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Sediment fingerprinting is used to identify catchment sediment sources. Traditionally, it has been based on the collection and analysis of potential soil sources and target sediment. Differences between soil source properties (i.e., fingerprints) are then used to discriminate between sources, allowing the quantification of the relative source contributions to the target sediment. The traditional approach generally requires substantial resources for sampling and fingerprint analysis, when using conventional laboratory procedures. In pursuit of reducing the resources required, several new fingerprints have been tested and applied. However, despite the lower resource demands for analysis, most recently proposed fingerprints still require resource intensive sampling and laboratory analysis. Against this background, this study describes the use of UV-VIS absorbance spectra for sediment fingerprinting, which can be directly measured by submersible spectrophotometers on water samples in a rapid and non-destructive manner. To test the use of absorbance to estimate spatial source contributions to the target suspended sediment (SS), water samples were collected from a series of confluences during three sampling campaigns in which a confluence-based approach to source fingerprinting was undertaken. Water samples were measured in the laboratory and, after compensation for absorbance influenced by dissolved components and SS concentration, absorbance readings were used in combination with the MixSIAR Bayesian mixing model to quantify spatial source contributions. The contributions were compared with the sediment budget, to evaluate the potential use of absorbance for sediment fingerprinting at catchment scale. Overall deviations between the spatial source contributions using source fingerprinting and sediment budgeting were 18 % for all confluences (n = 11), for all events (n = 3). However, some confluences showed much higher deviations (up to 52 %), indicating the need for careful evaluation of the results using the spectrophotometer probe. Overall, this study shows the potential of using absorbance, directly obtained from grab water samples, for sediment fingerprinting in natural environments.
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Purpose: Identifying best practices for sediment fingerprinting or tracing is important to allow the quantification of sediment contributions from catchment sources. Although sediment fingerprinting has been applied with reasonable success, the deployment of this method remains associated with many issues and limitations. Methods: Seminars and debates were organised during a 4-day Thematic School in October 2021 to come up with concrete suggestions to improve the design and implementation of tracing methods. Results: First, we suggest a better use of geomorphological information to improve study design. Researchers are invited to scrutinise all the knowledge available on the catchment of interest, and to obtain multiple lines of evidence regarding sediment source contributions. Second, we think that scientific knowledge could be improved with local knowledge and we propose a scale of participation describing different levels of involvement of locals in research. Third, we recommend the use of state-of-the-art sediment tracing protocols to conduct sampling, deal with particle size, and examine data before modelling and accounting for the hydro-meteorological context under investigation. Fourth, we promote best practices in modelling, including the importance of running multiple models, selecting appropriate tracers, and reporting on model errors and uncertainty. Fifth, we suggest best practices to share tracing data and samples, which will increase the visibility of the fingerprinting technique in geoscience. Sixth, we suggest that a better formulation of hypotheses could improve our knowledge about erosion and sediment transport processes in a more unified way. Conclusion: With the suggested improvements, sediment fingerprinting, which is interdisciplinary in nature, could play a major role to meet the current and future challenges associated with global change. Supplementary information: The online version contains supplementary material available at 10.1007/s11368-022-03203-1.
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Soil erosion and sediment transport are controlled by complex factors promoting variable responses in catchment's erosion rates and sediment yields. To mitigate eventual negative effects derived from altered fluxes, integrated catchment management plans should assess the sediment cascade from upstream erosive processes, sediment mobilization through hillslopes and within the channel, up to downstream sediment yields. This study links hydro-sedimentary dynamics with sediment fingerprinting source ascription in a mid-mountainous Mediterranean catchment during five hydrological years (2013-2018). Soil colour parameters and fallout radionuclides were used as tracers to predict dominant suspended sediment sources using (i) a Bayesian mixing model (MixSIAR) and (ii) an End Member Mixing Analysis (EMMA). MixSIAR suggested that crops were the dominant source in most of the collected samples. EMMA showed similar results, clustering all except one sediment samples close to the crop and channel bank signatures. In addition, a quantitative hysteresis index was calculated and floods were clustered in function of their hydro-sedimentary characteristics. Despite different patterns were associated to each of the four identified clusters (e.g. different sediment loads and maximum suspended sediment concentrations), correlation between sediment origin and hydro-sedimentary variables was not significant due to the little seasonal variation in source type ascription.
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Sedimentos Geológicos , Solo , Teorema de Bayes , Monitoramento Ambiental , Inundações , RadioisótoposRESUMO
PURPOSE: This review of sediment source fingerprinting assesses the current state-of-the-art, remaining challenges and emerging themes. It combines inputs from international scientists either with track records in the approach or with expertise relevant to progressing the science. METHODS: Web of Science and Google Scholar were used to review published papers spanning the period 2013-2019, inclusive, to confirm publication trends in quantities of papers by study area country and the types of tracers used. The most recent (2018-2019, inclusive) papers were also benchmarked using a methodological decision-tree published in 2017. SCOPE: Areas requiring further research and international consensus on methodological detail are reviewed, and these comprise spatial variability in tracers and corresponding sampling implications for end-members, temporal variability in tracers and sampling implications for end-members and target sediment, tracer conservation and knowledge-based pre-selection, the physico-chemical basis for source discrimination and dissemination of fingerprinting results to stakeholders. Emerging themes are also discussed: novel tracers, concentration-dependence for biomarkers, combining sediment fingerprinting and age-dating, applications to sediment-bound pollutants, incorporation of supportive spatial information to augment discrimination and modelling, aeolian sediment source fingerprinting, integration with process-based models and development of open-access software tools for data processing. CONCLUSIONS: The popularity of sediment source fingerprinting continues on an upward trend globally, but with this growth comes issues surrounding lack of standardisation and procedural diversity. Nonetheless, the last 2 years have also evidenced growing uptake of critical requirements for robust applications and this review is intended to signpost investigators, both old and new, towards these benchmarks and remaining research challenges for, and emerging options for different applications of, the fingerprinting approach.
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The use of sediment color as a fingerprint property to determine sediment sources is an emerging technique that can provide a rapid and inexpensive means of investigating sediment sources. The present study aims to test the feasibility of color fingerprint properties to apportion sediment sources within the South Tobacco Creek Watershed (74 km) in Manitoba, Canada. Suspended sediment from 2009 to 2011 at six monitoring stations and potential source samples along the main stem of the creek were collected. Reflectance spectra of sediments and source materials were quantified using a diffuse reflectance spectrometry, and 16 color coefficients were derived from several color space models. Canonical discriminant analysis was used to reclassify and downsize sediment source groups. After the linear additive test and stepwise discriminant function analysis, four color coefficients were chosen to fit the Stable Isotope Analysis in R model. Consistent with the conventional fingerprinting approach, the color fingerprint results demonstrated a switch in the dominant sediment source between the headwaters and the outlet of the watershed, with the main sources being topsoil in the upper reaches, whereas outcrop shale and stream bank materials dominated in the lower reaches. The color fingerprinting approach can be integrated with conventional fingerprints (e.g., geochemical and fallout radionuclide properties) to improve source discrimination, which is a key component for source ascription modeling. We concluded that the use of color fingerprints is a promising, cost-effective technique for sediment source fingerprinting.
