ABSTRACT
Identification of hot spots of land degradation is strongly related with the selection of soil tracers for sediment pathways. This research proposes the complementary and integrated application of two analytical techniques to select the most suitable fingerprint tracers for identifying the main sources of sediments in an agricultural catchment located in Central Argentina with erosive loess soils. Diffuse reflectance Fourier transformed in the mid-infrared range (DRIFT-MIR) spectroscopy and energy-dispersive X-ray fluorescence (EDXRF) were used for a suitable fingerprint selection. For using DRIFT-MIR spectroscopy as fingerprinting technique, calibration through quantitative parameters is needed to link and correlate DRIFT-MIR spectra with soil tracers. EDXRF was used in this context for determining the concentrations of geochemical elements in soil samples. The selected tracers were confirmed using two artificial mixtures composed of known proportions of soil collected in different sites with distinctive soil uses. These fingerprint elements were used as parameters to build a predictive model with the whole set of DRIFT-MIR spectra. Fingerprint elements such as phosphorus, iron, calcium, barium, and titanium were identified for obtaining a suitable reconstruction of the source proportions in the artificial mixtures. Mid-infrared spectra produced successful prediction models (R2 = 0.91) for Fe content and moderate useful prediction (R2 = 0.72) for Ti content. For Ca, P, and Ba, the R2 were 0.44, 0.58, and 0.59 respectively.
