AndreaBozzo/ceres-open-data-index huggingface dataset:
CLM GCM ranking

## **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. 



A table showing GCM (Global climate models) rankings for the Clarence-Moreton bioregion.

## **Purpose** 

The ranking of GCM was created to select the model that produced median changes in precipitation. The selected model was used to predict future rainfall for the years 2013 to 2102.

## **Dataset History** 

A total of 15 global climate model (GCM) was tested to identify the best GCM to predict future climate data for the Clarence-Moreton Bioregion. The objective in developing a future climate series was to choose the set of GCM's seasonal scaling factors that give the median change in mean annual precipitation. Four seasonal scaling factors for the seasons: summer (December-February), autumn (March-May), winter (June-August) and spring (September-November) were used to predict changes in precipitation in the Clarence-Moreton Bioregion under future climate. For each GCM the change in mean seasonal precipitation for 1 degree global warming was calculated. These seasonal changes were summed to get the change in mean annual precipitation. Based on resulting changes in mean annual precipitation for a 1 degree global warming the GCMs were ranked in ascending order. The GCM that produced median change in annual mean precipitation was selected to predict the future precipitation in the Clarence-Moreton Bioregion for the years 2013 to 2102.

## **Dataset Citation** 

Bioregional Assessment Programme (2016) CLM GCM ranking. Bioregional Assessment Derived Dataset. Viewed 28 September 2017, http://data.bioregionalassessments.gov.au/dataset/fc1071a3-5c30-4bf4-b288-428df83a1c32.

## **Dataset Ancestors** 

* **Derived From** [SEACI GCM scaling](https://data.gov.au/data/dataset/bde1e7b7-5bb3-483c-8616-c4176fde8818)



Tags: Clarence-Moreton bioregion, climatologyMeteorologyAtmosphere
Organization: Bioregional Assessment Program
CLM - Hydraulic conductivity QLD

## **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 the hydraulic conductivity and transmissivity data for the Queensland part of the Clarence-Moreton Basin. The data were organized by geological formations. The data were sourced from the Queensland state groundwater databases. Most records in the pumping test database do not have a hydraulic conductivity entry. The hydraulic conductivity was derived from the pumping test data by a two-step method to support the groundwater modelling: (i) transmissivity was estimated from the original test readings using the TGUESS approach; and (ii) hydraulic conductivity was calculated based on the estimated transmissivity and the screen information. The estimated hydraulic conductivity was mainly available for the alluvium and volcanics and varies in a range of six orders of magnitude.

## **Dataset History** 

This dataset was created through the following process:



1. Filter the data using the spatial extent of the Clarence-Moreton Basin;

2. Data quality check;

3. Calculate transmissivity using the TGUESS approach;

4. Compute hydraulic conductivity using the calculated transmissivity and the screen information in the state database;

5. Aquifer assignment.

## **Dataset Citation** 

Bioregional Assessment Programme (2014) CLM - Hydraulic conductivity QLD. Bioregional Assessment Derived Dataset. Viewed 28 September 2017, http://data.bioregionalassessments.gov.au/dataset/1e181f78-d670-4e1b-ae74-67ee66e28e80.

## **Dataset Ancestors** 

* **Derived From** [Bioregional Assessment areas v02](https://data.gov.au/data/dataset/e414b1b3-c42e-42e9-9cc4-2093054aa35f)

* **Derived From** [Natural Resource Management (NRM) Regions 2010](https://data.gov.au/data/dataset/1d54e38f-4051-4f0c-a350-c7dbd8eba65b)

* **Derived From** [Bioregional Assessment areas v03](https://data.gov.au/data/dataset/96dbf469-5463-4f4d-8fad-4214c97e5aac)

* **Derived From** [QLD Department of Natural Resources and Mines Groundwater Database Extract 20142808](https://data.gov.au/data/dataset/a5c5cbdb-1152-43f7-9533-a123027b7ce1)

* **Derived From** [Bioregional Assessment areas v01](https://data.gov.au/data/dataset/0fd0d820-30b3-451f-a126-a50040426999)

