AndreaBozzo/ceres-open-data-index huggingface dataset:
Namoi groundwater observation bores

## **Abstract** 

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.



This dataset was created by subsampling the observation bores from NGIS that have at least one relaible coordinate and at least one groundwater level measurement in the period 1993-2012. More details are provided in NAM213.

## **Purpose** 

The purpose of this dataset is to constrain the groundwater model predictions.

## **Dataset History** 

This dataset was created by subsampling the observation bores from NGIS that have at least one relaible coordinate and at least one groundwater level measurement in the period 1993-2012. More details are provided in NAM213.

## **Dataset Citation** 

Bioregional Assessment Programme (2016) Namoi groundwater observation bores. Bioregional Assessment Derived Dataset. Viewed 11 December 2018, http://data.bioregionalassessments.gov.au/dataset/673a0e8d-47fc-4942-acf3-99931718579f.

## **Dataset Ancestors** 

* **Derived From** [NSW Office of Water - National Groundwater Information System 20141101v02](https://data.gov.au/data/dataset/6c364d09-fc3b-47c3-aa98-6c702d3d8137)

* **Derived From** [Hydstra Groundwater Measurement Update - NSW Office of Water, Nov2013](https://data.gov.au/data/dataset/08b34518-c947-4665-82e5-c144b5b24e01)



Tags: Namoi subregion, New South Wales, geoscientificInformation
Organization: Bioregional Assessment Program
Impact Modes and Effects Analysis for the Namoi subregion

## **Abstract** 

This dataset and its metadata statement were created within the Bioregional Assessment Programme based on expert elicitation. There are no source datasets used, it was derived by expert opinion.



In this dataset we describe the application of Impact Modes and Effects Analysis (IMEA) to the hazards associated with coal seam gas and coal mining operations in the Namoi subregion. Attention is restricted to water mediated hazards, i.e. hazards that might lead directly or indirectly to impacts on groundwater or surface water, and the assets that depend on them. All other hazards, for example the effects of air quality, are explicitly excluded.  Full details of the hazard analysis process are described in http://data.bioregionalassessments.gov.au/submethodology/M11

## **Dataset History** 

Full details of the hazard analysis process are described in http://data.bioregionalassessments.gov.au/submethodology/M11

## **Dataset Citation** 

Bioregional Assessment Programme (2015) Impact Modes and Effects Analysis for the Namoi subregion. Bioregional Assessment Source Dataset. Viewed 11 December 2018, http://data.bioregionalassessments.gov.au/dataset/1be5b4b0-1bbf-45ae-b692-4f34c8b28d21.

Tags: Namoi subregion, New South Wales, economy, environment, inlandWaters, planningCadastre
Organization: Bioregional Assessment Program
Galilee drawdown grids

## **Abstract** 

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets.

The source datasets are identified in the Lineage field in this metadata statement.

The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. 





This dataset contains grids of the 5th, 50th and 95th percentile of drawdown in the model layers as well as grids of the probability of exceeding 0.2, 2 and 5 m drawdown as estimated with the GAL AEM model.

## **Dataset History** 

In dataset GAL_AEM_dmax_v01 the drawdown at each model layer is summarised by the 5th, 50th and 95th percentile and the probability of exceeding 0.2m, 2m and 5m. This information is contained in spreadsheets 'GAL_AEM_dmax_ExcProb_Alluvium.csv', 'GAL_AEM_dmax_ExcProb_Clematis.csv' and 'GAL_AEM_dmax_ExcProb_BCB.csv'.

The information in these spreadsheets is interpolated using QuantumGIS to create a regular grid to visualise the spatial drawdown trends. The interpolated grids are stored in this dataset.

## **Dataset Citation** 

Bioregional Assessment Programme (2016) Galilee drawdown grids. Bioregional Assessment Derived Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/b106283c-2347-4024-8fa7-c582292bee65.

