- Title
- Predictors of soil organic carbon in agricultural pastures
- Creator
- Kunkel, Veikko R.
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2018
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- The interaction between atmospheric CO₂ and the global pool of soil organic carbon (SOC) is one of the largest and at the same time most uncertain feedbacks of the carbon cycle. The current state, spatial distribution and temporal trends of SOC pools, including for Australian soils, are largely unknown or uncertain, principally because there are too few data available. Hence, ongoing field-sampling and mapping of SOC is necessary. This study assesses the catchment scale climate and geomorphic controls on SOC. The study was conducted in the Upper Hunter Valley, New South Wales, Australia, and focussed on a 562 km² (Krui River) catchment sampled across 41 sites in 2006 and 2014, and a 606 km² (Merriwa River) catchment sampled across 47 sites in 2015. Both catchments have similar soils, topography and landuse. It was found that there was no significant difference in SOC % between Krui 2006 and Krui 2014 data sets. SOC % was also shown to have no significant difference between Krui catchment and Merriwa catchment, indicating that SOC is spatially stable for catchments of similar land-use, climate and geomorphology. SOC % from all three data sets were compared to a range of terrain attributes and cumulative average vegetation indices (VIs). Similar with other studies, elevation, as a surrogate for orographic rainfall, and average Normalised Difference Vegetation Index (NDVI), as a surrogate for historical vegetation SOC input, were found to have the strongest significant controls on SOC %. Confirmation of the use of elevation as a surrogate for rainfall was made by comparing SOC with rainfall obtained from a network of weather stations across the study sites. Krui ΔSOC (change in SOC from 2006 to 2014) was compared to Krui Δ137Cs (change in 137Cs from 2006 to 2014). A moderate but significant relationship was observed between ΔSOC and Δ137Cs, indicating that catchment-scale erosion and deposition processes may control catchment SOC distribution. The findings demonstrate that for catchments with similar soils, topography and climate, SOC can be reliably predicted using linear models that incorporate elevation and/or average NDVI variables. The methods here provide a robust tool which can be used for SOC assessment at other sites as well as assist in understanding SOC distribution and controls for longer term and regional scales.
- Subject
- soil organic carbon; geomorphology; remote sensing; soil carbon modelling
- Identifier
- http://hdl.handle.net/1959.13/1391857
- Identifier
- uon:33302
- Rights
- Copyright 2018 Veikko R. Kunkel
- Language
- eng
- Full Text
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Thesis | 24 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 547 KB | Adobe Acrobat PDF | View Details Download |