Soil generic group (SGG) DSM data of the Southern Gulf catchments (NT and Qld) generated by the Southern Gulf Water Resource Assessment

Soil generic group (SGG) is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Southern Gulf Water Resource Assessment (SOGWRA) through the digital soil mapping process (DSM). SGG data has been created to simplify the complex information of individual soils and soil attributes for extension, planning and management. This data simultaneously covers a number of purposes: to be descriptive so as to assist non-expert communication regarding soil and resources; to be relatable to agricultural potential; and to align, where practical, to the classes of the Australian Soil Classification system (ASC) (Isbell and National Committee on Soil and Terrain, 2016). This SGG raster data represents a modelled dataset of 13 classes derived from rules applied to measured site data and modelled with environmental covariates. Descriptions of the 13 SGG classes, their rules and the spatial data value descriptions are supplied with this data. SGG mapping was also used as a minor input into the land suitability framework but primarily as a communication tool. This raster data provides improved soil information used to underpin and identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO SOGWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach. The DSM process is described in the CSIRO SOGWRA published report ‘Soils and land suitability for the Southern Gulf catchments’. A technical report from the CSIRO Southern Gulf Water Resource Assessment to the Government of Australia. The Southern Gulf Water Resource Assessment provides a comprehensive overview and integrated evaluation of the feasibility of aquaculture and agriculture development in the Southern Gulf catchments NT and Qld as well as the ecological, social and cultural (indigenous water values, rights and aspirations) impacts of development. \nLineage: This soil generic group dataset has been generated from a range of inputs and processing steps. Following is an overview. For more information refer to the CSIRO SOGWRA published reports and in particular ' Soils and land suitability for the Southern Gulf catchments’. A technical report from the CSIRO Southern Gulf Water Resource Assessment to the Government of Australia. 1. Collated existing data (relating to: soils, climate, topography, natural resources, remotely sensed, of various formats: reports, spatial vector, spatial raster etc). 2. Selection of additional soil and land attribute site data locations by a conditioned Latin hypercube statistical sampling method applied across the covariate data space. 3. Fieldwork was carried out to collect new attribute data, soil samples for analysis and build an understanding of geomorphology and landscape processes. 4. Database analysis was performed to extract the data to specific selection criteria required for the attribute to be modelled. 5. The R statistical programming environment was used for the attribute computing. Models were built from selected input data and covariate data using predictive learning from a Random Forest approach implemented in the ranger R package. 6. Create soil generic group Digital Soil Mapping (DSM) attribute raster dataset. DSM data is a geo-referenced dataset, generated from field observations and laboratory data, coupled with environmental covariate data through quantitative relationships. It applies pedometrics - the use of mathematical and statistical models that combine information from soil observations with information contained in correlated environmental variables, remote sensing images and some geophysical measurements. 7. Companion predicted reliability data was produced from the 500 individual Random Forest attribute models created. 8. QA Quality assessment of this DSM attribute data was conducted by three methods. Method 1: Statistical (quantitative) method of the model and input data. Testing the quality of the DSM models was carried out using data withheld from model computations and expressed as OOB and confusion matrix results, giving an estimate of the reliability of the model predictions. These results are supplied. Method 2: Statistical (quantitative) assessment of the spatial attribute output data presented as a raster of the attributes “reliability”. This used the 500 individual trees of the attributes RF models to generate 500 datasets of the attribute to estimate model reliability for each attribute. For categorical attributes the method for estimating reliability is the Confusion Index. This data is supplied. Method 3: A workshop was conducted in March 2023 to review DSM soil attribute and land suitability products and facilitated an alternative to the field external validation carried out in other northern Australia water resource assessments. Stakeholders from the NT and Qld jurisdictions reviewed, evaluated and discussed the soundness of the data and processes. The workshop desk top assessment approach provided recommendations for acceptance, improvement and re-modelling of attributes based on expert knowledge and understanding of the soil distribution and landscape in the study area and available data.\n