## **Dataset Ancestors** 

* **Derived From** [Galilee Hydrological Response Variable (HRV) model](https://data.gov.au/data/dataset/facb2291-249c-4903-93ce-d9c3f83e7640)

* **Derived From** [Galilee groundwater numerical modelling AEM models](https://data.gov.au/data/dataset/2698f3c2-b8d4-4b4e-899c-d50e0e1aac1f)

* **Derived From** [Geoscience Australia GEODATA TOPO series - 1:1 Million to 1:10 Million scale](https://data.gov.au/data/dataset/310c5d07-5a56-4cf7-a5c8-63bdb001cd1a)

* **Derived From** [Surface Geology of Australia, 1:2 500 000 scale, 2012 edition](https://data.gov.au/data/dataset/4a91fff8-ed51-4994-b358-066497e25c8c)

* **Derived From** [Galilee model HRV receptors gdb](https://data.gov.au/data/dataset/ee766aad-3849-4a5a-92b7-ff4098bd874e)



Tags: Galilee subregion, geoscientificInformation
Organization: Bioregional Assessment Program
Advatel Wireless Pty Ltd - Designated service areas - August 2020

This data set describes the service areas where Advatel Wireless is the Statutory Infrastructure Provider (SIP). This data set forms part of the SIP register which is managed by the ACMA. Further information on the SIP register is located on the ACMA’s website at https://www.acma.gov.au/sip-register

Tags: Advatel, SIP, Statutory Infrastructure Provider, Utilities and Communication, broadband, telecommunications
Organization: SIP Register - Advatel Wireless Pty Ltd
Groundwater Preliminary Assessment Extent for the Namoi subregion

## **Abstract** 

This dataset was derived by the Bioregional Assessment Programme. This dataset is an ESRI shapefile digital representation of the draft, hardcopy PAE approved by Damian Barrett (Principal Science Advisor). Refer to the parent dataset (source) in the Lineage field in this metadata statement. The History field in this metadata statement describes how this dataset was derived.

## **Purpose** 

The purpose of the PAE is to provide a first step in the process of determining whether a water-related link is possible between coal resource development and the assets. It is intended to be a realistic yet inclusive estimate of the land surface area where potential impacts might occur. As the model-data analysis, impact analysis and risk analysis components of a BA are completed it will be possible to more closely characterise and quantify impacts in terms of their extent and their likelihood.

## **Dataset History** 

The ESRI shapefile was created by soft copy digitising of the hand-drawn boundary developed from expert assessment of drawdown results from a groundwater model and likely groundwater flows and groundwater impacts in the Namoi Alluvium and the underlying Great Artesian Basin sequence. The choice of boundary in both hydrogeological systems is that there is no groundwater flow radially outwards from these boundaries. The boundary is constrained in the east by the Hunter-Mooki Fault.

## **Dataset Citation** 

Bioregional Assessment Programme (2015) Groundwater Preliminary Assessment Extent for the Namoi subregion. Bioregional Assessment Derived Dataset. Viewed 11 December 2018, http://data.bioregionalassessments.gov.au/dataset/e58298c8-dc0b-48da-aeca-50b86974954d.

## **Dataset Ancestors** 

* **Derived From** [Groundwater Zone of Impact for the Namoi subregion](https://data.gov.au/data/dataset/51aed716-276b-477f-ba48-ff99ffce7c4e)



Tags: Namoi subregion, New South Wales, geoscientificInformation
Organization: Bioregional Assessment Program
South Australia Petroleum Production Licenses

## **Abstract** 

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.



Location of all current Production Licences issued under the Petroleum Act, 2000, Petroleum (Submerged Lands) Act, 1982, or Petroleum (Submerged Lands) Act, 1967 for the regulated resource or commodity of petroleum. Production Licences provide exclusive tenure rights to produce for the regulated resource or commodity of petroleum for an unlimited term (usually 21 years). Comment is sought on applications for Production Licences from numerous sources before granting. Production programs are subject to strict environmental and heritage conditions.

