Presentation by Cara van Megchelen & Rob Swan, Cardno, at the Delft3D User Days - Australian Time zone: Inland to Estuary, during Delft Software Days - Edition 2020. Tuesday, 10 November 2020.

1. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Lake Turnover
Assessments using
Delft3D and SOBEK
An overview of the modelling
approach and pro’s & con’s of each
November 2020

2. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Today’s Speakers
Cara van Megchelen
Senior Water Engineer (Brisbane)
Rob Swan
Principal Water Engineer (Melbourne)

3. Lake Turnover Assessments using Delft3D and SOBEK
November 2020

4. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
THE BIG PICTURE
CHALLENGE'S
POTENTIAL
IMPROVEMENTS
What to Expect
CASE STUDY
METHODOLOGY

5. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
The Big Picture01

6. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
v
Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Creating Sustainable Lakes
> Urban lakes and ponds provide ecological
habitat
> They enhance the urban environment by
improving amenity and contributing to
reducing urban heat island effects
> Often constructed to enhance the aesthetics
within new residential urban estates
> Are a popular place for aquatic activities
Understanding lake and pond systems is integral
to successful design and implementation

7. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
v
Lake Turnover Assessments using Delft3D and SOBEK
November 2020
What is Turnover?

8. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
v
Lake Turnover Assessments using Delft3D and SOBEK
November 2020
> Approaches to model turnover
> Water balance
> Based on Qin / Qout
> Fast, but does not model variation within
the waterbody and does not consider
spatial variation, flow paths or velocity
> 1D hydraulic
> Fast and suitable for low risk simple
waterbodies
> 2D hydraulic or hydrodynamic
> Suitable for lakes and higher risk water
bodies
> 3D hydraulic or hydrodynamic
> Includes 3-dimensional affects such as
stratification and vertical velocities
Summary of Methods to Quantify Turnover

9. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Case Study –
Riverina Tidal Lake
02

10. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Residential development adjacent to a 3.5 ha feature lake located
along the Nerang River, South East Queensland
Key lake management considerations
> Quality of inflows
> 170 water quality observations in the river
> 2 x locations: 1km upstream & 1km downstream
> ~ Monthly between 2002 to 2018
> Sustainable water levels, flushing and mixing of the lake
> Tidal exchange via culvert connected to tidally influenced
river
> Management & prevention of high organic carbon loads
> Pre-treatment of stormwater runoff from urban areas prior
to entering the lake
Excerpt from landscape intent plan (sourced from drawing No. 8LA 190901-004) (8LA, 2020)
Designing an Aesthetic Lake

11. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Delft3D model developed to:
> Evaluate lake exchange
> Iterations were undertaken to select
culvert invert level and minimum size
> Assess the influence of freshwater inflows
during flood events
> Fish are susceptible to rapid changes in
salinity and / or temperature and hence
why this modelling was useful
Model to Predict Tidal Exchange Turnover
Tidal plane Water level (m
AHD)
Lake volume
(ML)
MSL 0.1 32.0
MHWS 0.6 47.0
HAT 1.01 59.7
Lake volume at various tidal planes
Tide water level projected at Nerang Township

12. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
> Key boundary conditions
> Lake inlet / outlet configurations
> Tidal water variation
> Duration
• Turnover modelling
❖ 2 months (first month run-up and the second
month to analyse)
• Freshwater inflow model timing based on the flood
hydrographs sourced from Glenhurst Station along
Nerang River
> Timestep 3 sec for tidal exchange 0.6 sec for freshwater
scenarios
> Grid 5m resolution
> Bathymetry based on LiDAR and functional design
Model Arrangement
Delft3D model bathymetry (Note: values are negative due to Delft3D input)
Scenario Lake
exchange
Culvert Level
(m AHD)
Description
Turnover Tidal 0.0 Culvert level slightly lower
than MSL
Freshwater A Flood event 0.0 March 2004 flood event
Freshwater B Flood event 0.0 January 2013 flood event
Model scenarios
Note: an overview of this project has been provided
and details can be discussed where there is further
interest.

13. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
> Lake water mixing & turnover driven by a tidal exchange
system
> Total Lake (i.e. surface, mid and bed layers) turnover
modelled to be less than 7 days
> Turnover found to be significantly faster than the
relevant guidelines (< 20 days) for lakes in South
East Queensland
> Reporting point located furthest from the
inlet/outlet
> Potential for water quality issues occurring due to long
Lake detention time minimised
> Cyanobacterial blooms due to poor mixing minimised
through the design of the Lakes tidal exchange system
0%
20%
40%
60%
80%
100%
30 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Concentration(%)
Time (days)
cTracer Concentration vs Time
cTracer - Bottom layer cTracer - Mid layer
cTracer - Surface layer eFolding
Lake turnover (culvert IL 0.0 m AHD, 2.1 m W x 0.9 m H)
Model to Predict Tidal Exchange Turnover

14. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Model to Predict Change in Salinity Behavior During Flood Events
Nerang River historic water level at Glenhurst (station No. 146002B)
0
0,5
1
1,5
2
2,5
3
3,5
5-3-2004 00:00 5-3-2004 12:00 6-3-2004 00:00 6-3-2004 12:00 7-3-2004 00:00 7-3-2004 12:00 8-3-2004 00:00
WaterLevel(mAHD)
Date
March 2004 Nerang River water level

15. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
0
5
10
15
5-03-2004 12:00 5-03-2004 18:00 6-03-2004 00:00 6-03-2004 06:00 6-03-2004 12:00
Salnity(ppt)
Time
Salinity Concentration Vs. Time
March 2004 Flood Event
Bottom layer Mid layer Surface layer
Change in Lake salinity – March 2004 flood event
Model to Predict Change in Salinity Behavior During Flood Events
March 2004 flood event, with a peak water level of
3.0mAHD, selected given similar water surface level
to the modelled 20% AEP event

16. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
> Design the waterbody to be visually aesthetic
> Designed to avoid problems in the lake as a result of
poor water quality
> Informed ecology decision making
> Inform sizing of tidal exchange pipes
> Challenges:
> Tidal data limited to monitoring locations
> Complex flooding behavior from the large
adjacent river
> Stormwater from urban development pre-treated
prior to discharging in to the lake system
Study Outcomes

17. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Case Study –
Ornamental Pond
02

18. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
> 1.6 ha ornamental pond
> Feature in an urban development located ~15 km east
of Melbourne
> Waterbody hydraulically connected to adjacent
catchments via an inlet to the north
> Stormwater runoff from a total residential catchment
area of 46.5 ha conveyed to the pond
Functional assessment
> Identification of criteria and relevant guidelines;
> Analysis of existing data;
> Development of a turnover model in SOBEK;
> Pond design and management of stormwater inflows;
and
> Development of a concept monitoring plan.
Ornamental Pond Design

19. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
The analysis included
• Water balance model calculates the volume of water over a
30-year period by accounting for:
• Inflow from the 46.5 ha catchment; and
• Water lost to evaporation.
Approach provides conservative results by excluding rainfall inflows
and additional mixing due to wind. Water lost by seepage through
the base excluded based on the outcomes of the geotechnical
investigation.
• Water balance and residence time model arrangement:
• Model duration 1984 – 2015;
• 30-minute interval for hydrodynamics & 2-hour interval for water
quality; and
• Results reported at 6 hourly time intervals.
Predict Turnover Driven by Stormwater

20. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Key SOBEK model inputs included
> Pond dimensions as per the functional design
> Catchment inflow time series
> Sourced from MUSIC
> Outlet pipe and weir dimensions
> Sourced from the functional design
> Daily evaporation (mm/day)
> Sourced from the closest rainfall station
Predict Turnover Driven by Stormwater

21. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
• SOBEK model of the pond and catchment inflows
developed to support the assessment
• The water quality performance criteria outlined in the
local permit conditions determined via results from
the SOBEK model
Risk of lakes developing algal blooms (MW, 2005)
Predict Turnover Driven by Stormwater

22. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
> Sufficient turnover in the pond via inflows
from the 46.5 ha catchment
• Volume exchange driven by frequent and
infrequent runoff events
> Permanent water level considered suitable
and sustainable
Modelled residence time (days)
Frequency Residence Time (days)
20th percentile 3.8
Mean 6.3
80th percentile 10.4
Maximum 57.9
Predict Turnover Driven by Stormwater

23. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Closing03

24. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
The potential for urban lakes to be utilised for recreational
activities can be limited by a number of constraints such
as the achieved water quality.
Creating Resilient Lake Environments
> Management options to resolve issues
> Planning for waterbodies
> Hydrodynamic modelling of small to large and complex
lakes
> Enables the modelling of more complex monitoring

25. Lake Turnover Assessments using Delft3D and SOBEK
November 2020
Thank you for listening
www.cardno.com
Cara van Megchelen
Senior Water Engineer (Brisbane)
+61 7 3877 6929
cara.vanmegchelen@cardno.com.au
Rob Swan
Principal Water Engineer (Melbourne)
+61 3 8415 7532
rob.swan@cardno.com.au