Presentation by Ary van der Lely to the Riverina branch of the Australian Society of Soil Science at a meeting on 16 Aug 2013

1. STRATIGRAPHICAL MODEL
of the
MIA
ILLUSION OR REALITY ?

2. History of Drilling
A lot of time and money !

3. Bore Log Description

5. WHY IS STRATIGRAPHICAL INFORMATION
IMPORTANT ?
1. UNDERSTANDING GROUNDWATER BEHAVIOUR
2. RICE LAND CLASSIFICATION
3. COMPUTER MODELS NEED INPUT
4. DRAINAGE APPLICATIONS
5. OTHER ?

6. UNDERSTANDING GROUNDWATER BEHAVIOUR

8. OBSERVED VERSUS PREDICTED
AVERAGE GROUNDWATER BEHAVIOUR
1.0
2.0
3.0
4.0
5.0
6.0
7.0
2000 2002 2004 2006 2008 2010 2012
Depth(m)
Observed versus Predicted Depth to Groundwater Kooba SE
Observed
Predicted

9. COMPUTER MODELLING AIMS
• Figure out Impact Irrigation and Rainfall
• Effect of Rice Growing, Channel Seepage etc.
• Long Term Salinity Effects
• Benefits of Management Options

10. STRATIGRAPHICAL INPUT NEEDS
• Deep Leakage Component
• Spatial Distribution of Stratigraphy
– Clays and Sands in the Profile
• Hydro-geological Factors
– Transmissivity
– Resistance in Clays to vertical Flow
WE CAN DO IT - THE MIA IS SO DATA RICH !!!

11. GROUNDWATER MANAGEMENT MODELS
1. Very Dependent on good Stratigraphical Data Input:
• SHAHBAZ etc – 2001 TO 2004 MIA MODEL
• CSIRO Canberra - 2006 TO 2011 MIA MODEL (follow up)
2. Less Dependent but Work better with good Stratigraphical Data:
• VAN DER LELY:
• GROUNDWATER BALANCE AND BEHAVIOUR MODEL
• SOIL SALINITY MODEL

12. The MIA SUPPOSEDLY has a
STRATIGRAPHY DATA RICH SYSTEM
But: Is it Real ?
Does it Exist ?
What is its Essence ?
Can it be used ?
ONTOLOGICAL COLLAPSE !!

13. 2012 RECONSTRUCTION
• BORE LOG DIGITISATION
• BORE COORDINATES ASSIGNED
• G.I.S COMPATIBLE DATA SET FOR M.I.
AND – Newly Generated:
• Hydro-geological Information based on
interpolation for a range of soil layers
(0-3, 3-6, 6-9, 9-13.5, 13.5-18, 18-22.5, 22.5-30m)

15. NUMBER OF BORES
Table 2: Number of bores for the Mirrool/Benerembah area and the Yanco I.A contributing
to gridding for mapping purposes.
Depth to
(m)
Mirrool /
Benerembah
Yanco I.A. Total (*1)
6 2235 1978 4213
13.5 1815 1741 3556
18 1086 1036 2122
22.5 704 668 1373
30 525 143 668
(*1: The bores in the overlapping area of the Kooba sub-division are duplicated in these numbers- see maps of
Appendix 2)

