Integrating 3D Hydrodynamic Modelling into DSS in a Large Drinking Water Utility. Dr Kathy Cinque and Dr Peter Yeates

Transcription

1 Integrating 3D Hydrodynamic Modelling into DSS in a Large Drinking Water Utility Dr Kathy Cinque and Dr Peter Yeates

2 Presentation Overview Melbourne Water System Water quality and risk management Modelling capabilities Decision Support System (DSS) Components Case Studies Recent modelling project Future direction

3 Melbourne Water Supply drinking and recycled water and manage Melbourne's water supply catchments, sewage treatment and rivers, estuaries and wetlands Drinking water 4.1 million customers 10 storage reservoirs Biggest reservoir = 1,068 GL (280,000 million gallons) Smallest reservoir = 3 GL (790 million gallons) Protected water supply catchments Total area = 1,600 km 2 (400,000 acres) 80% of water supplied is unfiltered but disinfected

4 Location of Melbourne, Australia Melbourne

5 Melbourne Water supply system

6 Risk management Unfiltered supply means our reservoirs are an important barrier to contamination Detailed understanding of hydrodynamics and water quality is paramount to ensuring safe drinking water Fate and transport of pollutants Risk of algal blooms Event management Impact of changes in operation Strategic planning

7 Decision Support System (DSS) framework Provides a single point of access

8 3D Hydrodynamic Model Hydrodynamics - ELCOM Uses an orthogonal grid Simulates temporal behaviour of water bodies with environmental forcing Models velocities, temperatures, salinities and densities Biogeochemistry - CAEDYM Represents the major biogeochemical processes influencing water quality, including sediment

9 Hydrodynamic modelling at Melbourne Water Drinking water reservoirs for over 10 years Significant investment 10 LDS s in 7 reservoirs Development of integrated modelling platform (ARMS) Dedicated in-house modeller Real-time and scenario analysis Wastewater treatment plant mixing zone studies Estuary research seagrass, mangroves, toxicants

10 Case Studies 1. Cardinia Reservoir Desalinated water inlet shute location Inform capital investment 2. Sugarloaf reservoir Aerator operation/augmentation Optimise operational decisions 3. Upper Yarra Reservoir High turbidity inflow event Incident management and response

11 1. Cardinia Reservoir Inform capital investment Reservoir capacity 287 GL Surface area 3,200 acres Water stored is from protected catchments, unfiltered Desalinated water to be added to natural water Model objective Best location for inlet to ensure mixing and dilution Ensure consistency of water quality at outlet

12 Model set-up 100 x 100 x 1m grid used 4 locations modelled for each season, aerator on/off

13 Proposed inlet location

14 1. Cardinia Reservoir Inform capital investment Desal water is warmer than reservoir water so restricted to top layers Mixing highly influenced by wind Recommended location ensure mixing and consistent outlet water quality Outcomes Recommended inlet shute location adopted by the Capital team Tens of millions of dollars saved by optimising site location

15 2. Sugarloaf Reservoir Optimise operational decisions Reservoir capacity 96 GL Maximum depth 89 m Reservoir stratifies causing reduction in DO in bottom waters causing leaching of Fe and Mn into water column, subsequent biofilm build up in distribution mains Existing aerator to deepen thermocline Model objective How efficient is the current aerator? Is there a need to retrofit/replace/duplicate/relocate? How does the aerator s operation affect its effectiveness?

16 Sugarloaf Reservoir model set-up 60 x 60m grid 60 second time-step 8 month simulation period Inputs = inflow rate and temp and meteorological conditions Calibration LDS and grab samples

17

18 2. Sugarloaf Reservoir Optimise operational decisions Outcomes Aerator location means it will not mix entire water column Grab samples and LDS are in a hole giving false indication of mixing in the remainder of reservoir Current aerator operation confines Mg to bottom waters and deepens thermocline Turning aerator on after December means waiting a month for the thermocline to be lowered

19 3. Upper Yarra Reservoir Incident management and response Drowned riverbed reservoir 84,000 acre protected catchment Risk of human infectious pathogens is very low but storm events can impact aesthetic water quality June 2012 large storm Model objective Predict travel times and dilution of dirty water Assist in operational decisions

20 Turbidity event in Upper Yarra 9 km (5.5 miles)

21 Measured vs modelled

22 Predictive turbidity modelling

23 3. Upper Yarra Reservoir Incident management and response Outcomes Turbidity remained below 15 NTU at the dam wall - as predicted Reservoir remained in operation based on predicted inflow intrusion being below offtake height Model run in real-time to track turbidity and assist with sampling Prevented issuing a boil water notice saving millions of dollars

24 Outcomes Broad range of operational circumstances and planning initiatives DSS with integrated data and model provides a platform to efficient quantitative risk assessment Accessible use and easy dissemination of information Significant investment over 10 years to develop this capacity Used to minimize the impact of what could have been serious incidents shows return for investment Communication of initiative with Vic. Dept. Health has resulted in confidence in the approach and acceptance of the tools

25 The future of modelling at Melbourne Water... is now!! Hydrodynamic and water quality modelling in bays and estuaries Predictive algal modelling in drinking water Pathogen fate and transport Wastewater treatment plant mixing zone studies Estuary research seagrass, mangroves, toxicants Coupling catchment runoff models to receiving water models

26 Thank-you for listening! Dr Kathy Cinque Dr Peter Yeates