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 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.
In Greece the hydrological analysis of ephemeral streams has been especially difficult due to the lack of precipitation and discharge gauges. This study focuses on the investigation of possible relationship between morphometric characteristics of small to medium drainage basins and hydrological indices in order to discover morphometric parameters "predictors" of flash flood potential of ungauged catchments. Twenty-two morphometric parameters of twenty-seven drainage basins (ranging in area between 3.6 km 2 and 330.5 km 2) located in the northern part of the Peloponnese in southern Greece were calculated utilizing GIS software ArcGIS10. Hydrological modeling was performed using a simplified Matlab implementation of TOPMODEL, a conceptual model based on the principle of variable contributing area to runoff production through saturated overland flow, and LISEM, a physically based hydrologic and soil erosion model. Rainfall-runoff simulations were performed for an extreme precipitation event. The simulations outcomes, which include the peak discharge, time to peak and the percentage runoff, were correlated with the morphometric parameters of the catchments. Results were not consistent between the two models, probably due to their different structure, with the LISEM results being closer to what is anticipated. The results demonstrate that area, length of the basin, perimeter and compactness factor appear better correlated with the peak discharge (Qpeak) of the catchment. The same parameters as well as Melton's number correlate with percentage runoff (C), while "celerity" of the flood wave (length of the basin/time to peak) is better correlated with relief, indicating that as the relief becomes greater, the response of the basin becomes fastest.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.