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Purpose: Fine sediment deposition is an important component of the catchment sediment budget and affects river morphology, biology, and contaminant transfer. However, the driving factors of fine sediment deposition remain poorly understood at the catchment scale, limiting our ability to model this process. Methods: Fine sediment deposition and river reach characteristics were collected over the entire river network of three medium-sized (200–2200 km2) temperate catchments, corresponding to 11,302 river reaches. This unique database was analyzed and used to develop and evaluate a random forest model. The model was used to predict sediment deposition and analyze its driving factors. Results: Fine sediment deposition displayed a high spatial variability and a weak but significant relationship with the Strahler order and river reach width (Pearson coefficient r = −0.4 and 0.4, respectively), indicating the likely nonlinear influence of river reach characteristics. The random forest model predicted fine sediment deposition intensity with an accuracy of 81%, depending on the availability of training data. Bed substrate granularity, flow condition, reach depth and width, and the proportion of cropland and forest were the six most influential variables on fine sediment deposition intensity, suggesting the importance of both hillslope and within-river channel processes in controlling fine sediment deposition. Conclusion: This study presented and analyzed a unique dataset. It also demonstrated the potential of random forest approaches to predict fine sediment deposition at the catchment scale. The proposed approach is complementary to measurements and process-based models. It may be useful for improving the understanding of sediment connectivity in catchments, the design of future measurement campaigns, and help prioritize areas to implement mitigation strategies. [ABSTRACT FROM AUTHOR]

The Fukushima nuclear accident inMarch 2011 generated a 3000 km² plume of soils heavily contaminated with 137Cs. Decontamination was completed early in 2019. Typhoon Hagibis was the first extreme event that occurred in the region after decontamination. Its impact on sediment sources and sediment 137Cs contamination was investigated through the application of a sediment fingerprinting procedure using spectrocolorimetry and geochemical properties. Sediment deposits (n = 24) were collected in the Mano and Niida River catchments after the 2019 typhoons, and their signature was compared to that of potential sources (e.g., cropland, forests, and subsurface; n = 57). Results demonstrate the dominance of cropland as the main source of sediment (mean: 54%) followed by forests (41%) with much lower contributions of subsurface material (5%). Overall, 137Cs concentrations in sedimentwere on average 84%--93%lower than the levels recorded after the accident in 2011, which demonstrates the effectiveness of cropland decontamination. [ABSTRACT FROM AUTHOR]