Enterprise Suitability Toolkit
What are Enterprise Suitability Maps?
Links to Enterprise Suitability Maps
Crop Rules to Guide Suitability
Digital Soil Mapping (DSM): Applying new technologies to soil science
New enterprise suitability maps can assist farmers and prospective investors to analyse potential crop or enterprise options for a property or district. The information is intended as a guide to the further on-farm investigations and business analysis required before making investment decisions.
Importantly at the regional or district level, the tool can help determine the wider potential for new crops, as a guide to the viability of a new enterprise at a state or regional scale.
Enterprise Suitability Maps are currently available for twenty different crops across the 45,000 hectare Meander Valley Irrigation Area, and a 27,000 hectare part of the new Midlands Irrigation Scheme around Tunbridge, Woodbury, York Plains, Nala, Pawtella and Andover. The Meander and southern Midlands were chosen as the two case-study areas for the now completed Wealth from Water Pilot Program. It is anticipated that commencing in 2013 DPIPWE will progressively undertake additional suitability mapping in other areas.
The enterprise suitability mapping data, and the consolidated soil and climate data is also available from DPIPWE for professional advisers and consultants under a standard data sharing agreement. Behind the enterprise suitability mapping sits extensive digital soil attribute modelling, soil profile sampling, and 12-months of continuous on-farm temperature and climate sampling correlated against historical weather state records.
Enterprise Suitability Maps page. Users can view the maps, zoom into specific locations, and also overlay other useful data sets. The suitability maps cover the following crops: barley; blueberries; carrot seed; carrots; cherries; hazelnuts; industrial hemp; linseed; lucerne; olives; onions; poppies; potatoes; pyrethrum; raspberries; rye grass for dairy; strawberries; wheat and wine grapes (pinot noir and chardonnay).
Crop Site Suitability Fact Sheets
For further information:
Contact: Section Leader-SLIMRhys Stickler
Section Leader - Sustainable Landuse & Information Management (SLIM)
Phone: 03 6336 5276
Prior to the Wealth from Water pilot program, soil mapping in the Meander Valley and Southern Midland was not at the scale, format or quality to allow for a detailed assessment of land suitability, for example 1:50,000 or better. Digital Soil Mapping (DSM) – or predictive soil mapping – was used to generate soil property surfaces. When compared to traditional soil mapping, these techniques can produce more realistic three dimensional and continuous soil property surfaces, while requiring fewer field sites and associated resources. Importantly, DSM also has the ability to derive information on the reliability (or uncertainty) of mapping produced by the modelling process.
With support from an Australian Research Council Linkage Grant, DPIPWE have partnered with University of Sydney Faculty of Agriculture, Food and Natural Resources and CSIRO Land and Water to undertake and develop the appropriate DSM approaches.
Traditional vs Digital Soil Mapping
Traditional soil property mapping requires development of subjective soil-landscape models and typical soil profile classes. Wherever these soil profile classes are mapped to occur in the landscape, it is assumed that summarised chemical and physical characteristics will be the same. These maps, while useful for communicating soil formation processes, do not necessarily produce realistic soil information for property or sub regional planning.
The DSM approach differs from these methods, in that the soil characteristics measured at each sampling site are extrapolated across the entire landscape in combination with information generated from a number of supporting datasets (e.g digital elevation models and vegetation mapping). The project also uses Gamma radiometrics, which is a measure of the natural radiation in the earth’s surface, which identifies the distribution of certain soils and rocks. Final outputs are shown as pixellated (raster) mapping, each pixel having its own set of attributes, which better represent the continuous nature of landscape soil properties.
An initial product of the mapping process is a “soil drainage map”. A number of sophisticated statistical analysis tools were used to model the soil drainage across the landscape, based on available supporting data and soil sampling. Initial field investigations indicate realistic results, which will be improved and statistically validated once remaining soil analysis and soil property surfaces are completed during 2011.
Modelling is Based on Soil Sampling
The DSM approach was initially being trialled in the Meander East irrigation district. In order to inform a statistically sound soil sampling design, an initial desk-top analysis was undertaken using existing soils and landscape data including existing 1:100,000 soil mapping. Physical sampling was then undertaken for 200 sites using a “Conditioned Latin Hypercube” sampling design, which is a randomised sampling approach that ensures the entire landscape is effectively sampled, (Minasny & McBratney, 2005). Soil cores were sub-sampled according to soil horizon, with samples undergoing Mid Infra Red and Near Infra Red scanning, and chemical calibration analysis.
Ground-based gamma radiometric mapping was also undertaken to help predict soil properties where no such data existed. Spatial soil surfaces (pH, EC, Clay %, Soil Depth, Stone %, Drainage), are now being generated using various modelling techniques (using data such as geology, existing soil maps, radiometrics, and terrain characteristics), to inform the enterprise suitability model for poppies, blueberries, carrots, barley, hazelnuts, pyrethrum and hemp crops.
Soil surfaces generated are validated by sampling a further 60 sites across the study area to compare modelled to actual soil information.
Findings to Date
Initial predictive outputs for various soil properties are encouraging. Further statistical analysis and field validation will provide insight into which of the numerous DSM techniques are most appropriate for Tasmanian irrigation areas. Traditional soil mapping methods are still considered beneficial in explaining soil formation processes and extents, communicable soil profile classes, and informing sustainable farming management. However, DSM tools will enhance these traditional approaches, especially in the generation of three-dimensional soil property surfaces with attached reliability assessments.
The work on the Wealth from Water pilot project has shown significant demand for property and regional scale decision support tools for matching agricultural enterprise options to land. The integration of raster based soil and climate information with well understood crop suitability rules provides a strategic advantage in the selection of enterprises for further investigation of market potential and social attractiveness for investment. The soil mapping produced also provides opportunities to enhance associated predictive mapping of biological habitats.
For further information on Digital Soil Mapping contact Darren Kidd, Senior Land Resource Analyst at the Land Conservation Branch on Phone:(03) 6336 5246 or email: Darren.Kidd@dpipwe.tas.gov.au
Tasmania Online | Service Tasmania
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