* **Derived From** [GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)](https://data.gov.au/data/dataset/96ebf889-f726-4967-9964-714fb57d679b)

* **Derived From** [GEODATA TOPO 250K Series 3](https://data.gov.au/data/dataset/a0650f18-518a-4b99-a553-44f82f28bb5f)

* **Derived From** [NSW Catchment Management Authority Boundaries   20130917](https://data.gov.au/data/dataset/0dc4272e-c081-4ed4-9645-aa336ffacd85)

* **Derived From** [Geological Provinces - Full Extent](https://data.gov.au/data/dataset/0a064b3b-2a1e-4672-80d9-03333be67aad)



Tags: Clarence-Moreton bioregion, geoscientificInformation
Organization: Bioregional Assessment Program
CLM - Bore assignments NSW

## **Abstract** 

The dataset was derived by the Bioregional Assessment Programme. This dataset was derived from the NSW Office of Water - National Groundwater Information System 20140701 dataset. You can find a link to the parent dataset in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived.



This dataset contains the aquifer assignment results for the NSW part of the Clarence-Moreton Basin. The data were organized by hydrostratigraphic units. Assigning a bore to a specific aquifer is underpinned by the screened interval data and the aquifer boundaries. In many cases, it is impossible to assign the screened interval of a bore to a single aquifer as bores are either screened across different aquifers or there is insufficient information on stratigraphy and screened intervals. Bores were assigned to aquifers by comparing their screen intervals and depth with aquifer boundary data. The required information was extracted from the NGIS database.

## **Dataset History** 

The following steps were followed during the aquifer assignment:



1. Assess the boundaries of aquifers.

2. Determine the screen intervals of bores. 

3. Determine the screen interval of bores for the Queensland bores.

4. Filter bores for a specific area using a shape file or coordinates.

5. Cross-check the final datasets against expert knowledge and spatial context of aquifers.

## **Dataset Citation** 

Bioregional Assessment Programme (2014) CLM - Bore assignments NSW. Bioregional Assessment Derived Dataset. Viewed 28 September 2017, http://data.bioregionalassessments.gov.au/dataset/e035500e-868e-44bb-8993-7c67048773a9.

## **Dataset Ancestors** 

* **Derived From** [NSW Office of Water - National Groundwater Information System  20140701](https://data.gov.au/data/dataset/7ab9820e-1e43-4600-8875-a0834345fb6d)



Tags: Clarence-Moreton bioregion, geoscientificInformation
Organization: Bioregional Assessment Program
CLM - Bore assignments NSW and QLD summary tables

## **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 consists of an MS-Excel spreadsheet which contains worksheets for both NSW and QLD which provide summaries for the results of aquifer assignment.

## **Dataset History** 

Two worksheets were created for Queensland and NSW to summarise the number of bores with different screen codes, respectively. A depth column was added in the summary table to present the depth range of all bores that are screened in a specific aquifer.

## **Dataset Citation** 

Bioregional Assessment Programme (2014) CLM - Bore assignments NSW and QLD summary tables. Bioregional Assessment Derived Dataset. Viewed 28 September 2017, http://data.bioregionalassessments.gov.au/dataset/f92af83d-3db0-4053-b766-4915609db12b.

## **Dataset Ancestors** 

* **Derived From** [CLM - Bore assignments QLD](https://data.gov.au/data/dataset/f8937dd8-b3a0-490e-a452-9dc56fe03914)

* **Derived From** [QLD Dept of Natural Resources and Mines, Groundwater Entitlements 20131204](https://data.gov.au/data/dataset/fd59894f-06b0-4c6f-9029-488934cfa7ba)

* **Derived From** [QLD Dept of Natural Resources and Mines, Groundwater Entitlements linked to bores and NGIS v4 28072014](https://data.gov.au/data/dataset/b1ba5370-2c60-485f-9620-ddad39498999)

* **Derived From** [CLM - Bore assignments NSW](https://data.gov.au/data/dataset/e035500e-868e-44bb-8993-7c67048773a9)

* **Derived From** [QLD Dept of Natural Resources and Mines, Groundwater Entitlements linked to bores v3 03122014](https://data.gov.au/data/dataset/68bbd3fb-6e2a-4088-a3dd-55cc44c2f0d6)

