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SOIL An interactive open-access journal of the European Geosciences Union
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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  16 Jul 2020

16 Jul 2020

Review status
This preprint is currently under review for the journal SOIL.

Mapping soil slaking index and assessing the impact of management in a mixed agricultural landscape

Edward J. Jones1, Patrick Filippi1, Rémi Wittig2, Mario Fajardo1, Vanessa Pino1, and Alex B. McBratney1 Edward J. Jones et al.
  • 1School of Life and Environmental Sciences & Sydney Institute of Agriculture, Faculty of Science, The University of Sydney, New South Wales, Australia
  • 2École Nationale Supérieure d'Agronomie et des Industries Alimentaires (ENSAIA), University of Lorraine, France

Abstract. Soil aggregate stability is a useful indicator of soil physical health and can be used to monitor condition through time. A novel method to quantify soil aggregate stability, based on the relative increase in the footprint area of aggregates as they disintegrate when immersed in water, has been developed and can be performed using a smartphone application – SLAKES. In this study the SLAKES application was used to obtain slaking index (SI) values of topsoil samples (0 to 10 cm) at 158 sites to assess aggregate stability in a mixed agricultural landscape. A large range in SI values of 0 to 7.3 was observed. Soil properties and land use were found to be correlated with observed SI values. Soils with clay content > 25 % and CEC : clay ratio > 0.5 had the highest observed SI values. Variation in SI for these soils was driven by OC content which fit a segmented exponential decay function. An OC threshold of 1.1 % was observed below which the most extreme SI values were observed. Soils under dryland and irrigated cropping had lower OC content and higher observed SI values compared to soils under perennial cover. These results suggest that farm managers can mitigate the effects of extreme slaking by implementing management practices to increase OC content, such as minimum tillage or cover-cropping. A regression-kriging method utilising a Cubist model with a suite of spatial covariates was used to map SI across the study area. Accurate predictions were produced with leave-one-out cross-validation (LOOCV) giving an LCCC of 0.85 and an RMSE of 1.1. Similar validation metrics were observed in an independent test set of samples consisting of 50 observations (LCCC = 0.82; RMSE = 1.1). The potential impact of implementing management practices that promote soil OC sequestration on SI values in the study area was explored by simulating how a 1 % increase in OC would impact SI values at observation points, and then mapping this across the study area. Overall, the maps produced in this study have the potential to guide management decisions by identifying areas that currently experience extreme slaking, and those areas that are expected to have a significant reduction in slaking by increasing OC content.

Edward J. Jones et al.

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Edward J. Jones et al.

Edward J. Jones et al.


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