High-resolution diffuse reflectance spectra in the visible and near-infrared wavelengths were used to predict chemical properties of sediment samples obtained from Lake Okeechobee (FL, USA). Chemometric models yielded highly effective prediction (relative percent difference (RPD) = SD/RMSE >2) for some sediment properties including total magnesium (Mg), total calcium (Ca), total nitrogen (TN), total carbon (TC), and organic matter content (loss on ignition (LOI)). Predictions for iron (Fe), aluminum (Al), and various forms of phosphorus (total P (TP), HCl-extractable P (HCl-P), and KCl-extractable P (KCl-P)) were also sufficiently accurate (RPD > 1.5) to be considered useful; predictions for other P fractions as well as all pore water properties were poor. Notably, scanning wet sediments resulted in only a 7 % decline in RPD scores. Moreover, interpolation maps based on values predicted from wet sediment spectra captured the same spatial patterns for Ca, Mg, TC, TN, and TP as maps derived directly from wet chemistry, suggesting that field scanning of perpetually saturated sediments may be a viable option for expediting sample analysis and greatly reducing mapping costs. Indeed, the accuracy of spectral model predictions compared favorably with the accuracy of kriging model predictions derived from wet chemistry observations suggesting that, for some analytes, higher density spatial sampling enabled by use of field spectroscopy could increase the geographic accuracy of monitoring for changes in lake sediment chemical properties.
Keywords: Chemometrics; Mapping; Okeechobee; Sediment; VNIR spectroscopy.