* **Derived From** [NSW Office of Water - National Groundwater Information System  20140701](https://data.gov.au/data/dataset/7ab9820e-1e43-4600-8875-a0834345fb6d)

* **Derived From** [National Groundwater Information System (NGIS) v1.1](https://data.gov.au/data/dataset/e157b1cd-3cb7-4cf9-a13c-a6bed576b8c7)



Tags: Clarence-Moreton bioregion, geoscientificInformation
Organization: Bioregional Assessment Program
Dams of the Murray-Darling Basin region

## **Abstract** 

This dataset was derived from borehole data provided by Geoscience Australia. You can find a link to the source dataset in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived.



This data represents dam centroids of the Murray-Darling Basin.

## **Purpose** 

To illustrate dam localities on a number of Northern Inland Catchments bioregion map elements.

## **Dataset History** 

Dam centroids have been derived from the GEODATA TOPO 250K Series 3 - Infrastructure/DamWalls layer.





http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_a05f7892-ecbd-7506-e044-00144fdd4fa6/GEODATA+TOPO+250K+Series+3+%28Packaged+-+Shape+file+format%29

## **Dataset Citation** 

Bioregional Assessment Programme (2009) Dams of the Murray-Darling Basin region. Bioregional Assessment Derived Dataset. Viewed 27 September 2017, http://data.bioregionalassessments.gov.au/dataset/d0738954-5d72-4796-98e3-cc77a85f6e1e.

## **Dataset Ancestors** 

* **Derived From** [GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)](https://data.gov.au/data/dataset/96ebf889-f726-4967-9964-714fb57d679b)

* **Derived From** [GEODATA TOPO 250K Series 3](https://data.gov.au/data/dataset/a0650f18-518a-4b99-a553-44f82f28bb5f)



Tags: Australia, Gwydir subregion, Maranoa-Balonne-Condamine subregion, inlandWaters
Organization: Bioregional Assessment Program
Queensland GAB monitoring bores 2008: Tabular data

## **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.



This data set represents a subset of the Queensland Groundwater Database (GWDB) data, to include only those groundwater monitoring bores completed in aquifers of the Great Artesian Basin.

## **Dataset History** 

Queensland groundwater monitoring data, both water level and water quality, is stored within the Groundwater Database (GWDB) system. The new system is based on web technology and is available through the department's intranet. Allocation and use data is obtained through the Water Entitlements Registration Database (WERD) which is an electronic database for water license details. Both databases are managed locally at district level, with respect to the collection and entering of water monitoring, allocation and use data; and are accessed statewide.

## **Dataset Citation** 

Queensland Department of Environment and Resource Management (2015) Queensland GAB monitoring bores 2008: Tabular data. Bioregional Assessment Source Dataset. Viewed 27 September 2017, http://data.bioregionalassessments.gov.au/dataset/286fdbc0-4786-476d-836f-cba8773ec263.

Tags: Cooper subregion, Maranoa-Balonne-Condamine subregion, Queensland, geoscientificInformation
Organization: Bioregional Assessment Program
Qld 100K mapsheets - Inglewood

## **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. The polygons in this dataset are a digital representation of the distribution or extent of geological units within the area. Polygons have a range of attributes including unit name, age, lithological description and an abbreviated symbol for use in labelling the polygons. These have been extracted from the Rock Units Table held in the Department of Natural Resources, Mines and Energy Merlin Database.

## **Purpose** 

To display the geology polygons which define the extent of rock units.

## **Dataset History** 

Data captured at 1:75 000 scale. The data set is sourced from the Department's Geoscience and Resources Database (GRDB), a component of the Mineral and Energy Resources Location and Information Network (MERLIN) corporate database. NOTE: GEOLDATA was in most cases compiled based on Datum AGD66. The map tile coverages so compiled have now been projected to geographics based on Datum GDA94. Consequently the boundaries for these map tiles will not conform to the Latitude and Longitude graticule based on Datum GDA94.

