https://nova.newcastle.edu.au/vital/access/ /manager/Index en-au 5 Spatial uncertainty of (137)Cs-derived net (1950s-1990) soil redistribution for Australia https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:14371 137Cs) technique has been used successfully in many parts of the world to estimate net (ca. 30–50 years) soil redistribution by wind and water erosion and tillage activities. The point‐based technique has hitherto been confined largely to individual fields and hillslopes, particularly in Australia. Its application here to the Australian continent (≈5 km grid) was achieved using geostatistics and nationally coordinated measurements (early 1990s) from ≈200 locations at the ≈1 km scale. A map of the 137Cs reference inventory for Australia has been previously established. Sequential indicator co‐simulation of the 137Cs inventory and the Australian Soil Classification was used to estimate net (between mid‐1950s and early 1990s) soil redistribution using the Australian Empirical Model. This geostatistical approach showed that nearly five times more soil was lost from cultivated land (−4.29 to +0.17t ha-1 yr-1) than from uncultivated (−0.91 to +0.05t ha-1yr-1) land in Australia. This information on spatial uncertainty is essential for regional soil management to assess the risk to soil conservation. Soil erosion exceeding a tolerable threshold value (e.g., 0.5 t ha-1 yr-1) occurred over 16% of Australia, mainly in cultivated regions (median = −1.26t ha-1yr-1). Soil erosion estimates are neglected in carbon balances for greenhouse gas abatement and carbon accounting models. Reliable quantitative data on the recent extent and rates of soil erosion are needed to underpin the selection of effective soil conservation measures, to inform carbon balances and to understand regional soil function for sustainable agricultural systems.]]> Wed 11 Apr 2018 13:01:35 AEST ]]> On the estimation of scale of fluctuation in geostatistics https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:21335 in situ cone penetration test (CPT) data. The first method belongs to the family of more traditional approaches, which are based on best fitting a theoretical correlation model to available CPT data. The second method involves a new strategy which combines information from conditional random fields with the traditional approach. Both methods are applied to a case study involving the estimation of θ at three two-dimensional sections across a site and the results obtained show general agreement between the two methods, suggesting a similar level of accuracy between the new and traditional approaches. However, in order to further assess the relative accuracy of estimates provided by each method, a second numerical analysis is proposed. The results confirm the general consistency observed in the case study calculations, particularly in the vertical direction where a large amount of data are available. Interestingly, for the horizontal direction, where data are typically scarce, some additional improvement in terms of relative error is obtained with the new approach. © 2013 Taylor & Francis.]]> Sat 24 Mar 2018 07:52:50 AEDT ]]>