The Ridracoli artificial basin is the main water reservoir of the Emilia-Romagna region (Northeast Italy). The reservoir was made by construction of a dam on the Bidente River in 1982. It is used as the main drinking water supply of the region and for hydropower production. The physical and chemical parameterseters (temperature, pH, electrical conductivity, and dissolved oxygen) of shallow water are continuously monitored whereas vertical depth profiles of water chemical data (major anions and cations, as well as heavy metals) are available on a bimonthly base. The dataset used in this research is related to the years 2015 and 2016. Data show that the reservoir is affected by an alternation of water stratification and mixing processes due to seasonal change in water temperature, density, and the reservoir water level. In late summer and winter months, the water column is stratified with anoxic conditions at the bottom. During the spring, on the other hand, when storage is at its maximum, water recirculation and mixing occur. The reservoir is characterized by a dynamic system in which precipitation, dissolution, and adsorption processes at the bottom affect water quality along the reservoir depth column. The temperature stratification and anoxic conditions at the reservoir bottom influence the concentration and mobility of some heavy metals (i.e., Fe and Mn) and, consequently, the quality of water that reaches the treatment and purification plant. This study is relevant for water resource management of the reservoir. Assessing the seasonal changes in water quality along the reservoir water column depth is fundamental to plan water treatment operations and optimize their costs. The reservoir assessment allows one to identify countermeasures to avoid or overcome the high concentrations of heavy metals and the stratification problem (i.e., artificial mixing of the water column, new water intakes at different depths operating at different times of the year, blowers, etc.).

The Adriatic Observatory Network has revealed new aspects of dense water spreading in the eastern Mediterranean Sea. By integrating multiple observing infrastructures and producing FAIR (Findable, Accessible, Interoperable, and Reusable) data, the network has uncovered previously unexplored features, highlighting their influence on thermohaline circulation and biogeochemical fluxes in the Mediterranean Sea, a key hot spot of climate change and biodiversity. In 2016–2017, the central Mediterranean experienced significant heat loss, reduced freshwater input, and a cyclonic phase of the Northern Ionian Gyre, which drove salty water into the Adriatic. These conditions facilitated dense water formation in the northern and southern Adriatic by shelf and open‐ocean convection. The dense water formed in the north flows southward along the western continental slope, in part cascading into the southern Adriatic Pit, where it mixes with resident waters to form the Adriatic deep water, which then spreads into the Ionian Sea. Our findings revealed that the dense water exiting the Adriatic follows two distinct pathways in the Ionian: a westward branch toward the Gulf of Taranto, which contributed to the reversal of the Northern Ionian Gyre, and a southward branch toward the Kerkyra‐Kefalonia Valley, spreading directly into the deep Hellenic Trench, ventilating its deep layers due to its high density and thus playing a key role in the renewal of the basin.

The impact of heavy metal pollution and elements accumulation on reservoirs is a matter of concern worldwide. In previous studies, we assessed the chemical compositions and seasonal changes in the water body and characterized the sediments from Ridracoli catchment and surrounding areas. The Ridracoli reservoir, an artificial basin for freshwater storage on the northern Apennines in Italy, is studied to highlight its importance as a drinkable water resource and for monitoring and maintaining its quality. In general, sediments composition was found to be consistent with a mixture of carbonate and clay, in agreement with the background composition. Aqua regia digestion data (AR) was studied along with the sequential extraction procedure data (SEP) on selected samples to evaluate the mobility of elements, in particular potentially harmful elements (PHEs). Therefore, this work highlights the importance of combining total and pseudo-total concentrations with SEP data in order to understand the partition and stability of elements in the different phases to which they are linked.The aims of this work are: I) to study relationships among elements by applying statistical methods; II) to compare with local sediments, literature data and limits proposed by the Italian legislation; III) to evaluate the extractability degree concerning the total and pseudo-total contents and understand stability and element mobility between solid and liquid phases inside the reservoir; and IV) to highlight the behaviour of potentially harmful elements (PHEs) in different exchangeable, reducible, oxidizable and residual fractions from sequential extractions.

Sediment samples were collected in 2019 from Fiumi Uniti catchment in Italy in an area between the Romagna Apennines and the Adriatic Sea. The sampling phase included the collection of sediments from the Ridracoli reservoir, a large artificial basin located at 480 m a.s.l. made by construction of a dam on the Bidente river and used as the main drinking water supply of the region and for hydropower production, as well as river sediments within the whole catchment that includes the dam (Bidente, Ronco and Fiumi Uniti rivers and tributaries) and marine sediments from the Adriatic sea. In addition, we collected in the reservoir area rock and soil samples to define the element behaviour during weathering and transport.Here we report data on chemical concentrations from different matrices within the area of Ridracoli reservoir as well as chemical characterization of sediments downstream the dam along the rivers. The chemical analyses were carried out at the State Key Laboratory of Marine Geology in Shanghai, where samples underwent a two-step digestion to assess the mobile and residual fraction using a first leaching step with 1N HCl and a second one with pure HNO3 and HF, respectively.The chemical differences between rock, soils and sediments inside the reservoir showed a system of element mobility that can be compared to the geochemistry of surrounding sediments to assess pathways of geochemical cycles of elements. The ratio between concentrations of different matrices shows an enrichment in soils compared to rock for some elements (>1.3; Li, V, Cr, Mn, Sr, Cd, U) and slightly depletion in lake sediments compared to rocks (0.8-0.9). The REE ratio between lake sediments and other matrices (i.e., rocks, soils, and stream sediments) equals to 0.7-0.8, while for other trace elements (Li, V, Mn, Fe, Ni) is 1.1-1.2 showing an opposite behaviour.More mobile elements assessed using the ratio between the first step of leaching and the total composition, are Mn (0.7 of extractability) and Sr (0.8) followed by Co, Cu, Se Cd and Pb (around 0.3-0.4). The more stable elements (higher in the residual) are Ti, Rb, Zr, Cs (max 0.015). Cu and Pb seems to be more mobile in sediments than rock and soil, whereas the mobility of other analytes doesn’t seem to be affected by the different matrices. REE are quite mobile showing good extractability for Eu, Gd, Tb, Dy. Spider diagrams of REE were normalized to PAAS (Post Archean Australian Shale) and show similar shapes with Gd peaks. A difference can be seen between rocks (values around 0.8 and 1.2) and sediments, with the latter showing higher values (1.2 and 1.4).The importance of this study relies on the implications that human activities have on river systems thanks to sediment quality and on the functioning of the river-sea system in Romagna and specifically in Ridracoli reservoir catchment.