## **Purpose** 

The dataset was developed to record information necessary for the administration of the Petroleum Act, 2000, Petroleum (Submerged Lands) Act, 1982, and Petroleum (Submerged Lands) Act, 1967.



Use: Used to supply government, industry and the general public with an up-to-date status and extent of petroleum production activities throughout the state.

## **Dataset History** 

Lineage:



Source Data History: Production Licences boundaries were sourced from the official Petroleum Register licence documents. Licence boundaries are legally defined to follow lines of latitude and longitude, based on potentially several geodetic datums.



Processing Steps: Coordinates entered by keyboard from licence documents. Non GDA94 coordinates transformed into GDA94. Linework cleaned to remove duplicate arcs. Data adjusted for accurate state border and coastline. Where appropriate cadastral parcels removed from licence polygons. Associated attribute data also captured from licence documents.

## **Dataset Citation** 

"SA Department for Manufacturing, Innovation, Trade, Resources and Energy" (2013) South Australia Petroleum Production Licenses. Bioregional Assessment Source Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/13dc0f31-6eae-44d7-85be-dcba662623ff.

Tags: Cooper subregion, Galilee subregion, South Australia, economy
Organization: Bioregional Assessment Program
QLD DNRM Surface Water Licences linked to Spatial Locations - v1 20140313

## **Abstract** 

The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from multiple datasets. You can find a link to the parent datasets in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived. 



This dataset is adapted from an extract from the QLD Dept of Natural Resource and Mines licensing data from the water management system. The dataset includes basic right (domestic & stock) licences as well as surface water licences (eg. irigation, town supply etc). Surface water licences can have an allocation as megalitres or a right to irrigate a certain number of hectares. There is no basic conversion to determine how many megalites/hecatre. The volume allocated for domestic and stock also varies based on the management area. This information can be found resource operations plan or water sharing rules.

## **Purpose** 

For licences that do not have a offtake lat/long, this has been linked to the Cadastre information (also provided by DNRM) that ties the offtake to the centroid of the property.

Although this is not 100% accurate, it now allows future users of the surface water licences to be able to plot locations within a catchment.



In all cases, the 'off-take lat' and 'off-take long' should be used where available. This is the location provided from the licensing system where one was available. Where no location is provided for the offtake, the 'centroid lat' and 'centroid long' should be used.



DNRM counld not supply GIS layers for the water management areas refered to in the dataset.

## **Dataset History** 

An additional column, 'asset class' was also added to the dataset for the purpose of the economic asset database. "Asset Class'aggregates the purpose of the licence into the set classes for the Asset Database. Where purpose = domestic; or domestic & stock; or stock then it was classed as 'basic water right'. Where it is listed as both a domestic/stock and a licensed use such as irrigation, it was classed as a 'water access right.' All other take and use were classed as a  'water access right'.

## **Dataset Citation** 

Bioregional Assessment Programme (2013) QLD DNRM Surface Water Licences linked to Spatial Locations - v1 20140313. Bioregional Assessment Derived Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/caf51590-ad61-492d-87b6-89fc95ff842a.

## **Dataset Ancestors** 

* **Derived From** [QLD DNRM Licence Locations Linked to Cadastre Plan - v1 - 20140307](https://data.gov.au/data/dataset/bf1085d8-9752-4533-a65a-820a020907db)

* **Derived From** [QLD Dept of Natural Resources and Mines, Surface Water Entitlements 131204](https://data.gov.au/data/dataset/fc8366ad-46d8-463a-aa79-8e1679a74f1a)



Tags: Clarence-Moreton bioregion, Galilee subregion, Maranoa-Balonne-Condamine subregion, Queensland, inlandWaters
Organization: Bioregional Assessment Program
Vegetation height for Australia (Simard)