## **Dataset Citation** 

"Queensland Department of Natural Resources, Mines and Energy" (2014) Qld 100K mapsheets - Inglewood. Bioregional Assessment Source Dataset. Viewed 28 September 2017, http://data.bioregionalassessments.gov.au/dataset/32869100-6b73-44a4-bcef-c58e380d0b7d.

Tags: Clarence-Moreton bioregion, GEOSCIENCES-Geology, Queensland, geoscientificInformation
Organization: Bioregional Assessment Program
GLO SW Model Calibration Gauges v01

## **Abstract** 

The dataset was derived by the Bioregional Assessment Programme from the Gloucester Surface Water Discharge & Quality extract v1 060314 dataset. The source dataset is 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 is a point shapefile of selected gauges derived from data provided by the The New South Wales Office of Water (NOW) and collated by the Bureau of Meteorology. Daily streamflow data from 16 unregulated catchments collated by the Bureau of Meteorology were used for model calibration. Out of the 16, four contribute to the Gloucester or Karuah river basins, including the Barrington River at Forbesdale (calibration gauge 208006), Gloucester River at Gloucester (208020), Mammy Johnsons River at Pikes Crossing (209002) and Karuah River at Dam site (209018). Of the remaining catchments, five are in the Manning river basin, six are in the Hunter river basin and one is in the Wallis Lake river basin. The history field in this metadata statement describes how this dataset was derived.

## **Dataset History** 

Daily streamflow data from 16 unregulated catchments collated by the Bureau of Meteorology  were used for model calibration. These stream gauging sites for the catchments surrounding the Gloucester subregion were selected to represent the rainfall runoff relationship for catchments in the immediate vicinity. Sixteen gauging sites were selected where data quality and length of record was sufficient to calibrate the surface water model within acceptable error bounds. Site details including location information were sourced from the file Gloucester_subregion_Sites.xlsx which forms part of the source dataset.  The latitude and longitude fields were used to define the location of the selected gauges and a shapefile was created with the attributes table containing these location information and other fields from the site details file.





Criteria for selecting the calibration catchments include that they:

\*	have long term measurements (>20 years from 1980)

\*	are not impacted by coal mining or coal seam gas extraction

\*	have no significant flow regulation (e.g. dams)

\*	are not nested

\*	are close to the Gloucester subregion and have similar catchment sizes and climate regimes.

## **Dataset Citation** 

Bioregional Assessment Programme (XXXX) GLO SW Model Calibration Gauges v01. Bioregional Assessment Derived Dataset. Viewed 18 July 2018, http://data.bioregionalassessments.gov.au/dataset/0336445d-a34c-4a4c-a83d-000a3ed1895d.

## **Dataset Ancestors** 

* **Derived From** [Gloucester Surface Water Discharge & Quality extract v1 060314](https://data.gov.au/data/dataset/5915baad-51c9-4637-9461-88e88426a981)



Tags: Gloucester subregion, climatologyMeteorologyAtmosphere, inlandWaters, utilitiesCommunication
Organization: Bioregional Assessment Program
MBC Groundwater model uncertainty plots

## **Abstract** 

The dataset was derived by the Bioregional Assessment Programme from the MBC Groundwater Model dataset. The source dataset is 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 data set comprises a series of outputs produced from the groundwater model runs. This include drawdown grids corresponding to 95 percentile drawdown obtained as a difference between the baseline and crdp runs. The follwoing steps were involved in producing these outputs.

1) 200 runs each of the baseline and CRDP versions of the model were undertaken



 2) The maximum drawdown (dmax) and time of maximum (Tmax) drawdown were computed for each of the 200 runs for each m odel layer.



3)  The 95th percentile of the Dmax and Tmax were computed by removing the highest 10 (5% of 200) Dmax and Tmax values using the C code in the folder 95_percentile_drawodwn



4) The probablity of exceedence of 5 and 0.2 m drawdown were computed as a percentage of the 200 runs. The probabilities were gridded and plotted to the MBC maps.

## **Purpose** 

These formed the basis of the figures in the MBC 2.6.2 product.

