Product catalogue
Groundwater dependent ecosystem assessment using remote sensing. Exploring for the Future - Upper Darling River floodplain, New South Wales
<div>This report presents the findings of a study conducted in the upper Darling River floodplain, aimed at improving optical and interferometric synthetic aperture radar (InSAR) remote sensing products for groundwater dependant vegetation (GDV) characterisation. The research was part of the Upper Darling Floodplain (UDF) groundwater study, funded by the Exploring for the Future program.</div><div>This work tests the suitability of two novel remote sensing methods for characterising ecosystems with a range of likely groundwater dependence: combined wetness and greenness indices derived from Landsat products available through Geoscience Australia’s Digital Earth Australia platform, and an InSAR derived index of vegetation structure (known as SARGDE), which has been so far tested only in northern Australia. In addition, the relationship between the Normalised Difference Vegetation Index (NDVI), a remotely sensed proxy for vegetation condition, and water availability from surface water flows, rainfall, and groundwater was tested for sites with a range of low to high likely groundwater dependence. </div><div>The key findings of this work, and potential implications, are:</div><div>• A multiple lines of evidence approach, drawing on persistence of wetness/greenness and vegetation structure, and correlation between inferred vegetation condition and groundwater levels, gives high confidence in the groundwater dependence of parts of the floodplain, particularly within the riparian zone. These indices require calibration with ground condition data to be applied in different regions, but a combined index could provide a high confidence measure of groundwater dependence.</div><div>• Combined greenness and wetness, SARGDE, and the relationship between NDVI and groundwater levels all showed areas classified as ‘moderate’ likelihood of groundwater dependence having signatures comparable to areas classified as high likelihood. This could address a shortcoming of the groundwater dependence classification methodology, which, when groundwater level information is missing, classifies some vegetation types as moderate.</div><div>• A combined index taking into account both greenness and wetness was able to better delineate vegetation types with a range of groundwater dependence previously not achievable using remote sensing products. </div><div>This work has provided improved methodology for applying remote sensing products to groundwater dependent vegetation characterisation in the study area. The methods are likely to be applicable to other regions with groundwater dependent vegetation. The results add to the evidence that it is necessary to better integrate surface and groundwater resources in water sharing plans at a basin scale. Further work is required to quantify the frequency and magnitude of flow events required to replenish alluvial groundwater sufficiently to maintain existing groundwater dependent ecosystems. </div><div><br></div><div><br></div>
Simple
Identification info
- Date (Creation)
- 2023-06-17T00:00:00
- Date (Publication)
- 2023-08-15T01:13:13
- Citation identifier
- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/148545
- Citation identifier
- Digital Object Identifier/https://dx.doi.org/10.26186/148545
- Cited responsible party
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Role Organisation / Individual Name Details Publisher Commonwealth of Australia (Geoscience Australia)
Voice Author Buckerfield, S.
Internal Contact Author Kilgour, P.
Internal Contact Author Castellazzi,P.
External Contact Author Dabovic, J.
External Contact Author McPherson, A.
Internal Contact Author Dixon-Jain, P.
Internal Contact Author Symington, N.
Internal Contact Author Buchanan, S.
Internal Contact
- Name
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GA Record
- Issue identification
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GA Record 2023/30
- Purpose
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To test and improve optical and interferometric synthetic aperture radar (InSAR) remote sensing products for characterisation of groundwater dependent vegetation. The study area is the upper Darling River floodplain, where regional ecosystem mapping has been performed and provides a comparative dataset. This research is part of the Upper Darling Floodplain (UDF) groundwater study, funded by the Exploring for the Future program.
- Status
- Completed
- Point of contact
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Point of contact Buckerfield, S.
MEG Internal Contact Resource provider Minerals, Energy and Groundwater Division
External Contact
- Spatial representation type
- Topic category
-
- Geoscientific information
Extent
))
- Maintenance and update frequency
- As needed
Resource format
- Title
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Product data repository: Various Formats
- Website
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Data Store directory containing the digital product files
Data Store directory containing one or more files, possibly in a variety of formats, accessible to Geoscience Australia staff only for internal purposes
- Project
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EFTF – Exploring for the Future
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- Project
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Darling River Floodplain
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- Project
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Darling-Curnamona-Delamerian
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- Keywords
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Groundwater dependant ecosystem
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- Keywords
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Groundwater dependant vegetation
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- Keywords
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NDVI
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- Keywords
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InSAR
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- Keywords
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Darling River
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- Keywords
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New South Wales
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- Keywords
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NSW
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- Keywords
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Remote sensing
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Landsat
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Tasselled Cap
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- theme.ANZRC Fields of Research.rdf
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Groundwater hydrology
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- Keywords
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Published_External
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Resource constraints
- Addressee
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Role Organisation / Individual Name Details User Any
- Use constraints
- License
- Use constraints
- Other restrictions
- Other constraints
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© Commonwealth of Australia (Geoscience Australia) 2023
Resource constraints
- Title
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Australian Government Security Classification System
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
- Classification system
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Australian Government Security Classification System
Associated resource
- Association Type
- Was informed by
- Title
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Groundwater dependent ecosystems in the upper Darling River floodplain NSW, mapped using Landsat satellite data
- Citation identifier
- 148626
- Citation identifier
- e0bb1a45-22b6-432b-a791-3df1782e9578
- Language
- English
- Character encoding
- UTF8
Distribution Information
- Distributor contact
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Role Organisation / Individual Name Details Distributor Commonwealth of Australia (Geoscience Australia)
Voice facsimile
- OnLine resource
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Download the Record (pdf) [24.7 MB]
Download the Record (pdf) [24.7 MB]
- Distribution format
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pdf
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Resource lineage
- Statement
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This report is based on analysis of InSAR data (by CSIRO), and DEA products, bore hydrographs, and modelled soil moisture data (by GA).
Metadata constraints
- Title
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Australian Government Security Classification System
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
Metadata
- Metadata identifier
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urn:uuid/6e322ef2-7cf6-4511-a5f4-bc97f8b2558d
- Title
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GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
- Contact
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Point of contact Buckerfield, S.
MEG Internal Contact
Type of resource
- Resource scope
- Document
- Name
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GA Record
Alternative metadata reference
- Title
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Geoscience Australia - short identifier for metadata record with
uuid
- Citation identifier
- eCatId/148545
- Date info (Creation)
- 2023-06-15T01:50:27
- Date info (Revision)
- 2023-06-15T01:50:27
Metadata standard
- Title
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AU/NZS ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-3
- Title
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Geoscience Australia Community Metadata Profile of ISO 19115-1:2014
- Edition
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Version 2.0, September 2018
- Citation identifier
- http://pid.geoscience.gov.au/dataset/ga/122551