Farm-Scale Modelling for the Spatio-Temporal Prediction of Soil Carbon Sequestration in South-Western Australia: Bringing Soil Carbon Modelling to the Farm Gate

Jolene Otway

doi:10.26182/5ee976a77a300

Farm-Scale Modelling for the Spatio-Temporal Prediction of Soil Carbon Sequestration in South-Western Australia: Bringing Soil Carbon Modelling to the Farm Gate

Jolene Otway

UWA School of Agriculture and Environment

Research output: Thesis › Doctoral Thesis

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Abstract

This research defines a region-specific tuning methodology for internationally accepted soil carbon (C) turnover models. Due to the complex relationships between climate, soil, landscape, and land management leading to cross-field soil C content variations, modelling provides high definition estimates without the cost of intensive sampling. Additionally, balancing science community accuracy and agricultural community practicality within soil C modelling brings soil C estimation to the farm gate through automation, sensitivity simplification and local knowledge integration. The SWARM (South-Western Australian RothC Modelling) Tool exemplifies a globally-applicable methodology which provides fine-scale soil carbon estimation and optimal land selection for carbon sequestration initiatives.

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	The University of Western Australia
Supervisors/Advisors	Abbott, Lynette, Supervisor Barton, Louise, Supervisor Dungait, Jennifer A.J., Supervisor, External person
Thesis sponsors	Australian Government Research Training Program
Award date	25 May 2020
DOIs	https://doi.org/10.26182/5ee976a77a300
Publication status	Unpublished - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 2 Zero Hunger

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10.26182/5ee976a77a300

THESIS - DOCTOR OF PHILOSOPHY - OTWAY Jolene - 2020
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Cite this

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AB - This research defines a region-specific tuning methodology for internationally accepted soil carbon (C) turnover models. Due to the complex relationships between climate, soil, landscape, and land management leading to cross-field soil C content variations, modelling provides high definition estimates without the cost of intensive sampling. Additionally, balancing science community accuracy and agricultural community practicality within soil C modelling brings soil C estimation to the farm gate through automation, sensitivity simplification and local knowledge integration. The SWARM (South-Western Australian RothC Modelling) Tool exemplifies a globally-applicable methodology which provides fine-scale soil carbon estimation and optimal land selection for carbon sequestration initiatives.

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Farm-Scale Modelling for the Spatio-Temporal Prediction of Soil Carbon Sequestration in South-Western Australia: Bringing Soil Carbon Modelling to the Farm Gate

Abstract

UN SDGs

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