A comparison of predictive soil-carbon models across multiple spatio-temporal catchment scales.

Monday, 15 December 2014
Veikko Kunkel1, Greg R Hancock2 and Tony Wells1, (1)University of Newcastle, Callaghan, Australia, (2)University of Newcastle, Callaghan, NSW, Australia
Soil’s potential as a carbon sink for atmospheric CO2 has been widely discussed. Studies of soil organic carbon (SOC) controls, and the subsequent models derived from their findings, have focussed mainly on North American and European regions, and more recently, in regions such as China. In Australia, agricultural practices have led to losses in SOC. This implies that Australian soils have a large potential for increases in SOC. Building on previous work, here we examine the spatial and temporal variation in soil organic carbon (SOC) and its controlling factors controls across a large catchment of approximately 600 km2 in the Upper Hunter Valley, New South Wales, Australia, using data collected from two sampling campaigns, (April 2006 and June-July 2014). Remote sensing using Landsat (30m) and MODIS (250m) NDVI was used to determine if catchment SOC could be predicted using both low and high resolution remote sensing . Relationships between SOC and elevation, aboveground biomass (as represented by NDVI), topographic wetness index (TWI), and incident solar radiation as a surrogate for soil temperature were compared. Initial results demonstrate that higher spatio-temporal resolution may not be necessary for predicting SOC at larger scales. The relationship between SOC and the environmental tracer 137-Cesium as a surrogate for the loss of SOC by erosion also suggests that sediment transport and deposition influences the distribution of SOC. A model developed for the site suggests that simple linear relationships between vegetation, climate and sediment transport could improve SOC predictions.