A regolith depth map of the Australian continent

Wilford, John; Searle, Ross; Thomas, Mark; Pagendam, Dan; Grundy, M. J.

doi:10.1016/j.geoderma.2015.11.033

Cited by 51 publications

(42 citation statements)

References 18 publications

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“…Few studies have used DSM approaches to map the depth-to-soil constraints, but there has been considerable research in mapping the depth to bedrock [42][43][44]. The methods used in these studies are essentially traditional DSM approaches, and differ significantly from the current study.…”

Section: Modelling/mapping Approach and Validationmentioning

confidence: 99%

“…The methods used in these studies are essentially traditional DSM approaches, and differ significantly from the current study. For example, data for the depth to which bedrock is reached is commonly available from mining exploration and bore hole drilling exercises, and Wilford et al [44] used a database of these observations to create depth-to-bedrock maps of Australia using a Cubist model. In contrast, rather than use direct observations of the depth of the target variable/constraint, the current study uses splined soil pH data, and machine learning to predict the depth in which an alkalinity constraint is reached at each 1-cm vertical increment, which is then combined to create a depth-to-soil pH constraint map.…”

Section: Modelling/mapping Approach and Validationmentioning

confidence: 99%

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Mapping the Depth-to-Soil pH Constraint, and the Relationship with Cotton and Grain Yield at the Within-Field Scale

et al. 2019

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Subsoil alkalinity is a common issue in the alluvial cotton-growing valleys of northern New South Wales (NSW), Australia. Soil alkalinity can cause nutrient deficiencies and toxic effects, and inhibit rooting depth, which can have a detrimental impact on crop production. The depth at which a soil constraint is reached is important information for land managers, but it is difficult to measure or predict spatially. This study predicted the depth in which a pH (H2O) constraint (>9) was reached to a 1-cm vertical resolution to a 100-cm depth, on a 1070-hectare dryland cropping farm. Equal-area quadratic smoothing splines were used to resample vertical soil profile data, and a random forest (RF) model was used to produce the depth-to-soil pH constraint map. The RF model was accurate, with a Lin’s Concordance Correlation Coefficient (LCCC) of 0.63–0.66, and a Root Mean Square Error (RMSE) of 0.47–0.51 when testing with leave-one-site-out cross-validation. Approximately 77% of the farm was found to be constrained by a strongly alkaline pH greater than 9 (H2O) somewhere within the top 100 cm of the soil profile. The relationship between the predicted depth-to-soil pH constraint map and cotton and grain (wheat, canola, and chickpea) yield monitor data was analyzed for individual fields. Results showed that yield increased when a soil pH constraint was deeper in the profile, with a good relationship for wheat, canola, and chickpea, and a weaker relationship for cotton. The overall results from this study suggest that the modelling approach is valuable in identifying the depth-to-soil pH constraint, and could be adopted for other important subsoil constraints, such as sodicity. The outputs are also a promising opportunity to understand crop yield variability, which could lead to improvements in management practices.

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Section: Modelling/mapping Approach and Validationmentioning

confidence: 99%

Section: Modelling/mapping Approach and Validationmentioning

confidence: 99%

Mapping the Depth-to-Soil pH Constraint, and the Relationship with Cotton and Grain Yield at the Within-Field Scale

et al. 2019

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“…Estimates of the depth to magnetic source based on the gradient properties of the magnetic anomalies help to discriminate between magnetic and nonmagnetic components of the regolith and bedrock. Wilford et al (2016) have used the full range of such geophysical and geological constraints in conjunction with multi-scale attributes from digital topography to develop a model for regolith thickness across the whole continent. They use a database of depth to bedrock derived from drillhole data as the training dataset.…”

Section: Regolith Thicknessmentioning

confidence: 99%

The Australian Continent: A Geophysical Synthesis

Chopping¹,

Blewett²

2018

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This synthesis of geophysical results for Australia is designed to provide an summary of the character of the Australian continent through the extensive information available at the continental scale. We present a broad range of geophysical attributes for the continent nation. We also endeavour to examine the relationships between different fields, and their relations to known resources. The work represents part of a continuing collaboration between the Research School of Earth Sciences at The Australian National University and Geoscience Australia, with the objective of bringing together all aspects of the structure of Australia in convenient forms. The results build on the extensive databases assembled at Geoscience Australia, particularly for potential fields, supplemented by the full range of seismological information mostly from The Australian National University. The book builds in part on the AuSREM project, sponsored by the AuScope infrastructure organisation, to develop a 3-D representation of seismological structure beneath the Australian region.

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“…Figure 4.6, based on the work of Wilford (2011b), illustrates the idealized evolution of regolith, with the concomitant losses of cations (useful for calculating weathering ratios), as well as changes in properties of the regolith such as permeability and water holding capacity, fertility, and biological activity. Although weathering varies by three-dimensional space, across geographic area and into the surface thickness, it also varies over time.…”

Section: Rock Decay In the Fourth Dimension: Time And Rates In The Crmentioning

confidence: 99%

Regolith and Weathering (Rock Decay) in the Critical Zone

Pope

2015

Developments in Earth Surface Processes

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A regolith depth map of the Australian continent

Cited by 51 publications

References 18 publications

Mapping the Depth-to-Soil pH Constraint, and the Relationship with Cotton and Grain Yield at the Within-Field Scale

Mapping the Depth-to-Soil pH Constraint, and the Relationship with Cotton and Grain Yield at the Within-Field Scale

The Australian Continent: A Geophysical Synthesis

Regolith and Weathering (Rock Decay) in the Critical Zone

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