Testing the ability of submersible spectrophotometers to trace suspended sediment sources at high-temporal frequency

Reliable and detailed information on the primary sources of suspended sediment (SS) and sediment-associated nutrient and contaminant transfers is needed to target mitigation measures for delivering healthy ecosystems and meeting environmental policy objectives. To this end, the SS source fingerprinting approach is proven an effective tool for assembling reliable information on the sources of SS and SS-associated nutrients and contaminants within a catchment. However, SS source estimates at a high temporal resolution are often lacking due to the high workload and costs involved in collecting and analysing SS and soil samples using conventional means. Given this background, here, we propose the use of submersible spectrophotometers that measure absorbance spectra at 2.5 nm intervals in the 200-750 nm range (UV-VIS) in-situ and at high temporal frequency (i.e. minutes) to fingerprint SS sources. We hypothesise that increasing the measurement frequency will eventually help to better characterise changes in sources over time, whilst also giving further insights on how to improve the classical sediment fingerprinting approach, which is currently based on the use of temporally-lumped data. In this research, we first test our approach under fully controlled conditions in a laboratory experiment. To this end, we use a large cylindrical tank (40-L) equipped with a spectrophotometer as well as a LISST sensor (measuring the effective particle size distribution (PSD)). A mechanical stirring device ensures homogeneous conditions in the system and prevents the settling of soil particles (added in solution). The used soil samples originate from different areas within Luxembourg, whereby a selection was made based on differences in tracer properties and colour. The soils were sieved to three different fractions to take account of PSD control on tracer properties. Using the laboratory experiment, we investigated how suspended particle properties affect the absorbance spectra readings. In particular, we looked at the effects of: (i) increasing concentrations of suspended particles, and; (ii) differences in PSD. We then created artificial mixtures composed of two, three and four soil types mixed in different proportions to investigate if the absorbance readings at different wavelengths (i.e., considered as tracers or fingerprints) can be used to un-mix the known proportions of the SS sources. For this, we used the predictions of MixSIAR, a well-established Bayesian tracer un-mixing model. Our preliminary results indicate the promising use of high resolution absorbance data to un-mix artificial sediment mixtures. Ongoing work is testing the approach at larger scales.