## **Abstract** 

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. Data was downloaded from http://lidarradar.jpl.nasa.gov/MAPS/Simard_Pinto_3DGlobalVeg_JGR.tif.gz



Vegetation height was measured using a satellite based light detection and ranging (lidar) system between 20 May 2005 to 23 June 2005 using the Geoscience Laser Altimeter System (GLAS) aboard ICESat (Ice, Cloud and Land Elevation Satellite). Using a regression tree approach to model canopy height, Simard et al. (2011) were able to globally model overstorey vegetation height at 1 km spatial resolution with a vertical RMSE of 4.4 m and coefficient of determination (r2) of 0.7 when compared against 59 flux-tower field observations globally. The dataset covers the whole of Australia.



Simard M, Pinto N, Fisher JB and A. B (2011) Mapping forest canopy height globally with spaceborne lidar. Journal of Geophysical Research: Biogeosciences, 116(G04021), doi:10.1029/2011JG001708.

## **Dataset History** 

Vegetation height was measured using a satellite based light detection and ranging (lidar) system between 20 May 2005 to 23 June 2005 using the Geoscience Laser Altimeter System (GLAS) aboard ICESat (Ice, Cloud and Land Elevation Satellite). Using a regression tree approach to model canopy height, Simard et al. (2011) were able to globally model overstorey vegetation height at 1 km spatial resolution with a vertical RMSE of 4.4 m and coefficient of determination (r2) of 0.7 when compared against 59 flux-tower field observations globally. 



The data were downloaded from the Jet Propulsion Laboratory website here: http://lidarradar.jpl.nasa.gov/MAPS/Simard_Pinto_3DGlobalVeg_JGR.tif.gz



Data covering the Australian continent was extracted and converted to a ArcGIS raster using the bounding coordinates (GCS_WGS_1984): 



Latitude (min): -43.6369999991

Longitude (min): 112.921

Latitude (max): -10.0620134291

Longitude (max): 153.64598371

## **Dataset Citation** 

Caltech/JPL (2014) Vegetation height for Australia (Simard). Bioregional Assessment Source Dataset. Viewed 11 December 2018, http://data.bioregionalassessments.gov.au/dataset/09f0ceb4-d401-410c-bd4f-dfbc5276ef8b.

Tags: Hunter subregion, Namoi subregion, elevation, environment
Organization: Bioregional Assessment Program
SYD ALL climate data statistics summary

## **Abstract** 

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.



There are 4 csv files here:

BAWAP_P_annual_BA_SYB_GLO.csv

Desc: Time series mean annual BAWAP rainfall from 1900 - 2012.

Source data: annual BILO rainfall on \\wron\Project\BA\BA_N_Sydney\Working\li036_Lingtao_LI\Grids\BILO_Rain_Ann\



P_PET_monthly_BA_SYB_GLO.csv

long term average BAWAP rainfall and Penman PET from 198101 - 201212 for each month



Climatology_Trend_BA_SYB_GLO.csv

Values calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P; (ii) Penman ETp; (iii) Tavg; (iv) Tmax; (v) Tmin; (vi) VPD; (vii) Rn; and (viii) Wind speed.  For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend



Risbey_Remote_Rainfall_Drivers_Corr_Coeffs_BA_NSB_GLO.csv

Correlation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons.  The data and methodology are described in Risbey et al. (2009).  All data used in this analysis came directly from James Risbey, CMAR, Hobart.  As described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid.  BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November.  The analysis is a summary of Fig. 15 of Risbey et al. (2009).

## **Dataset History** 

Dataset was created from various BILO source data, including Monthly BILO rainfall, Tmax, Tmin, VPD, etc, and other source data including monthly Penman PET (calculated by Randall Donohue), Correlation coefficient data from James Risbey

## **Dataset Citation** 

Bioregional Assessment Programme (XXXX) SYD ALL climate data statistics summary. Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/b0a6ccf1-395d-430e-adf1-5068f8371dea.