## **Dataset History** 

This a derived data set. All the inputs for this data set were obtained from the groundwater model data set. The outputs have been derived from Monte Carlo runs to produce upper and lower statistical boundaries for uncertainty analysis. Plots were developed for inclusion in the MBC 2.6.2 product using outputs from Python scripts.

## **Dataset Citation** 

Bioregional Assessment Programme (2015) MBC Groundwater model uncertainty plots. Bioregional Assessment Derived Dataset. Viewed 25 October 2017, http://data.bioregionalassessments.gov.au/dataset/44f36874-d053-4cfb-9ccd-d5407e3b1b18.

## **Dataset Ancestors** 

* **Derived From** [MBC Groundwater model](https://data.gov.au/data/dataset/6fe25546-a6ca-44fc-a101-51b1758e2890)

* **Derived From** [MBC Groundwater model mine footprints](https://data.gov.au/data/dataset/6c87cc94-7186-4fdd-a58c-6d52dc5856b1)

* **Derived From** [MBC Groundwater model layer boundaries](https://data.gov.au/data/dataset/32b986d0-c3d0-4a01-a5a9-6fffde638e11)



Tags: Maranoa-Balonne-Condamine subregion, Queensland, geoscientificInformation
Organization: Bioregional Assessment Program
GLO GCM ranking

## **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. 



A table showing GCM (Global climate models) rankings for the Gloucester subregion.

## **Purpose** 

The ranking of GCM was created to select the model that produced median changes in precipitation. The selected model was used to predict future rainfall for the years 2013 to 2102.

## **Dataset History** 

A total of 15 global climate model (GCM) was tested to identify the best GCM to predict future climate data for the Gloucester subregion. The objective in developing a future climate series was to choose the set of GCM's seasonal scaling factors that give the median change in mean annual precipitation. Four seasonal scaling factors for the seasons: summer (December-February), autumn (March-May), winter (June-August) and spring (September-November) were used to predict changes in precipitation in the Gloucester subregion under future climate. For each GCM the change in mean seasonal precipitation for 1 degree global warming was calculated. These seasonal changes were summed to get the change in mean annual precipitation. Based on resulting changes in mean annual precipitation for a 1 degree global warming the GCMs were ranked in ascending order. The GCM that produced median change in annual mean precipitation was selected to predict the future precipitation in the Gloucester subregion for the years 2013 to 2102.

## **Dataset Citation** 

Bioregional Assessment Programme (XXXX) GLO GCM ranking. Bioregional Assessment Derived Dataset. Viewed 18 July 2018, http://data.bioregionalassessments.gov.au/dataset/212c9416-a8bb-48c0-a8e5-83fa375883b0.

## **Dataset Ancestors** 

* **Derived From** [SEACI GCM scaling](https://data.gov.au/data/dataset/bde1e7b7-5bb3-483c-8616-c4176fde8818)



Tags: Gloucester subregion, Queensland, climatologyMeteorologyAtmosphere
Organization: Bioregional Assessment Program
SSB master list coal mines and deposits 20160203 spatial

## **Abstract** 

This dataset was derived by the Bioregional Assessment Programme. The parent 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.



Spatial layer depicting known mine point locations as at Feb 2016. Includes in the attribute table information about mines (eg opencut/underground, owner/operator, date opened etc..) taken from the source database.

## **Purpose** 

Created for the purpose of showing mine locations and status in  report maps.

## **Dataset History** 

Tabular data from the source dataset was reformatted to enable it to be read into ArcGIS. An X Y event layer was then created using the the co-ordinate data (lat long) provided and a spatial later created.

## **Dataset Citation** 

Bioregional Assessment Programme (2016) SSB master list coal mines and deposits 20160203 spatial. Bioregional Assessment Derived Dataset. Viewed 18 June 2018, http://data.bioregionalassessments.gov.au/dataset/bb331c3f-56ca-4fb3-a841-b8103cebb452.

## **Dataset Ancestors** 

* **Derived From** [SSB master list coal mines and deposits 20160203](https://data.gov.au/data/dataset/f21c605d-2860-4aa5-b785-422f56724232)



Tags: New South Wales, Sydney Basin bioregion, economy
Organization: Bioregional Assessment Program