Ruo-Qian Wang, David Bazzett

Water color changes are closely linked to variations in suspended sediment characteristics, motivating efforts to reliably determine sediment concentration and size through remote sensing. However, current turbidity measurement practices that rely on empirical correlations have not been rigorously tested in the lab and the past testing was limited to limited particle conditions, leading to a wide range of accuracy and limiting its applicability in the field. The advancement of hyper-spectral imaging technology offers new possibilities for enhancing the analysis of water color-based sediment characterization. This study explores the application of hyperspectral imaging to analyze variations in particle sizes and concentrations in suspended sediment samples. Results indicate that higher concentrations result in elevated differences, with low concentrations (<2 mg/L) and specific particle sizes showing unique sensitivities. Sensitivity analysis revealed that smaller particles and lower concentrations exhibit greater responsiveness to concentration changes, particularly within the red and near-infrared (NIR) bands. Despite noise at the spectrum's extremes, focusing on red and NIR wavelengths enhances detection accuracy. This work underscores hyperspectral imaging's potential in environmental monitoring and remote sensing, advocating for targeted band utilization to improve the sensitivity and accuracy of suspended sediment characterization.