## **Dataset Ancestors** 

* **Derived From** [BILO Gridded Climate Data: Daily Climate Data for each year from 1900 to 2012](https://data.gov.au/data/dataset/7aaf0621-a0e5-4b01-9333-53ebcb1f1c14)



Tags: Hunter subregion, New South Wales, climatologyMeteorologyAtmosphere
Organization: Bioregional Assessment Program
Namoi Valley Flood Plain Atlas 1979

## **Abstract** 

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 the known details at the time of acquisition.



This dataset were digitised from the Namoi Valley Flood Plain Atlas produced in 1979 by consultants Laurie, Montgomerie and Pettit Pty Ltd on contract to the NSW Water Resources Commission.



The Atlas was producted using aerial photography and from interviews and other information gained through local contacts, and from formal Commission records.  In theory at least, the Atlas reflects the maximum extent of floods in 1954, 55, 1962, 64, 1971, 74, 76 and 1977. The original data were mapped at 1:50,000 scale.

## **Dataset History** 

No metadata was provided with this dataset.



The Atlas was producted using aerial photography and from interviews and other information gained through local contacts, and from formal Commission records.  In theory at least, the Atlas reflects the maximum extent of floods in 1954, 55, 1962, 64, 1971, 74, 76 and 1977. The original data were mapped at 1:50,000 scale.

## **Dataset Citation** 

NSW Office of Environment and Heritage (1979) Namoi Valley Flood Plain Atlas 1979. Bioregional Assessment Source Dataset. Viewed 10 December 2018, http://data.bioregionalassessments.gov.au/dataset/d42235b8-2c0b-4179-bcf7-e37b40bf21f1.

Tags: Maranoa-Balonne-Condamine subregion, Namoi subregion, New South Wales, inlandWaters
Organization: Bioregional Assessment Program
Northern Inland Catchments 1M Surface Geology - Pilliga Sandstone (GAB Recharge Beds)

## **Abstract** 

This dataset was derived from data provided by the Geoscience Australia.  The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.



Extract from the 1:1M Geoscience Australia Surface Geology of Pilliga Sandstone relating to the NIC BA area. This outcrop is considered the groundwater recharge/intake beds for the Great Artesian Aquifer.

## **Purpose** 

The Surface Geology of Australia 1:1M scale dataset (2012 edition) is a seamless national coverage of outcrop and surficial geology, compiled for use at or around 1:1 million scale. The data maps outcropping bedrock geology and unconsolidated or poorly consolidated regolith material covering bedrock. Geological units are represented as polygon and line geometries, and are attributed with information regarding stratigraphic nomenclature and hierarchy, age, lithology, and primary data source. The dataset also contains geological contacts, structural features such as faults and shears, and miscellaneous supporting lines like the boundaries of water and ice bodies. The 2012 dataset has been updated from the previous 2010 data by updating geological unit data to 2012 information in the Australian Stratigraphic Units Database (http://www.ga.gov.au/products-services/data-applications/reference-databases/stratigraphic-units.html).

## **Dataset History** 

Piiliga sandstone units (PLOT SYMBOL - Js) exported from the Geoscience Australia 1:1M Surface geology dataset

## **Dataset Citation** 

Bioregional Assessment Programme (2014) Northern Inland Catchments 1M Surface Geology - Pilliga Sandstone (GAB Recharge Beds). Bioregional Assessment Derived Dataset. Viewed 10 December 2018, http://data.bioregionalassessments.gov.au/dataset/2c7bf639-dd94-4abb-af6f-b64e544194b6.

## **Dataset Ancestors** 

* **Derived From** [Surface Geology of Australia, 1:1 000 000 scale, 2012 edition](https://data.gov.au/data/dataset/8284767e-b5b1-4d8b-b8e6-b334fa972611)



Tags: Central West subregion, Namoi subregion, geoscientificInformation
Organization: Bioregional Assessment Program