16. ASSUMED HYDRAULIC CONDUCTIVITY
FOR EACH TEXTURE CLASS
DESCRIPTION k m/day DESCRIPTION k m/day
BROWN COAL 0.100 GRAVEL 20.000
CLAY 0.020 GRIT 2.000
CEMENTED CLAY LOAM 0.050 GRAVELLY CLAY 0.100
CEMENTED LOAM 0.100 GRAVELLY SAND 6.000
CEMENTED SANDY CLAY 0.100 GRAVELLY LOAM 0.300
CEMENTED SANDY CLAY 0.020 HEAVY CLAY 0.003
CLAY LOAM 0.150 LOAM 0.300
CLAYEY COARSE SAND 1.000 LIGHT CLAY 0.030
CLAYEY FINE SAND 0.300 LOAMY SAND 0.500
CLAYEY GRAVEL 2.000 MEDIUMCLAY 0.006
CLAYEY SAND 0.500 PIPE CLAY 0.001
COARSE SAND 15.000 ROCK, STONE OR SIMILAR 0.001
COARSE SAND AND GRAVEL 20.000 SAND 8.000
DIRTY COARSE SAND 5.000 SANDY CLAY 0.030
DIRTY COARSE SAND AND GRAVEL 5.000 SANDY CLAY LOAM 0.200
DIRTY FINE SAND 1.500 SAND AND GRAVEL 10.000
DIRTY SAND 2.000 SANDY HEAVY CLAY 0.006
DIRTY SAND AND GRAVEL 3.000 SILTY CLAY 0.100
FINE SAND 2.000 SILTY HEAVY CLAY 0.010
FINE SANDY CLAY 0.100 SILTY MEDIUMCLAY 0.020
FINE SANDY CLAY LOAM 0.300 SANDY LOAM 0.300
FINE SAND AND GRAVEL 5.000 SANDY MEDIUMCLAY 0.010
FINE SANDY LOAM 0.400 SANDY PIPE CLAY 0.005
FINESANDY MEDIUMCLAY 0.020

20. THERE ARE 22 MAPS LIKE THIS !

21. WHAT CAN WE DO WITH THIS?
1. Numerical Groundwater Models. Improved input data for a groundwater flow
model, if such was contemplated (again).
2. Groundwater Balance and Behaviour Model. Reference Deep Leakage Factors to
improve the results spatially.
3. Soil Salinity Model. Input in terms of hydrological factors such as
transmissivity, resistance to vertical flow and deep leakage.
4. Rice Environmental Management. Two aspects:
a) current soil profile criteria based for classifying rice land suitability
b) the effect of seepage from rice fields in high ground water table areas.
5. Channel Seepage. Finding potential channel seepage sites
6. Drainage / Groundwater Pumping Sites
This Talk will only Consider the Rice Management Aspects.

22. Rice Land Classification
• Current System only considers layers to 3 metres, not
always adequate. The stratigraphical model information
allows consideration of deeper layers; clearly useful.
• Rice Water Use data and WT monitoring have shown that
groundwater will rise anyway. Consideration of the top
three metres only is not a sufficient indicator of
“suitability”.
CONCLUSION: USE IT – DON’T LOSE IT !

23. RICE FIELD SEEPAGE MODELING
The Quantification of:
the flow from a rice field through the clays vertically, and then
through the aquifer (if any) horizontally, and then the upward
movement in adjacent land.....
should be considered.
The Stratigraphical Model offers an opportunity to find a
spatial representation of this potential flow.

24. Rice Seepage Analytical Model
(Lateral Seepage beneath Boundary)
Ponded Field Dry Area
q(x) HydraulicHead Aquifer
h(x) H
Original watertable
q(x) New watertable
--->s(0) ------ >s(x)
-x <------ x=0 ------->+x
A
s (0) = H * T / (SQRT(T x Cp) + SQRT(T x Cd))

25. POTENTIAL RATES
OF
LATERAL RICE SEEPAGE
MAPS

28. Implications of
High Rice Lateral Seepage Rates
• High rice seepage rates cause higher WTs in adjacent areas.
• More Salt movement to adjacent Land
• Reduced viability of other crops such as cotton and grapes
where groundwater levels are high ?
• Somewhat Higher Rice Water Use

29. CONCLUSIONS
• The historical data has been preserved
• The stratigraphical data may be used to develop spatially
distributed information of T and C for all layers to 30 metres depth
• The T and C information is potentially useful for a range of
modelling applications
• The T and C information of deeper layers may be used as a back-up
of rice classification questions
• Clearly, some parts of the MIA are more suited for rice than others
• Quantification of spatially distributed potential lateral rice seepage
rates may allow the addressing of crop compatibility questions