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. Tracing the origin of sediment is needed to improve our knowledge ofhydro-sedimentary dynamics at the catchment scale. Several fingerprintingapproaches have been developed to provide this crucial information. Inparticular, spectroscopy provides a rapid, inexpensive and non-destructivealternative technique to the conventional analysis of the geochemicalproperties. Here, we investigated the performance of four multi-proxyapproaches based on (1) colour parameters, (2) geochemical properties, (3) colour parameters coupled with geochemical properties and (4) the entirevisible spectrum to discriminate sediment source contributions in a miningcatchment of New Caledonia. This French archipelago located in thesouth-west Pacific Ocean is the world's sixth largest producer of nickel.Open-cast nickel mining increases soil degradation and the downstreamtransfer of sediments in river systems, leading to the river systemsiltation. The sediment sources considered in the current research weretherefore sediment eroded from mining sub-catchments and non-miningsub-catchments. To this end, sediment deposited during two cyclonic events(i.e. 2015 and 2017) was collected following a tributary design approach inone of the first areas exploited for nickel mining on the archipelago, theThio River catchment (397 km2). Source (n=24) and riversediment (n=19) samples were analysed by X-ray fluorescence andspectroscopy in the visible spectra (i.e. 365–735 nm). The resultsdemonstrated that the individual sediment tracing methods based onspectroscopy measurements (i.e. (1) and (4)) were not able to discriminatesources. In contrast, the geochemical approach (2) did discriminatesources, with 83.1 % of variance in sources explained. However, it is theinclusion of colour properties in addition to geochemical parameters (3) which provides the strongest discrimination between sources, with 92.6 %of source variance explained. For each of these approaches ((2) and (3)), theassociated fingerprinting properties were used in an optimized mixing model.The predictive performance of the models was validated through tests withartificial mixture samples, i.e. where the proportions of the sources wereknown beforehand. Although with a slightly lower discrimination potential,the “geochemistry” model (2) provided similar predictions of sedimentcontributions to those obtained with the coupled “colour + geochemistry”model (3). Indeed, the geochemistry model (2) showed that mining tributarycontributions dominated the sediments inputs, with a mean contribution of 68 ± 25 % for the 2015 flood event, whereas the colour + geochemistry model (3) estimated that the mining tributaries contributed 65 ± 27 %. In a similar way, the contributions of mining tributarieswere evaluated to 83 ± 8 % by the geochemistry model (2) versus88 ± 8 % by the colour + geochemistry model (3) for the 2017flood event. Therefore, the use of these approaches based on geochemicalproperties only (2) or of those coupled to colour parameters (3) was shown toimprove source discrimination and to reduce uncertainties associated withsediment source apportionment. These techniques could be extended to othermining catchments of New Caledonia but also to other similar nickel miningareas around the world.

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Combining colour parameters and geochemical tracers to improve sediment source discrimination in a mining catchment (New Caledonia, South Pacific Islands)