Hia - I’m on the hunt for someone to conduct a relatively discrete and well specified analysis of an existing workflow using the RothC soil model.
Unfortunately, this is only open to Australians. I have funding for approximately 20 days and would suit a mid-term or recently finished PhD student. Ecological literacy would be great but not required.
Please email firstname.lastname@example.org for more information.
This position is still available and I now have an approved brief!
16 Feb. 21
RE: Development of satellite driven soil carbon measurements
Climate Friendly believe that a data driven modelling approach, using satellite imagery and biomass measurements, is necessary to unlock extensive application of a soil carbon method. Roughly 55% of Australia (4.2 million ha) is managed for grazing, nearly always on properties that are too large to be commercially viable under the Measured Soil Method (2018).
The Rothamsted soil carbon model (RothC) has been well tested across Australian conditions and forms a core component of the Australian Government’s Full Carbon Accounting Model (FullCAM). In fact, RothC was used to derive the regional sequestration rates in the Default Soil Method (2015). With recent advances in remotely sensed biomass and cover data, this model (RothC) can now be accurately applied at the project scale and supplement traditional soil measurement.
We require a soil scientist, data scientist or statistician familiar with parameterising dynamical systems models to help derive RothC soil carbon calibrations that leverage remotely sensed biomass and ground cover data to provide accurate abatement estimates. The successful applicant will be required to build on Climate Friendly’s existing preliminary analysis to constrain the RothC model, using existing libraries of measured soil carbon and soil carbon fractions (e.g. SCaRP; Sanderman et al., 2011). The successful applicant would then work with the Climate Friendly team to make suggestions for a revised soil carbon method that can be applied nationally.
This calibration will be the core deliverable of your internship. We expect this to take approximately 20 working days and would suit a late-stage or recently graduated PhD student, with support from our internal R&D team. Familiarity with differential equations; frequentist or Bayesian optimisation; R, Python or Stan are desired. We support the participation of groups underrepresented in STEM and encourage women, Aboriginal and Torres Strait Islander people to apply.
For enquiries and applications, please contact:
Dr. Andrew O’Reilly-Nugent