Sediment grain size and its spatial distribution is a very important aspect for many applications and processes that occur in the coastal zone. One of these is coastal erosion which is strongly dependent on sediment distribution and transportation. To highlight this fact, surficial coastal sediments were collected from a densely populated coastal zone in Western Greece, which suffers extensive erosion, and grain size distribution was thoroughly analysed, to predict the spatial distribution of the median grain size diameter (D₅₀) and produce sediment distribution maps. Four different geostatistical interpolation techniques (Ordinary Kriging, Simple Kriging, Empirical Bayesian Kriging and Universal Kriging) and three deterministic (Radial Basis Function, Local Polynomial Interpolation, and Inverse Distance Weighting) were employed for the construction of the respective surficial sediment distribution maps with the use of GIS. Moreover, a comparative study between the deterministic and geostatistical approaches was applied and the performance of each interpolation method was evaluated using cross-validation and estimating the Pearson Corellation and the coefficient of determination (R²). The best interpolation technique for this research proved to be the Ordinary Kriging for the shoreline materials and the Empirical Bayesian Kriging (EBK) for the seabed materials since both had the lowest prediction errors and the highest R².

This study focuses on the role of topography in soil erosion modelling by examining the impact of topographic data from various sources on the calculation of the slope length and slope steepness factor (LS). For this purpose, the Pinios dam drainage basin in the Ilia Regional Unit, Western Greece, was selected as a pilot area of this study. Specifically, six Digital Elevation Models (DEM) from four different sources with various resolutions (5, 30, and 90 m) were compared with ground control point (GCP) values to assess their relative vertical accuracy. These DEM were acquired for the calculation of the LS factor by using two different equations. Then the calculated LS factors were implemented in the RUSLE model for the estimation of soil loss. The current study includes a comparative analysis of the elevation, the slopes, the LS factor, and the soil loss. The results showed that the 5 m resolution DEM had the best vertical accuracy, and thus it is considered to be the most suitable DEM for soil erosion modelling. Moreover, the comparison of the DEM elevation values showed high similarity, in contrast to the slope values. In addition, the comparative assessment of the LS and soil loss values calculated from each DEM with the two LS equations revealed a great divergence. It is noticeable that both LS and soil loss results presented higher values for slopes greater than 20°. It is concluded that the comparison of the LS values calculated with the two examined approaches and the use of different DEM with various resolutions and different sources does not change consistently with the increase of DEM grid size and accuracy. Thus, it is very significant in soil erosion modelling to use an LS equation that imports thresholds in its formula to avoid overestimation in soil loss calculations.

In recent decades, wildfires have become a serious threat worldwide, producing disasters in the natural and anthropogenic environment as well as serious economic losses. One of wildfire’s major impacts is soil erosion, as it may cause major problems in both the physical and anthropogenic environment and seriously affect the landscape. This study investigates the soil erosion rate changes in areas affected by wildfires and uses, as a pilot area, the drainage basin of the Pinios earth-filled dam located in the Ilia Regional Unit, western Greece, which has suffered serious erosion changes after a wildfire event. For this purpose, the Revised Universal Soil Loss Equation (RUSLE) is applied in GIS software, and the soil erosion rate changes in the selected investigation area are estimated at different time intervals. Specifically, soil erosion rate changes are calculated by importing the factors from the RUSLE equation in the GIS software and uses as a dependent variable the cover management factor C, which is strongly influenced by large destructive fires. The models that are produced are compared with each other by collating average annual soil erosion maps and rates before the fire, immediately after the fire and for the existing conditions occurring in the pilot area.

On the outskirts of the Pinios dam reservoir (Ilia Regional Unit, Greece), a water treatment plant serves the water supply needs of the surrounding municipalities, in which high concentrations of Fe and Mn, before treatment, have been observed. The main purpose of this research was to investigate the mechanism of increased iron (Fe) and manganese (Mn) levels in the reservoir of the Pinios dam, which impacts its water treatment plant operation. A wide range of hydrochemical and sedimentological analyses were conducted over a hydrological year, focusing on the spatial and temporal distribution of Fe and Mn in both water and sediment samples across the established research monitoring stations. Sediment samples from the reservoir’s bottom revealed predominantly fine-grained material, rich in total organic carbon, with elevated Mn and Fe oxide levels. Significant seasonal variations in Fe and Mn levels were also discovered, with higher Mn levels observed in the anoxic bottom waters of the reservoir during the dry season, attributed to the reduced conditions favoring Mn oxide dissolution over Fe. Conversely, during the wet season, a homogenization of metal concentrations throughout the water column was observed due to increased oxygenation and freshwater inflow. These outcomes were confirmed by the hydrochemical analysis, indicating that the redox conditions, pH, and temperature, as well as the presence of organic matter, significantly influence the mobility and bioavailability of these metals in the reservoir. The findings of this study clarify that the high concentration of Fe and Mn can be linked to the mineral composition of the upstream Neogene and flysch formations in the study area. As these formations are affected by geological weathering, they tend to enrich the streams, through soil erosion and runoff processes, with metals like Fe and Mn, which are eventually transported into the dam reservoir. This study highlights the critical influence of lithological, sedimentological, and hydrological factors on the redox conditions and seasonal stratification that govern the behavior of Fe and Mn concentrations and mobility in dam reservoirs. These findings are critical for informing water resource management practices and dam infrastructure operators and developing effective environmental conservation strategies in similar cases.

Climate change and extreme events such as droughts, heavy rainfall and flooding can influence the water column stratification in reservoir dams, decrease storage capacity, increase sediment and pollutant loads and, as a result, affect water quality. The seasonal variation in the water column stratification of reservoirs is an important parameter for the study of dam life cycle as well as water management and use. In the present study a detailed bathymetric survey was carried out, and a digital elevation model (DEM) of the reservoir was constructed. Seasonal physicochemical monitoring data such as temperature, dissolved oxygen, pH and conductivity are presented. The seasonal thermal stratification was recorded, resulting in an isolated hypolimnion where anoxic layers formed below 17 m in summer and autumn. Manganese and iron concentrations exhibited values higher than 150 mg/L in the anoxic hypolimnion during summer and autumn, indicating solubilization from the sediment. The observed seasonal and depth-dependent variations in physicochemical parameters underline the reservoir’s susceptibility to eutrophication and metal mobilization, particularly during stratified periods. These findings are critical for designing management strategies to mitigate potential water quality issues.

The integration of new technologies across scientific disciplines, including rock slope engineering, is increasingly essential. The use of drones and advanced software tools for mapping and analyzing large rocky slopes in detail has become indispensable and highly beneficial. In this context, this paper examines the process and key parameters involved in generating a high-resolution 3D terrain model and evaluating rock-mass stability using advanced software tools (UgCS version 5.5.0, ArcGIS version 3.4.3, Drone2Map version 2024.2.1, DSE version 3.02, and Rocfall3D version 1.014). These technologies facilitate the identification of hazard zones on rocky slopes in monuments of archaeological interest. The evaluation of this modeling approach is conducted at the monolithic rock of Ancient Corinth (Acrocorinth), one of Greece’s most significant archaeological sites. This study focuses on assessing its vulnerability to rockfalls and identifying hazard zones. This methodology involves the development of a 3D rockfall analysis system and the implementation of a specialized hazard matrix for the quantitative assessment of rockfall risk. This approach enables the development of a decisive model for mitigating rockfall hazards, ensuring the safety of visitors in high-traffic areas such as major archaeological sites.