A devastating forest fire in August 2021 burned about 517 km² of the northern part of Evia Island, affecting vegetation, soil properties, sediment delivery and the hydrological response of the catchments. This study focuses on the estimation of the annual soil loss in the study area under natural (pre-fire) and post-fire conditions. The assessment of the soil loss potential was conducted with the application of the Universal Soil Loss Equation (USLE), which is an empirical equation and an efficient way to predict soil loss. The USLE factors include rainfall erosivity (R), soil erodibility (K), the slope and slope length factor (LS), the cover management factor (C) and the erosion control practice factor (P). The USLE quantified the annual soil erosion (in t/ha/year) for both pre- and post-wildfire conditions, and the study area has been classified into various soil loss categories and soil erosion intensity types. The results showed that the annual soil loss before the forest fires ranged from 0 to 1747 t/ha, with a mean value of 253 t/ha, while after the fire the soil loss significantly increased (the highest annual soil loss was estimated at 3255 t/ha and the mean value was 543 t/ha). These values demonstrate a significant post-fire change in mean annual soil loss that corresponds to an increase of 114% compared to the pre-fire natural condition. The area that is undergoing high erosion rates after the extreme wildfire event increased by approximately 7%, while the area of moderate rates increased by 2%. The calculated maximum potential of soil erosion, before and after the 2021 extreme wildfire event, has been visualized on spatial distribution maps of the average annual soil loss for the study area. The present study underlines the significant post-fire increase in soil loss as part of the identification of the more vulnerable to erosion areas that demand higher priority regarding the protective/control measures.

This study deals with the assessment and mapping of neotectonic landscape deformation in the northern part of the Evia Island (Central Greece). Multi-Criteria Decision Analysis (MCDA) utilizing Analytic Hierarchy Process (AHP) and Weighted Linear Combination (WLC) procedures were conducted for the calculation of the Neotectonic Landscape Deformation Index (NLDI). The study is based on the combination of morphotectonic, geomorphological and geological parameters. The GIS-based spatial MCDA led to the classification of the study area into five classes of neotectonic deformation (from very low to very high) and to a neotectonic deformation map. The results were compared with the outputs of a relative tectonic activity classification approach based on quantitative geomorphic analysis at a regional scale, including site-specific field observations. Areas of high and very high deformation are related to the major active faults of Dirfis, Kandili and Gregolimano–Telethrio. Other minor active normal faults of medium to high seismic risk level, affecting the northern and northeastern parts of the island, are also associated with areas of intense landscape neotectonic deformation.

The aim of this study is to evaluate the relative tectonic activity in the north part of the Evia Island, located in Central Greece, and to investigate the contribution of neotectonic processes in the development of the fluvial landscape. Five morphometric parameters, including Drainage Basin Slope (S_b), Hypsometric Integral (H_i), Asymmetry Factor (A_f), Relief Ratio (R_h), and Melton’s Ruggedness Number (M), were estimated for a total of 189 drainage basins. The catchments were classified into two groups, according to the estimated values of each morphometric parameter, and maps showing their spatial distribution were produced. The combination of the calculated morphometric parameters led to a new single integrated Index of relative tectonic activity (named Irta). Following this indexing, the basins were characterized as of low, moderate, or high relative tectonic activity. The quantitative analysis showed that the development of the present drainage systems and the geometry of the basins of the study area have been influenced by the tectonic uplift caused by the activity of two NW-SE trending offshore active normal fault systems: the north Gulf of Evia fault zone (Kandili-Telethrion) and the Aegean Sea fault zone (Dirfis), respectively. The spatial distribution of the values of the new integrated index Irta showed significant differences among the drainage basins that reflect differences in relative tectonic activity related to their location with regard to the normal fault systems of the study area.

This paper presents the results of geomorphological investigations carried out on the Lilas River fan delta in central Evia Isl., Greece. A geomorphological map has been prepared using Digital Elevation Model analysis, aerial photos and Google Earth image interpretation, a reliable map of 1846, and extensive fieldwork. The Holocene sequence stratigraphy of the fan delta has been studied based on profiles of seven deep cores drilled by the municipal authorities. Two additional shallow boreholes were drilled with a portable drilling set and collected samples were analyzed using micropaleontological and grain size analysis methods while four sediment samples were dated using optically stimulated luminescence (OSL) techniques. During the early Holocene, most of the fan delta plain was a shallow marine environment. Between 4530 ± 220 and 3600 ± 240 years BP the depositional environment at the area of Nea Lampsakos changed from shallow marine to a lower energy lagoonal one. The main distributary changed its course several times leading to the building and subsequent abandonment of five fan delta lobes, through which the fan delta advanced during the late Holocene. The eastern part of the Kampos abandoned lobe is retreating with a maximum mean rate of −0.94 m/year for the period 1945–2009, whereas the presently active mouth of the river and its immediate surrounds are prograding with a mean rate of about +3.2 m/year.

This study presents a comprehensive flood-hazard assessment and mapping of the Messapios River catchment in Evia Island, Greece, utilizing a combination of Multi-Criteria Decision Analysis (MCDA) and Geographic Information Systems (GISs). Flood-prone zones were identified based on five critical factors, which were determined to be the most influential in the watercourse when excessive discharge overwhelms the drainage network’s capacity: slope, elevation, proximity to stream channels, geological formations, and land cover. The Analytic Hierarchy Process (AHP) was applied to assign weights to these factors, while the final flood-hazard map was generated using the Weighted Linear Combination (WLC) method. The analysis revealed that 17.8% of the catchment, approximately 39 km², falls within a very high flood-hazard zone, while 18.02% (38.91 km²) is classified as highly susceptible to flooding. The flood-prone areas are concentrated in the central, southern, and western parts of the study area, particularly at the lower reaches of the catchment, on both sides of the main streams’ channels, and within the gently sloping, low-lying fan delta of the river. The study area has high exposure to flood hazards due to the significant population of approximately 9000 residents living within the flood-prone zones, a fact that contributes to the area’s potential vulnerability. Additionally, critical infrastructure, including five industrial facilities, the Psachna General High School, the local Public Power Corporation substation, about 21 km of the road network, and 21 bridges are located within the zones classified as having high and very high flood-hazard levels. Furthermore, about 35 km² of economically vital agricultural areas (such as parts of the Psachna and Triada plains) are situated in highly and very highly prone to floods zones. MCDA proved to be an effective and reliable approach for assessing and mapping flood-hazard distribution in the Messapios River catchment. The results provide valuable insights to assist decision-makers in prioritizing intervention areas and efficiently allocate resources.