SOIL
SOIL
SOIL
Articles | Volume 10, issue 2
Articles | Volume 10, issue 2
https://doi.org/10.5194/soil-10-619-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-10-619-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 2
Original research article
 | 
10 Sep 2024
Original research article |  | 10 Sep 2024

An ensemble estimate of Australian soil organic carbon using machine learning and process-based modelling

Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, and Raphael A. Viscarra Rossel

Data sets

Soil and Landscape Grid National Soil Attribute Maps - Clay (3" resolution) - Release 2. v5. CSIRO Brendan Malone and Ross Searle https://doi.org/10.25919/hc4s-3130

Soil and Landscape Grid National Soil Attribute Maps - Bulk Density - Whole Earth - Release 2 Brendan Malone https://doi.org/10.25919/gxyn-pd07

MODIS/Terra Net Primary Production Gap-Filled Yearly L4 Global 500m SIN Grid V061 S. Running and M. Zhao https://doi.org/10.5067/MODIS/MOD17A3HGF.061

Model code and software

Wanglingfei170/MIMICS: MIMICS-Australia (v1.0-MIMICS-Aus) Lingfei Wang https://doi.org/10.5281/zenodo.13638194

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Short summary
Effective management of soil organic carbon (SOC) requires accurate knowledge of its distribution and factors influencing its dynamics. We identify the importance of variables in spatial SOC variation and estimate SOC stocks in Australia using various models. We find there are significant disparities in SOC estimates when different models are used, highlighting the need for a critical re-evaluation of land management strategies that rely on the SOC distribution derived from a single approach.
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