Victorian winterfill sustainable diversion limit aggregate basins
dataset:
SDL_BASIN
Winterfill sustainable diversion limit volumes (SDLs) have been developed across Victoria and represent the upper limit on
winterfill diversions, beyond which there is an unacceptable risk that additional extractions may degrade the environment.
The SDL_BASIN dataset is a spatial representation of river basins, which represent an aggregate of the intermediate SDL catchments.
These basins DO NOT reflect the Victorian surface water river basins as defined by the Australian Water Resources Council.
Winterfill SDL data is held in the SDL_DATA layer.
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Citation proposal Citation proposal
(2024) Victorian winterfill sustainable diversion limit aggregate basins Department of Energy, Environment and Climate Action https://metashare.maps.vic.gov.au/geonetwork/srv/eng/catalog.search#/metadata/45377f61-4c11-4e0d-a1f9-d1dba8f8d08a |
- Description
- Temporal
- Spatial
- Maintenance
- Format
- Contacts
- Keywords
- Resource Constraints
- Lineage
- Metadata Constraints Metadata Constraints
- Quality
- Acquisition Info
- Raster Data Details
- Raster Type Details
- Point Cloud Data Details
- Contour Data Details
- Survey Details
Description
- Title
- Victorian winterfill sustainable diversion limit aggregate basins
- Alternate title
- SDL_BASIN
- Purpose
- This dataset is an optional spatial aid used when interrogating the winterfill SDL intermediate catchments (refer to dataset SDL_CATCH). It holds no attributes relevant to winterfill SDL volumes.
- Supplemental Information
- Status: completed
Maintenance
- Maintenance and update frequency
- Not planned
Contacts
Point of contact
Department of Energy, Environment and Climate Action
-
Hydrology and Climate Science
8 Nicholson St
East Melbourne
Vic
3002
Australia
Cited responsible party
No information provided.
Keywords
- Topic category
-
- Inland waters
Resource Constraints
- Classification
- Unclassified
Metadata Constraints Metadata Constraints
- Classification
- Unclassified
Quality
Attribute Quality
Positional Accuracy
Conceptual Consistency
Missing Data
Excess Data
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