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Abstract	Soil waterlogging hazard was digitally mapped as part of the DPIPWE Water for Profit Program to enhance identification of Enterprise Suitability by effectively incorporating a sustainability measure of vulnerable soils. The mapping shows areas where a waterlogging hazard might exist if sufficient management is not applied, which could lead to soil resource degradation, trafficability issues and crop losses. Assigned classes are; Nil, Very Low, Low, Moderate, High and Very High as classified ratings of a waterlogging hazard index. The index was generated by combining Digital Soil Mapping (DSM) inputs of the soil properties of soil drainage index and permeability index, and mapped areas of flood risk, where very poor drainage and low permeability imply a high waterlogging hazard, and rapid drainage and high permeability imply a low waterlogging hazard. The mapping covers the entire state of Tasmania at 30m resolution.
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Each Raster cell is attributed by multiple soil models to arrive at an erodibility rating. The accuracy is therefore limited by the precision of the input models. The result of the validation diagnostics can be made available for each surface on request. The input soil models validated to at least a reasonable level with the standard error within acceptable ranges. Preliminary field validation was carried out to ensure integrity had been maintained and from this, attribute accuracy of the suitability categories was estimated to be no worse than 70%. 
During the Water for Profit project in 2015-2017 an additional 400 soil sites were sampled and combined with approximately 6,500 DPIPWE soil database sites. Logical Consistency: All raster cell data are labelled with an approximate waterlogging hazard rating. There are no duplicates. Completeness: The spatial layers cover the entire state of Tasmania, excluding Macquarie Island. Additional: Component layers of Digital Soil Mapping components are available upon request.

Statement 	
Digital Soil Assessment is being used to model land suitability in recently commissioned irrigation schemes in the State of Tasmania, Australia, in support of Government agricultural expansion policy. The model requires comprehensive soil, climate and terrain parameters to rate the suitability of land for each chosen enterprise. The Wealth from Water pilot program commenced in a 20,000 ha irrigation district in the Meander Valley Region. This was later extended to cover a further 25,000 ha in the Meander area, 27,000 ha through the Midlands around Tunbridge, Woodbury, York Plains, Nala and Andover and an additional 10,000ha on Flinders Island. The project has now evolved to the state wide extent as part of the Water for Profit program, an element of the Tasmanian government AgriVision 2050 plan for agriculture with an additional concentration of soil and climate sampling occurring for the Midlands area of Tasmania (approximately 40,000 ha of additional detailed analysis). Digital soil mapping techniques were used to produce soil information at 30m resolution. Soil attribute spatial layers were produced from interpolation of the soil core data using the regression trees data mining algorithm in concert with predictive covariate data such as the SRTM DEM and derivatives, Gamma Radiometrics, legacy soil map, surface geology, and Satellite imagery. Layers produced included soil depth, pH, electrical conductivity, clay and stone content, drainage, and depth to sodic and/or impeding layer. Uncertainty assessment of the surfaces involved running a K-fold cross validation procedure, the result of which can be requested from the custodian. In general, however, the assessment resulted in acceptable prediction accuracies for each surface with the Root Mean Square Error (RMSE), R2 and concordance coefficient within acceptable ranges. The diagnostics information and waterlogging hazard rankings can be made available upon request. The combination of soil drainage, permeability data and flood risk was used to generate the erosion hazard rating, appropriate management of soil drainage can be found in the DPIPWE management guidelines, here:

Vulnerable Soils - https://nrmdatalibrary.dpipwe.tas.gov.au/FactSheets/WfW/ListMapUserNotes/Vulnerable_soils.pdf

Further reading:

Kidd, D. B. (2003). "Land Degradation and Salinity Risk Investigation in the Tunbridge District, Tasmanian Midlands." Department of Primary Industries, Parks, Water and the Environment.  Tasmania, Australia. (https://www.researchgate.net/publication/283615050_Land_Degradation_and_Salinity_Risk_Investigations_Tunbridge_Tasmania).

Kidd, D., Malone, B., Mcbratney, A., Minasny, B., Odgers, N., Webb, M., Searle, R., 2014a. A New Digital Soil Resource for Tasmania, Australia, 20th WORLD CONGRESS OF SOIL SCIENCE, pp. 612-613;

Kidd, D., Webb, M., Malone, B., Minasny, B., McBratney, A., 2015a. 80-metre Resolution 3D Soil Attribute Maps for Tasmania, Australia. Soil Research;

Kidd, D., Webb, M., Malone, B., Minasny, B., McBratney, A., 2015b. Digital soil assessment of agricultural suitability, versatility and capital in Tasmania, Australia. Geoderma Regional 6, 7-21;

Kidd, D.B., Malone, B.P., McBratney, A.B., Minasny, B., Webb, M.A., 2014b. Digital mapping of a soil drainage index for irrigated enterprise suitability in Tasmania, Australia. Soil Research 52, 107-119;

Kidd, D.B., Webb, M.A., Grose, C.J., Moreton, R.M., Malone, B.P., McBratney, A.B., Misnasny, B., Viscarra-Rossel, R.A., Cotching, W.E., Sparrow, L.A., Smith, R., 2012. Digital soil assessment: Guiding irrigation expansion in Tasmania, Australia. In: Minasny, B., A. B. McBratney, et al. (2012). Digital Soil Assessments and Beyond: Proceedings of the 5th Global Workshop on Digital Soil Mapping 2012, Sydney, Australia, Taylor & Francis;

Kidd, D.B., Webb, M.A., McBratney, A.B., Minasny, B., Malone, B.P., Grose, C.J., Moreton, R.M., 2014c. Operational Digital Soil Assessment for Enterprise Suitability in Tasmania, Australia., in: Arrouays, D., McKenzie, N.J., Hempel, J., Richer-de-Forges, A.C., McBratney, A. (Eds.), GlobalSoilMap: Basis of the global spatial soil information system. CRC Press, Orleans, France, pp. 113-120;

Webb, M., Hall, A., Kidd, D., Minasny, B., 2015. Local-scale spatial modelling for interpolating climatic temperature variables to predict agricultural plant suitability. Theor Appl Climatol, 1-21;

Webb, M (2015) Incorporating Climate Futures into Enterprise Suitability Mapping -Technical report. Department of Primary Industries, Parks, Water and Environment. Launceston,Tasmania. URL:http://www.dpac.tas.gov.au/__data/assets/pdf_file/
0009/266184/Incorporating_Climate_Futures_Tasmania_into
_Enterprise_Suitability_Mapping_Technical_Report.pdf

Webb, M., Pirie, A., Kidd, D., Minasny, B. 2017. Spatial analysis of frost risk to determine viticulture suitability in Tasmania, Australia. Australian Journal of Grape and Wine Research 24, 219-233.

Dataset Classification Definitions-
6: Very High
8: High
10: Moderate
14: Low
18: Very Low

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