Geochemical characterization of surface sediments from the Ridracoli reservoir area and surroundings, Italy. Details on bulk composition and grain size

Sediment characterization of Ridracoli reservoir, an artificial lake for water supply, and surroundings of the Fiumi Uniti catchment in the northern Apennines, Emilia-Romagna, Italy, is carried out to evaluate the overall status of the drainage basin encompassing the reservoir. The study area combines the reservoir catchment that is part of the Foreste Casentinesi-Monte Falterona-Campigna National Park, formed by the construction of a dam operating since 1982 for drinking water storage and electricity production, and the upstream side of Fiumi Uniti catchment that flows into the Adriatic Sea, including also nearby sub-catchments of Ridracoli reservoir, named Corniolo and Pietrapazza. We collected surface sediments within the area of the reservoir and riverbed sediments of surroundings catchments, analyzed grain size distribution and the chemical composition, including carbon and nitrogen. This work investigates the chemistry and distribution of elements within the study area, evaluates the dam's effect upstream and downstream, and studies the processes that happen in rivers and the reservoir. The bulk composition is mainly represented by SiO2, Al2O3, CaO, with high Corg content reflecting the Marnoso Arenacea Formation geology of the area. Statistical data analysis on the available parameters suggests the presence of two main types of sediment, namely clayey and carbonate-dominated sediments. On the reservoir area, the relationship between elements and clay matrix and organic matter, besides iron, points to a potential grain size influence, degradation of organic matter, and mineralization processes. The grain size analysis shows that silty and clayey sediments are in the bottom of the reservoir, and sand, is apparent in sediment samples from the tributaries, due to sorting effects and likely directly explained by metals concentrations. This reasoned investigation included further samples from the literature to consider the entire surrounding area and was supported by Principal Component Analysis and Cluster Analysis.