Storm Daniel initiated on 3 September 2023, over the Northeastern Aegean Sea, causing extreme rainfall levels for the following four days, reaching an average of about 360 mm over the Peneus basin, in Thessaly, Central Greece. This event led to extensive floods, with 17 human lives lost and devastating environmental and economic impacts. The automatic water-monitoring network of the HIMIOFoTS National Research Infrastructure captured the evolution of the phenomenon and the relevant hydrometeorological (rainfall, water stage, and discharge) measurements were used to analyse the event’s characteristics. The results indicate that the average rainfall’s return period was up to 150 years, the peak flow close to the river mouth reached approximately 1950 m³/s, and the outflow volume of water to the sea was 1670 hm³. The analysis of the observed hydrographs across Peneus also provided useful lessons from the flood-engineering perspective regarding key modelling assumptions and the role of upstream retentions. Therefore, extending and supporting the operation of the HIMIOFoTS infrastructure is crucial to assist responsible authorities and local communities in reducing potential damages and increasing the socioeconomic resilience to natural disasters, as well as to improve the existing knowledge with respect to extreme flood-simulation approaches.

This study investigates the potential of Sentinel-1 data in assisting flood modeling procedures. Two different synthetic aperture radar (SAR) processing methodologies, one simplified based on single-flood image thresholding and one automatic based on SAR statistical temporal analysis, were exploited to delineate the flooding caused by a storm event that took place in Spercheios River, Central Greece. The storm event was simulated by coupling a HEC-HMS hydrologic model and an integrated 1D/2D HEC-RAS hydraulic model. Both SAR methodologies were compared to each other and also used as a reference to test the sensitivity of the hydraulic model in the variation of upstream discharge and roughness coefficient. Model sensitivity was investigated with respect to the change in the derived inundation extent and three additional metrics: the Critical Success Index (CSI), the Hit Rate (HR), and the False Alarm Ratio (FAR). The model response was found to be affected in the following order: by the upstream inflow, and by the variation of the roughness coefficient in the main channel and in the land use “cultivated crops”. The discrepancies observed between model- and SAR-derived inundation products are associated with the uncertainty accompanying the SAR processing and the utilized satellite data itself, the underlying topography, and the structural uncertainty inherent in the modeling procedure. Regarding the SAR methodologies tested, the second one (FLOMPY approach) proved to be more suitable, yielding a more coherent and realistic flooded area. According to the applied metrics and considering as reference the FLOMPY result, model performance ranged between 22–27.5% (CSI), 36.9–60.4% (HR), and 62.1–68.2% (FAR).

The efficiency of constructed floating wetlands (CFWs) in their ability to remove agrochemicals (nutrients and pesticides) is here investigated in a series of pilot-scale systems. Four experimental CFWs were designed and constructed; three of them were planted with the aquatic plant species Lemna minor, Azolla pinnata and Eichhornia crassipes. The fourth did not contain any plants and was used as the control. The aim of the study was to evaluate the efficiency of CFW containing aquatic macrophytes in the reduction of pesticides and nutrients, under field conditions. The CFWs operated continuously from May 2021 to September 2021, and their removal efficiencies of nitrogen and phosphorus ions, and five commonly used pesticides were examined. The CFW systems were fed daily with agricultural wastewater which was prepared by mixing a fertilizer and predetermined doses of pesticides. The hydraulic residence time was kept at 14 days. Samples were collected on a weekly basis from both the influent and the effluent of each experimental tank, and were subsequently analyzed in the laboratory. HPLC-DAD and Ion Chromatography were implemented for sample analysis following a very simple sample preparation. Reductions for nutrient ranged from no reduction to 100% removal, whereas for pesticides these varied from no reduction to 98.8% removal, indicating that these systems can be used as efficient and low-cost pollution control technologies for agrochemical wastewater treatment. Significant reduction for certain pesticides was also observed in the algae control tank, thus, proving the efficiency of algae in organic pollution reduction, and recognizing the limitations of aquatic plant use in decontamination.

The Prespa Lakes system, shared between Greece, the Republic of North Macedonia, and Albania, forms a significant transboundary, large-scale integrated freshwater ecosystem subject to multiple anthropogenic and natural pressures. This study focuses on the Greek part of the Prespa Lakes system with particular emphasis on the identification of the ecological and hydrological impacts of the contributing stream inflows on the lakes by examining the spatial variability in physicochemical and biological conditions and conducting water balance and isotopic analyses. Based on our results, streams draining into Lesser Prespa Lake exhibited more pronounced hydrological and physicochemical fluctuations than the Agios Germanos River connected to Great Prespa Lake, while ecological status classifications of all studied streams ranged from high to moderate. Furthermore, moderate ecological status conditions (mainly observed at the downstream stations) were closely associated with adjacent anthropogenic pressures, including agricultural drainage, livestock activities, irrigated croplands, and wastewater discharges. In addition, although both lakes were classified as mesotrophic, field data indicated greater transparency loss in Lesser Prespa than in Great Prespa Lake. Regarding the stream influences on Lesser Prespa Lake’s water quality, nutrient loads induced changes in lake concentrations by roughly one month. Total nitrogen showed moderate stream–lake correlations (R = 0.61) and a strong negative correlation for total phosphorus (R = −0.94), suggesting substantial nutrient retention and processes within the lake. Water balance analysis revealed an annual water deficit for both Lesser and Great Prespa, with the latter exhibiting a markedly stronger and systematic long-term decline in water level. In the Lesser Prespa, seasonal fluctuations in water volume were primarily driven by excess rainfall, while stream inflows contributed minimally. Conversely, correlation analysis for Great Prespa identified surface inflow from the Ag. Germanos catchment as the dominant driver of water storage variability, surpassing direct rainfall, with strong correlations in both wet (R = 0.79) and dry (R = 0.88) periods. Isotopic compositions (δ¹⁸O, δ²H) did not differ significantly between the two lakes, indicating common recharge sources and strong evaporative imprints, while stream isotopic signatures highlighted spatial and seasonal variability in hydrological inputs. Seasonal and spatial variations were proved to be strongly influenced by both natural hydrological dynamics and anthropogenic pressures within the basin, while these findings reinforce the importance and the necessity of adopting holistic, cross-border management strategies that maintain the ecological integrity and the long-term sustainability of the Prespa Lakes ecosystem.