Embed Size (px)
Citation preview
Profile
Georgina grew up in Victoria where on the completion of high school she undertook a
Bachelor of Arts degree at Monash University. She moved to Perth to
undertake her PhD under Professor Bob Gilkes. She is looking at one of several
engineering options for addressing salinity in the landscape and has relished the
opportunity to get out in the thick of things as well as conduct research with real
applications.
MS GEORGINA HOLBECHE
Georgina HolbecheProf. Bob Gilkes
Dr Richard George
10,000km of drainage in the Wheatbelt, what are the issues?
Background
Salinity represents one of the greatest problems facing agricultural productivity in the south-west of Western Australia.
As traditional plant-based solutions may prove unsuccessful engineering solutions provide new options for salinity management
Engineering alternatives
Relief and siphon boresSurface water managementGroundwater pumpingDeep drainage
Area of Blackboy Creek requiring surface water management
Cox 2005
Complexity of materials
Lee 1999
The complex, highly weathered landscape of Western Australia
An agricultural problem
Valley floors are occupied by sediments and highly weathered soils and are consequently complexRising groundwaters and associated salts threaten agricultural productivityDeep drainage has resulted in inconsistent degrees of successUnderstanding the materials may make deep drainage more predictable
Deep drain design
An open deep drain with a levee on both sides
An open deep drain with a levee on one side of the drain
EEI 2005
Drainage in the Wheatbelt of W.A.
Cox 2002Solomon 2005
Herringbone design in DumbleyungDeep drain near Wubin
Aims of research
To identify and understand the materials that are being drained
To develop a user-friendly classification system for predicting the impact of deep drainage prior to construction
Components of project
Field work
General observation of materials
Mineralogy
Chemistry
Microscopy
Hydrology (known)
Develop classification tool
Development of classification
Develop a better understanding of different types of valley floor materials and their propertiesInitial basis for classification
TextureStructureCoarse materialMottlingCementation
Good micro classification can be macro useful
Development of classification
Macro + Micro + Hydrology
Macro Classification Tool
Impact of material permeability
The properties of a material determine how it well it drains
Cox 2005
Diversity of drain materials
ClaySandCarbonatesCoarse sedimentsIndurated material (silica, iron oxides)
Examples of diverse materials
Mineralogy of drainage materials in W.A.
Typical XRD patterns for three different materials
0
200
400
600
800
1000
1200
3 13 23 33 43 53 63
Degrees 2‐Theta
Counts
ka olinite
quartz
goethite
feldspar
calcitedolomite
hematite
Mineralogy and drainage
The common regolith consists of kaolinite, quartz and feldspar
Some regolith has been impregnated by iron oxides or carbonates which will reduce permeability
Thin section of carbonate material
TS004 60 – 180 carbonate material
Thin section of quartz dominated material
WC021 45 – 60 quartz dominated material
Image analysis of pore size distribution
0 10 20 30 40 50 60 70 80 90 100
Micropo
0
10
20
30
40
50
60
70
80
90
100
esopore
0
10
20
30
40
50
60
70
80
90
0
KandKandKandKandKandiustox (Pc) Limestone
Kandiudox (Ak) LimestoneKandiustox (Ci) BasaltKandiudox (Ti) Basalt
Cryptopores = < 0.1 μm
Ultramicropores = 1 – 5 μm
Micropores = 5 – 30 μm
Mesopores = 30 – 75 μm
Macropores = > 75 μm
Mesopores Micropores
Macropores Tawornpruek 2003
Cryptopores contribute 23 – 35% of total porosityTotal pore volume = 30 – 50%
A practical application
Understanding micro features of samples (such as porosity)
Relate these to analogous macro features (such as texture)
Relate material properties to water flow
Make drainage prediction more user-friendly
Conclusions
Drains are constructed through highly diverse materials
Materials range from sand to clay resulting in large differences in hydraulic conductivity
Comprehension at a micro scale can assist the construction of a user-friendly classification system at a macro scale
Acknowledgements
GRDC for their generous funding
Department of Agriculture and Food, WA
School of Earth and Geographical Sciences
Mr Michael Smirk
