Aquaculture suitability data of the Southern Gulf catchments (NT and Qld) generated by the Southern Gulf Water Resource Assessment

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These aquaculture suitability raster datasets (GeoTIFF format) indicate areas of potential suitability for freshwater and marine aquaculture species in earthen or lined ponds. A multi-criteria analysis, involved the integration of soil data and biophysical characteristics within a GIS spatial analysis environment to predict potential sites to inform decision making. A set of limitations and rules were adapted from (McLeod et al., 2002) to determine suitability. These aquaculture datasets were generated within the ‘Land suitability’ activity in consultation with the agricultural viability activity of the Southern Gulf Water Resource Assessment (SOGWRA). The aquaculture suitability analysis 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. There are five suitability classes coded 1-5. 1 – Highly suitable land with negligible limitations 2 – Suitable land with minor limitations 3 – Moderately suitable land with considerable limitations 4 – Currently unsuitable land with severe limitations and 5 – Unsuitable land with extreme limitations. Each drop in suitability implies that more management input (and cost) is required to achieve incremental increases in production. The soil and land characteristics considered for all configurations include; clay content, sodicity and rockiness; and mainly refer to geotechnical considerations (e.g. construction and stability of pond walls). Other limitations, including slope, and the likely presence of gilgai microrelief and acid sulfate soils, infer more difficult, expensive and therefore less suitable development environments, and a greater degree of land preparation effort. Key considerations for earthen ponds included soil properties preventing pond leakage and soil acidity (pH); the latter taking into account negative growth responses of species from unfavourable pH values (i.e. biological limitation) as well as engineering, as pH may affect the structural integrity of earthen walls. Proximity to sea water was considered for marine species although the characteristics of tides and their suitability for marine aquaculture have not been applied in this analysis therefore the full inland distance of tidal waters has not been explored. The aquaculture suitability rules, including the limitation classes and suitability subclasses for each species by pond configuration, is provided in the above referenced publication. It is important to emphasize that this is a regional-scale assessment: further data collection and detailed soil physical, chemical and nutrient analyses would be required to plan development at a scheme, enterprise or property scale. Several limitations that may have a bearing on aquaculture suitability were out of scope and not assessed as part of this activity (refer to the report), these limitations include biophysical and socio-cultural. For example these land suitability raster datasets do not include consideration of the licensing of water, flood risk, risk of irrigation or land tenure and other legislative controls. Some of these may be addressed elsewhere in SOGWRA eg flooding was investigated by the Earth observation remote sensing group in the surface water activity. 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.
Lineage: These aquaculture raster datasets have been generated from a range of inputs and processing steps. Following is an overview. For more information refer to 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. 1. Collated existing data. 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. 6. Create Digital Soil Mapping (DSM) attribute raster datasets. 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. Aquaculture suitability rules created for DSM attributes. 8. Suitability rules were run to produce limitation subclass datasets. 9. Final suitability data created for aquaculture options. 10. QA Quality assessment of these land suitability data was conducted by two methods. Method 1: Statistical (quantitative) assessment of the "reliability" of the spatial output data presented as a raster of the Confusion Index. Method 2: 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.