach: • Collection of scientific literature to draft

protocols (WaterRA) using lessons learnt from “Stage 1” & 9 principals of WaterVal

• Creation of a protocol development group (subject matter experts) to review the protocols

• Selection of an independent accessor to validate these protocols (pilot/full trails)

• Dissemination of the outcome via paper publications & factsheets

Team: • Melbourne Water is engaged with

recommissioning Yan Yean pilot plant (from March 2020): Site for pilot protocol development/trials

• Seeking $80K sponsorship

IWN Technology Trial:

To trail an ultrasound tech buoy (new version with new frequencies to limit algal growth) using protocols developed and verified during “Stage 2”.

Team:

WaterRA, Melbourne Water & IWNproposal: Establish a training & tech-transfer hub at Melbourne Water Yan Yean pilot plant ($800K facility) for Australian operator training & innovative technology pilot trials

Training material includes but not limited to: • Protocols developed at Stage 2• WaterVal protocols • AOP (UV-Cl2, UV-H2O2, etc.) protocols &

set-up from WaterRA#3046/WRF#5050 project

• Testing facility for new technologies

Team & ongoing/proposed projects:• WaterRA#4528 UNSW PhD student using

Yan Yean pilot for T&O removal by GAC/BAC

• WaterRA#1136 Monash ARC EES Hub using the pilot to assess application of hydrogen economy based AOP

• WaterRA#1137 Monash ARC EES Hub using the pilot for assessment of an mobile RO emergency water treatment module

Focus on algal bloom management: WaterRA strategy to facilitate novel technology transfer into the water industry!

Page 45: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level

Resources

https://www.waterra.com.au/publications/

Page 46: Mike Burch - WaterRA Bur… · Best Case 14.4 2,000 0.03 1,000 1.8 0.07 Most Likely Case 24 27,000 1.15 13,000 96 0.9 Worst Case 32 44,000 12.8 44,400 720 2.9 Current nutrient level