1. HEADLINE TO BE PLACED IN
Dynamic Habitat Program
Sunil Sharma, Simon Benger and Jason Tanner
CLLAMMecology Research Cluster partners:
2. Dynamic Habitat Report Sections
Sharma, S. K., Tanner, J.E. & S. Benger, 2009. Digital Elevation Model for
the Coorong and surrounding areas.
Sharma, S. K., Benger, S., Fernandez, M. & J.E. Tanner, 2009. Sediment
mapping of the Coorong: implications for habitat distributions.
Sharma, S. K., Benger, S. & J.E. Tanner, 2009. Habitat Mapping of the
Coorong and Surrounds.
Benger, S., Sharma, S.K., and J.E. Tanner, 2009. Mudflat geomorphology
and availability at varying water levels in the Coorong.
Sharma, S. K., Benger, S., Tanner, J.E. & I.T. Webster, 2009. Spatial
Modelling of mudflat availability and fish habitat in the Coorong.
3. Bathymetry for the Murray Mouth and the South Lagoon
-Needed to address data gaps
-Allows for volumetric analyses
of the lagoons
-Not possible to survey completely
-Modelled from Landsat and
4. Bathymetry for the Murray Mouth and the South Lagoon
Depth in metres AHD
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106 113 120 127 134 141 148 155 162 169 176 183 190
Depth locations from Parnka Point to Salt Creek
Modelling used Generalised Additive Model for predicting a response
variable y at i location with predictive variables xij
yi = β 0 + ∑S
i =1, j =1
j ( xij )
Depth = β0 + S1(x) + S2(y) S3(Ls1) + S4(Ls 2) + S5(Ls 3) + S6(Ls 4) +
S7(Ls 5) + S8(Ls 6) + S9(Ls7) + S10(Sp1) + S11(Sp2) + S12(Sp3)
5. Sediment Modelling
Response curves for predictor variables and mean grain size for the final 5 variable model for the North
Lagoon. The solid line is the smooth function of the explanatory variable, while the dashed lines indicate
the 95% confidence region. The rugplot indicates the values of the predictor variables for which
observations were available.
Generalized Additive Modelling (GAM) was used to assess the relationship between the sediment characteristics
measured and a range of potential predictor variables
g(SA)= β0 + s(Northing) + s(Easting) + s(Depth) + s(Slope) +
s(Aspect) + s(distance to the east shore) + s(distance to (1)
the west shore) + s(Nearest distance to shore) +
s(distance from the Murray Mouth) + s(salinity)
6. Sediment Modelling
7. Quantifying Habitat
Habitat in the Reference Sites was quantified using remote
sensing, underwater videography, fieldwork, DEH mapping.
A habitat classification scheme with 12 descriptors encompassing
a range of geographical, physical, chemical and biological
characteristics was developed
Habitat Zone Habitat Type
Habitat category Salinity
Wetland system Cover Percent
Water Regime Habitat Condition
Wetland Type Habitat Area
8. Quantifying Habitat
9. Habitat Mapping
10. HEADLINE TO BE PLACEDhabitat for many species in the Coorong, in particular wader
Mudflats form critical IN
Maximising the productivity of mudflats, through maintaining water levels and
water quality is essential for ensuring the Ramsar status of the Coorong by
providing coastal foraging habitat required by migratory birds.
Healthy mudflats support large and diverse macroinvertebrate populations, are
important as fish breeding areas and form substrate for submerged aquatic
vegetation such as Ruppia species. Restoring the productivity of the Coorong
mudflats is an important conservation goal for the region.
CLLAMMecology Research Cluster partners:
11. Mudflat Morphology
12. Mudflat Morphology
Hypsometric Curves for
each Reference Site
Also characterised mudflat slope and area
for a range of elevation classes
13. Mudflat Morphology
The characterisation of mudflat morphology
allows for detailed estimates of mudflat
habitat availability at different water levels.
Study confirms the importance of the
South Lagoon in terms of mudflat
habitat, as it contains some 61% of
available mudflat as measured in the
Mudflat areas at elevations between 0m and 0.5m AHD yield the greatest
availability of habitat and suggest that manipulations of water level should be kept
within this range.
