Deakin Carbon Project
ERF162592
Project Information:
The Deakin Carbon Project is a soil carbon sequestration project located in the Southern Tablelands of New South Wales, approximately 25 kilometers north of Goulburn and 20 kilometers southeast of Crookwell. Registered in January 2021, the project covers a land area of roughly 306 hectares within the Upper Lachlan Shire. The property is situated in the vicinity of Pejar Dam, a region characterised by rolling grazing country.
The project operates under the Estimation of Soil Organic Carbon Sequestration using Measurement and Models (2021) methodology. This method is a hybrid approach that allows project proponents to calculate carbon abatement by combining physical soil core sampling with computer modelling. This specific project transitioned to the 2021 methodology in September 2022, having originally been registered under the 2018 measurement-only determination. This shift is common among Agriprove projects, as the 2021 method reduces the cost and frequency of physical sampling required to earn Australian Carbon Credit Units (ACCUs).
Environmentally, the Upper Lachlan region is a cool temperate zone well-suited to livestock grazing, which is the primary land use in the area. The region generally experiences reliable rainfall, with the nearby Pejar locality recording an annual average of approximately 800mm. The soils in this part of the Southern Tablelands are typically derived from a mix of granite and basalt parent materials, forming loams and clay-loams that support improved pastures.
The project activities focus on regenerative agricultural practices designed to build soil health. Specifically, the project involves altering the stocking rate, duration, and intensity of grazing. By optimizing grazing pressure (often through time-controlled or cell grazing), the project aims to increase ground cover and root biomass, thereby sequestering more atmospheric carbon into the soil profile. The proponent, Agriprove Solutions, manages the project and utilizes satellite imagery and data modelling to monitor these outcomes.
