Linking spatial patterns of soil organic carbon to topography - A case study from south-eastern Spain
|AGRICULTURAL SOIL; CHEMICAL-PROPERTIES; DIFFUSE-REFLECTANCE SPECTROSCOPY; Digital terrain analysis; EROSION; FIELD; Geography, Physical; Geology; Geosciences, Multidisciplinary; Hyperspectral remote sensing; LAND ABANDONMENT; Physical Geography; RUNOFF GENERATION; Semi-arid regions; SEMIARID ENVIRONMENT; Soil organic carbon; Spatial prediction; Terrain classification; VEGETATION; WATER-BALANCE
A key uncertainty in our understanding of the global carbon cycle is the lateral movement of carbon through the terrestrial system. Soils are the major storage of carbon in the terrestrial biosphere and the inventory of soil organic carbon (SOC) is required for greenhouse gas inventories and carbon mitigation projects. The aim of this study is to characterize spatial patterns of the concentrations of topsoil total organic carbon (TOC) in a semi-arid Mediterranean area in south-eastern Spain and to assess their relationship to topography. We adopt a remote sensing based approach for the spectral determination and quantification of TOC with a complete coverage of bare soil surfaces. Digital terrain analysis and geostatistical techniques are applied to analyze the spatial patterns of TOC at different spatial scales. We show that accumulation of topsoil SOC is dependent on topographic position at the landscape scale with highest values found in valley bottoms. At the hill-slope scale, differences among terrain classes exist regarding the topographic controls on SOC. While positive correlation between the topographic wetness index (TWI) and TOC can be observed on steep slopes, that correlation is not significant on wide pediments. Small scale spatial variability is large on ridges, steep slopes and valley bottoms, while SOC distribution on pediments is relatively homogeneous. These differences are most likely governed by the presence of vegetation patches and variable runoff and sediment transport rates among the terrain classes. The successful application of hyperspectral remote sensing for the spatial estimation of SOC concentrations suggests that it is a promising technique to advance SOC inventories in semi-arid and arid regions. (C) 2010 Elsevier B.V. All rights reserved.
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checked on Feb 26, 2024