Understanding the dynamics of coastal marine ecosystems is fundamental for assessing environmental health and addressing anthropogenic impacts. This study analyzes a decade-long dataset of high-resolution Chlorophyll fluorescence (ChlF) measurements collected hourly from August 2012 to December 2022 at the E1 meteo-oceanographic buoy (Böhm et al. 2016). The buoy is located in the Northern Adriatic Sea (44° 08.58’ N; 12° 34.20’ E), approximately 100 km south of the Po River delta and 7 km northeast of Rimini, Italy. As part of the “Delta del Po and Costa Romagnola” (Bergami and Riminucci 2025) research site within the Italian LTER network and the PNRR ITINERIS project, the E1 station provides a unique platform for multidisciplinary research and long-term environmental monitoring. ChlF data, collected by the WET Labs^® ECO Triplet (now SeaBird Scientific), reveal significant seasonal and interannual variations in chlorophyll concentration, estimates from in situ ChlF, ranging from below detection limits to a maximum daily average of 41 μg/L. Together with ChlF, other meteorological, chemical, and physical parameters such as temperature (TEMP), dissolved oxygen (DO), salinity (SAL), turbidity (TURB), and wind speed (WS) were incorporated for this study (Riminucci et al. 2024, Riminucci et al. 2025). A total of 40 distinct algal bloom events were identified using ChlF concentration thresholds and growth rate dynamics (Trombetta et al. 2019). The analysis of bloom frequency revealed two main periods of bloom events per year (Fig. 1), with the identified blooms lasting an average of 13±10 days. During these events, ChlF concentration increased to an average of 6.5 μg/L, indicating substantial algal growth, compared to a baseline of 2.8 μg/L observed outside bloom periods. The most intense blooms occurred in spring, driven by nutrient inputs and increased sunlight, while summer blooms were weaker, less frequent, and shorter in duration due to thermal stratification. In contrast, autumn and winter saw a resurgence of bloom activity, influenced by freshwater inflow, nutrient resuspension, and strong mixing. These seasonal patterns underscore the dynamic interplay between temperature, wind, and nutrient availability in shaping phytoplankton dynamics. Principal Component Analysis (PCA) was conducted to identify key relationships among environmental variables and their influence on algal blooms (Fig. 2). The strong correlation between ChlF and DO during bloom periods reflects the role of photosynthesis in elevating oxygen levels. TEMP and SAL are linked due to seasonal stratification, while WS and TURB highlight wind-driven physical disturbances, such as sediment resuspension and waves. Overall, PCA captures both seasonal and biological processes, including bloom dynamics, as well as physical disturbances driven by wind and water movement. Seasonal factors govern bloom dynamics, with spring and late autumn/winter supporting phytoplankton growth due to favourable nutrient availability and stable conditions, while summer stratification limits blooms. These findings underscore the interplay of biological and physical drivers in shaping the ecosystem response over the decade. Two bloom types were identified: Single-Peak Blooms, typical in spring, characterized by rapid growth and short durations, and Multi-Peak Blooms, more common in autumn, with extended periods due to intermittent nutrient apportion. Nutrient-rich freshwater inputs from the Po River, nitrogen and phosphorus, and seasonal cycles of phytoplankton play a significant role in driving these blooms. Diatoms such as Skeletonema marinoi dominate the winter bloom, while spring and autumn blooms are diatom-driven, modulated by rainfall and nutrient runoff (Grilli et al. 2020, Totti et al. 2019). Summer, characterized by water column stratification, generally exhibits lower ChlF concentrations unless disturbed by storms or mixing events that reintroduce nutrients into surface waters. These findings emphasize the complex seasonal and environmental drivers shaping bloom dynamics. This study introduces a methodological framework for detecting coastal algal blooms by analyzing patterns derived from in-situ fluorescence measurements, offering insights into bloom dynamics. While challenges such as data gaps due to sensor maintenance and biofouling, the findings underscore the value of long-term, high-frequency observations in understanding environmental processes and managing coastal ecosystems. Future research should focus on integrating complementary datasets, such as nutrient concentrations or satellite observations, to deepen the understanding of bloom drivers. Additionally, expanding datasets temporally, by including more years, and spatially, by incorporating other monitoring systems (e.g., fixed-point stations), will further enhance the robustness and applicability of the framework.