GLO AWRA Model v01

Created 12/07/2018

Updated 20/11/2019

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.

The dataset contains 20,000 files, half of these are streamflow simulated under baseline condition and the other half are streamflow simulated under the CRDP condition. The difference between CRDP and baseline is used for predicting ACRD impacts on hydrological response variables in 30 simulation nodes (Zhang et al., 2016).

References

Zhang Y Q, Viney N R, Peeters L J M, Wang B, Yang A, Li L T, McVicar T R, Marvanek S P, Rachakonda P K, Shi X G, Pagendam D E and Singh R M (2016) Surface water numerical modelling for the Gloucester subregion. Product 2.6.1 for the Gloucester subregion from the Northern Sydney Basin Bioregional Assessment. Department of the Environment, Bureau of Meteorology, CSIRO and Geoscience Australia, Australia., Department of the Environment, Bureau of Meteorology, CSIRO and Geoscience Australia, Australia., http://data.bioregionalassessments.gov.au/product/NSB/GLO/2.6.1.

Purpose

To quantify the impacts of mining development on hydrological response variables for Gloucester subregion

Dataset History

This metadata has been overwritten by Version 2. Please refer to GLO AWRA Model v02 and its registration details are in below.

GLO AWRA Model v02

SYD\GLO\DATA\RiskAndUncertainty\Model\GLO_AWRA_LR_v02

http://data.bioregionalassessments.gov.au/dataset/018bfc12-6b9f-4ccc-83e4-e002cfd72b6a

The dataset has all files and scripts necessary to execute the 10,000 runs on the linux platform of the CSIRO High Performance Cluster computers.

The main script is 'STEP3_CaolMining_ImpactAnalysis_DailyOutputsNewScalingF_update.m', which is uploaded at the following folder\lw-osm-01-cdc.it.csiro.au\OSM_CBR_LW_BAModelRuns_app\GLO\AWRA_postprocessing\mfiles. This scripts does postprocessing using mine footprint data together with AWRA_L surface water model outputs (GUID: http://data.bioregionalassessments.gov.au/dataset/63549eae-6632-4a45-bfda-5793454955f1) and MODFLOW groundwater outputs (GUID: http://data.bioregionalassessments.gov.au/dataset/9d732408-003e-4901-86a7-cea95b585640).

The script was compiled into an executable file on the linux platform, and has been computed for getting 10,000 jobs running in a parallel way.

The dataset was uploaded to

\OSM-07-CDC.it.csiro.au\OSM_CBR_LW_BA_working\SYD\DATA_in_progress\GLO\Data\Hydrology\GLO_AWRA_outputs_v01 on 20 June 2016

This dataset were further computed to get 9 hydrological response variables (AF, P99, FD, IQR, ZFD, P01, LFD, LFS, LLFS) under CRDP and baseline conditions, respectively

Dataset Citation

Bioregional Assessment Programme (2015) GLO AWRA Model v01. Bioregional Assessment Derived Dataset. Viewed 12 July 2018, http://data.bioregionalassessments.gov.au/dataset/15ca8f9d-84b4-4395-87db-ab4ff15b9f07.

Dataset Ancestors

Files and APIs

This dataset has no data

Tags

Additional Info

Field Value
Title GLO AWRA Model v01
Language eng
Licence Restricted access. This dataset is not available for public distribution.
Landing Page https://devweb.dga.links.com.au/data/dataset/2190dfa2-707e-4afe-be4e-96d974f19be5
Contact Point
Bioregional Assessment Program
bioregionalassessments@environment.gov.au
Reference Period -
Geospatial Coverage POLYGON ((0 0, 0 0, 0 0, 0 0))
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "GLO AWRA Model v01". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/15ca8f9d-84b4-4395-87db-ab4ff15b9f07

  • GLO AWRA Model v01

    Bioregional Assessment Program

    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...

    Dataset updated: 20/11/2019

No duplicate datasets found.