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Spectrocolorimetric properties provide a quick, low-cost and non-destructive alternative to the measurement of geochemical and organic matter parameters. Their potential to discriminate between forest, cultivated and subsoil sources was tested in soils and sediment collected in coastal catchments draining the main radioactive pollution plume of Fukushima Prefecture, Japan.Fifteen spectrocolorimetric properties were determined in potential source (n=37) and sediment (n=400) samples collected during 13 campaigns from 2011–2017 in two catchments (covering a total surface area of 450 km²) draining the main radioactive pollution plume. Potential sources included topsoil from forest and cropland sources along with subsoil material originating from landslides, channel banks and the decontamination of cultivated areas. The optimum set of parameters used in the mixed linear model to calculate the sediment source contributions was obtained through the use of a range test, the Kruskal-Wallis H-test, and a linear discriminant analysis. Nine colour parameters correctly classified 100% of the source samples (forest, subsoil and cultivated sources). The results illustrate that cultivated landscapes were the main source of sediment to these river systems (mean 56%, SD 34%) followed by subsoil (mean 26%, SD 16%) and forest sources (mean 21%, SD 24%). However, these contributions strongly varied over time, with a peak of subsoil contributions (mean 57%, SD 17%) in Fall 2015, coinciding with the occurrence of a typhoon after the remediation works. These original results demonstrate that spectrocolorimetric measurements provide a powerful tool for the monitoring of the effectiveness of remediation works in this post-accidental context. [ABSTRACT FROM AUTHOR]

An important step in the sediment source fingerprinting approach is the selection of the appropriate tracing parameters to maximise source discrimination. In order to reduce uncertainties and increase discrimination between sources it may be necessary to use multiple tracing parameters. Accordingly, this study investigates the discrimination and apportionment of sediment sources in a rural agricultural catchment obtained by combining colour, magnetic, and geochemical fingerprinting approaches. The Conceição River catchment (804 km²) has predominantly deep and highly weathered Ferralsols with land-use consisting of croplands (73%), pastures (18%), forests (8%) and other uses (1%). A total of 189 samples were taken from the main sediment sources, including: Croplands (CR, n=78), pastures (P, n=24), unpaved roads (UR, n=38), gullies (G, n=15) and stream bank (SB, n=34). Sediment samples were taken from the surface bed (n=10) of the river and with time integrated samplers (n=4). Twenty-two geochemical tracers, 6 magnetic properties and 24 colour parameters were analyzed. Tracers were selected following a three step procedure, including: (i) a conservative range test (95% confident interval), (ii) a Kruskal–Wallis H test, and (iii) discriminant function analysis (DFA). The DFA was performed using four different sets of variables: (i) geochemical variables only (G); (ii) geochemical+magnetic+colour (GMC); (iii) geochemical+colour (GC); (iv) geochemical+magnetic (GM). The selected tracers were introduced into a modified version of the classical Solver-based mixing model that in order to determine the relative contribution of different sources to in-stream sediment through simultaneously minimizing mixing model difference. The G and GC DFAs both resulted 69% of samples correct classified (SCC) as no colour parameters were selected by the DFA. The GMC and GM approaches improved the discrimination, both resulting in 76% of SCC. For the G and GC approaches, the average source contribution for the 12 sediment samples were P 47%, SB 29%, CR 19%, UR 5% and G 0%. For the GMC and GM approaches, the contribution of each source was P 41%, SB 37%, CR 14%, UR 8% and G 0%. These results are counterintuitive to field observations where cropland is anticipated to contribute more sediment than pastures. Future research should use artificial mixtures to validate these results. Both magnetic and colour parameters hold potential to improve discrimination between sources, particularly magnetic parameters in catchments with high weathered soils. [ABSTRACT FROM AUTHOR]