This dataset was supplied to the Bioregional Assessment Programme by a third party and is presented here as originally supplied. Metadata was not provided and has been compiled by the Bioregional Assessment Programme based on known details at the time of acquisition.
Vegetation in NSW of high ecological value having high probability of being groundwater dependent were identified through a process that used current vegetation data, depth to groundwater data, data that showed potential frequency of water use other than surface water based on a continuous 10 year period and expert opinion. High Probability vegetation communities were identified as being of High Ecological Value when they sat within one or more selected datasets. (see below) Geographic Extent: Hunter & Central Rivers CMA
This is a preliminary dataset, the project is on going.
This dataset has been provided to the BA Programme on the condition that third parties may not reproduce this dataset. Third parties wishing to use or reproduce this data should contact the data provider.
Note this dataset is a draft pre-release for use in the Bioregional Assessment Programme. This dataset is not to be published in BA until the data provider releases the data on their website.
Data Quality:
Data sources:
High Probability
Vegetation: obtained from OEH
Depth to groundwater: modelled data provided by Office of Water Hydrogeologists
Potential frequency of water use other than surface water based on a continuous 10
year period : This data set was created by Herbert Hemakumara (Office of Water) using
remote sensing MODIS
High Ecological Value
National Parks and State Forests (OEH)
SEPP 14 & 26 (Dept Planning)
RAMSAR Wetlands (OEH)
Marine parks and aquatic reserves (OEH)
Identified rain forest communities (OEH)
Threatened or endangered species (OEH)
Wildlife corridors, Regional Conservation strategies or communities identified as
being significant in various studies (Various Sources)
NSW Office of Water (2015) Hunter CMA GDEs (DRAFT DPI pre-release). Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/469d6d2e-900f-47a7-a137-946b89b3d188.