Most important elevation range is 0.2m to 0.4m AHD, as manipulations in this range
accomplish wetting and drying of the maximum area of mudflat, most of which is
found in the South Lagoon.
Mudflats throughout the Coorong are generally likely to be geomorphically stable with
mean mudflat slopes averaging 0.72%.
14. Linking to the Hydrodynamic Model of Webster (2007)
Locations of water level and salinity data points generated through the
hydrodynamic model. (Where GC = Goolwa Channel; MC = Mundoo Channel;
EI = Ewe Island; BK = Barker Knoll; PP = Pelican Point; MP = Mark Point; LP =
Long Point; NM = Noonameena; PA = Parnka Point; VY = Villa dei Yumpa; JP
= Jack Point and SC = Salt Creek.
15. Linking the Hydrodynamic Model to Habitat
The hydrodynamic model simulates water level and salinity for
117 years (the period between 1891 and 2008) in combination
with an inflow model.
For habitat modelling of the Coorong, we chose to predict habitat
availability for the baseline scenario (Scenario A - the current state
of agricultural development and current water management rules
from CSIRO Sustainable Yields).
Two ‘very wet’ and ‘very dry’ years in the past decades were
selected for a comparison of habitat availability under these
Under scenario A, we identified 1976 and 1993 as wet years; and
1988 and 2005 as dry years. The hydrodynamic model was run for
these years and water level and salinity data were linked to the
geographical coordinates of the respective points.
17. The Dynamic Habitat Model
Part A Part B Part C Part D
The fine resolution bathymetry (1 m2), water level data from the
hydrodynamic model and a boundary layer covering up to the high water
mark level were used to predict the spatial-temporal availability of mudflat
habitats in the Coorong.
The model is composed of six model parameters (blue ovals) and uses 12
processes (yellow rectangles) and generates 12 outputs (green ovals)
including 9 intermediate and 3 final outputs:
Exposed Area (WL to HW), Mudflat area (Eastern Shore), Mudflat area
18. The Dynamic Habitat Model
Mudflat area (ha) 3.00
-0.30 -0.14 -0.07 0.00 0.09 0.18 0.20 0.26 0.31 0.34 0.56 0.72 0.87 1.17
Mean water level (mAHD)
Eastern shore Western shore Channel Total
Mudflat availability on the eastern shore, western shore,
channel and the total areas at different water levels at
19. The Dynamic Habitat Model
Water Level (mAHD)
Mudflat area (ha)
6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00
Hours (22 Jan. 1976)
Mudflat - Barker Knoll Mudflat - Noonameena
Mudflat - Salt Creek Water Level - Barker Knoll
Water Level - Noonameena Water Level - Salt Creek
Mudflat availability and water levels between 6:00 - 20:00 at three reference sites
on 22 Jan. 1976. The average water level on this day was the monthly maximum for
20. Predicting fish habitat based on fish occurrence probability using logistic regression
21. Model coefficients and parameters for seven key species in the Coorong.
22. Habitat prediction for Smallmouth Hardyhead in July 1976, July 1988 and
23. Habitat prediction for Yelloweye Mullet in July 1976, July 1988 and January 2005
24. The Dynamic Habitat Model: Conclusions
Salinity range from 5 to 90 g/L along the Lagoon was best in terms of the
suitability of entire Lagoon for the four key fish species as well as supporting other
important biological communities including both macrophytes and infauna.
Analysis of mudflat availability at different water levels suggests that average water
level of 0.12m AHD gives the maximum average mudflat area.
Outputs depict the mudflat areas up to 12 cm depth from the water level at 1 cm
vertical resolution. Waterbirds are specific in their prey and are specialized in their
use of mudflats under different water depths. Possible to model the relationship
between different waterbirds and their requirements at particular depths.
These spatial models can be a management tool allowing quantification of habitats
for key species for specified flow scenarios and can inform decisions on the amount
and frequency of barrage outflows once the Lower Lakes are recharged and excess
water is available for the Coorong.