Abstract
AbstractSediment fingerprinting has been widely used to distinguish discrete sediment sources; however, application to intra‐storm sediment source variability has received relatively little focus despite the benefit being long recognized. In this investigation, sediment fingerprinting was applied to a 53‐hr storm event sampled hourly to determine sediment source dynamics throughout the event. Sediment sources were differentiated using 16 variables, and source contribution determined using Bayesian and Frequentist mixing models for comparison. Both models provided comparable source predictions for the dominant source estimates and the general temporal pattern. The Frequentist model appeared to exhibit some unreliable values coinciding with low GOF and attributed to inherent model structure. The Bayesian model showed higher uncertainty, likely due to the “process error” utilized associated with single sample mixtures. High variability in sediment source contribution was observed between hourly time steps; however, local smoothing reveals temporal trends during the event. A higher average proportion of mudstone is found in the falling limb (0.544) compared with the rising limb (0.464), and the reverse is observed for mountain range (0.218 vs. 0.283) and unconsolidated (0.073 vs. 0.055). In the initial hours of the storm, mudstone source contribution significantly drops, whereas mountain range and unconsolidated contributions peak. The SSC‐Q clockwise hysteresis indicates proximal sediment sources, suggesting the mudstone sediment is stored channel sediment and easily entrained. This sediment flushes through, coinciding with a drop as the distal mountain range and unconsolidated sources arrive to peak contribution. The wider Manawatū discharge and sediment load then arrive, delivering increasing levels of mudstone throughout the remainder of the event while mountain range sediment diminishes. Spatial representation of the sediment source contribution was derived from distributing sediment source loads to the spatial extent of the source material according to sub‐catchment sediment loads and was weighted according to slope. This provided an effective means to visualize the origin of the sediment and a better spatial interpretation of sediment fingerprinting results, which is typically limited by poor spatial resolution.
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