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.

A new methodology for shallow landslide forecasting in wildfire burned areas is proposed by estimating the annual probability of rainfall threshold exceedance. For this purpose, extensive geological fieldwork was carried out in 122 landslides, which have been periodically activated in Western Greece, after the devastating wildfires that occurred in August 2007 and burned large areas in several parts of Western Greece. In addition, daily rainfall data covering more than 40 years has been collected and statistically processed to estimate the exceedance probability of the rainfall threshold above which these landslides are activated. The objectives of this study are to quantify the magnitude and duration of rainfall above which landslides in burned areas are activated, as well as to introduce a novel methodology on rainfall-induced landslide forecasting. It has been concluded that rainfall-induced landslide annual exceedance probability in the burned areas is higher when cumulative rainfall duration ranges from 6 to 9 days with local differences due to the prevailing geological conditions and landscape characteristics. The proposed methodology can be used as a basis for landslide forecasting in wildfire-affected areas, especially when triggered by rainfall, and can be further developed as a tool for preliminary landslide hazard assessment.

The primary objective of this research is to demonstrate advanced surveying methods and techniques for coastal erosion identification and monitoring in a densely human-populated coastline, the southern coastline of the Gulf of Patras (Greece), which diachronically suffers erosion problems expected to become worse in the forthcoming years due to climate change and human intervention. Its importance lies in the fact that it presents a robust methodology on how all modern scientific knowledge and techniques should be used in coastal erosion problems. The presented methods include the use of satellite and aerial photo imaging, shallow seabed bathymetry and morphology, sediment sampling, geotechnical investigations, as well as hydrodynamic modelling. The results are extensively analyzed in terms of their importance in coastal erosion studies and are cross-validated to define those areas most vulnerable to erosion. Towards this scope, the seabed erosion rate produced by hydrodynamic modelling is compared with the coastal vulnerability index (CVI) calculations performed in the examined area to identify which coastal zones are under a regime of intensive erosion. The results between the CVI and the seabed erosion rate appear to coincide in terms of the erosion potential, especially in zones where the vulnerability regime has been calculated as being high or very high, with the P. oceanica meadows playing an important role in reducing erosion.