Field-Scale Mapping of Soil Organic Carbon with Soil-Landscape Modeling

Feng Chen 1+,  Larry T. West 2, David E. Kissel ¹, Rex Clark 3, and Wayne Adkins 1 
1 Department of Crop & Soil Sciences, University of Georgia, USA
2 National Soil Survey Center, USDA-NRCS, USA
Department of Biological & Agricultural Engineering, University of Georgia, USA

Abstract. Predicting soil organic carbon (SOC) at a field scale plays an important role in field management practices for studies in both soil quality and carbon sequestration. Examining SOC concentration with soil- landscape relations provided an alternative technique for mapping SOC concentrations. The objectives of this study were to develop soil-landscape models for a crop field by quantifying the relationships between SOC concentration and terrain attributes derived from digital elevation models (DEMs), and to refine the models by delineating the sub-watersheds within the field. Separated soil sample sets were obtained from a 115 ha field located in the coastal plain region of Georgia for model development and model validation. The high accuracy GPS measurements over the field were obtained with a survey grade GPS system. The DEMs with 1, 2, 4, and 8 m grid sizes were created by interpolating the GPS data, and the terrain attributes were further derived from the DEMs. Correlation coefficients between SOC concentration and  terrain attributes were analyzed and indicated that the topographic wetness index was the best single predictor for mapping SOC concentration. The study found that prediction of SOC concentration using the DEM with 2 m grid size yielded the best accuracy in both cases. The effects  of grid sizes on the sub-watershed delineation and prediction accuracy were also discussed.

Keywords: digital elevation model, global positioning system, soil-landscape  modelling, soil organic carbon, sub-watershed.

In: Wan, Y. et al. (eds) Proceeding of the 8th international symposium on spatial accuracy assessment in natural resources and environmental sciences, World Academic Union (Press).

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