Our study was conducted in the suburban forest of Thessaloniki (Seich Sou), which constitutes one of the most significant suburban forests of Greece and is located northeast of Thessaloniki. In 1997, more than the half of the forest area was destroyed by a wildfire, while recently (May 2019), a significant insect outbreak by the bark beetle Tomicus piniperda was detected. The insect action still goes on, while the infestation has destroyed so far more than 300 ha of forest area. Extensive selective logging and removal of infected trees from the forest were carried out in order to mitigate and restrict the outbreak spread. In the current study, silt-fenced erosion plots were installed on representative locations of disturbed (by fire and insect action) and undisturbed areas, in order to quantify the effect of the above-mentioned forest disturbances on soil erosion and correlate the height and intensity of precipitation with the soil erosion rate. The results show that there was no statistically significant increase in soil erosion in the areas of insect outbreak compared with the control plots. However, there was a statistically significant increase in soil erosion in areas where logging works had been applied as an infestation preventive measure. In addition, the study revealed that 25 years after the forest fire, the erosion rate is still at higher level compared with the undisturbed forest areas. This study could be considered as one of the first attempts to evaluate the impact of an insect outbreak infestation on soil erosion, while there is also a great lack of information concerning the assessment of long-term post-fire effects on the soil erosion of a forest ecosystem.

In this paper, three different flash floods episodes were analyzed, which occurred in October 2006, February 2010, and June 2018 in the Chalkidiki peninsula (North Greece). The Soil Conservation Service (SCS) model and a revised assessment of the CN parameter were applied to estimate the flood hydrographs, and Hydrologic Engineering Center’s-River Analysis System (HEC-RAS) software was used for the flood simulations. Initially, hydrological and hydraulic models were calibrated at Vatonias watershed (240.90 km², North Greece), where three rain gauges and one water level station are located. Vatonias is located very close to the Stavros ungauged watersheds and presents similar geomorphology and land use conditions. The effectiveness and accuracy of the methodology were validated using post-flash-flood measurements. The root mean square error goodness of fit was used to compare the observed and simulated flood depths. Critical success index was calculated for the assessment of the accuracy of observed and modeled flooded areas. The results showed that the dense forest vegetation was not capable of preventing the flash flood generation or reducing the peak discharge, especially in small watersheds characterized by short concentration times. The main cause of flash flood generation was the human interference that influenced the hydraulic characteristics of streams and floodplains. The revised assessment of the CN parameter enhanced the estimation and spatial distribution of CN over the entire watershed. The results revealed that the proposed methodology could be a very useful tool to researchers and policy makers for flood risk assessment of higher accuracy and effectiveness in ungauged Mediterranean watersheds.

The aim of this study was to assess soil erosion changes in the mountainous catchment of the Portaikos torrent (Central Greece) under climate change. To this end, precipitation and temperature data were derived from a high-resolution (25 × 25 km) RegCM3 regional climate model for the baseline period 1974–2000 and future period 2074–2100. Additionally, three GIS layers were generated regarding land cover, geology, and slopes in the study area, whereas erosion state was recognized after field observations. Subsequently, the erosion potential model (EPM) was applied to quantify the effects of precipitation and temperature changes on soil erosion. The results showed a decrease (−21.2%) in annual precipitation (mm) and increase (+3.6 °C) in mean annual temperature until the end of the 21st century, and the above changes are likely to lead to a small decrease (−4.9%) in soil erosion potential.

The potential correlation between fir tree-ring width (Abies borisii regis Mattf.) variability and the respective variability of the main climatic parameters in the region of University Forest of Pertouli (central Greece) are being analyzed in the current study, taking into consideration a 60-year period (1961–2020). Correlation and response function analyses were applied to examine the climate–tree-growth relationship. Precipitation was found to be the most crucial and driving factor that most intensively influences the tree growth of A. borisii-regis trees under Mediterranean climate conditions. It was evident that this species is characterized by drought sensitivity and even a short and mild drought event could significantly influence adversely its growth and productivity. June, May and July precipitation present the higher and statistically significant correlation of monthly precipitation with tree-ring width, affecting the ring-width variability by 31.2%. Temperature (mean, max or min) does not seem to highly influence the tree growth, despite the obvious and statistically significant trend increase that has been recorded in the last decades within the frame of climate change. June maximum temperature presents a strong negative correlation with tree-ring width, while April maximum temperature is positively correlated with tree-ring width. The combined impact of precipitation and max temperatures on tree-ring growth is 38.5%. Snow did not reveal any statistically significant correlation to tree-ring width, independent of the height of monthly snow accumulation. A. borisii-regis grown in high altitudes in the Mediterranean region demonstrate high adaptability to the recorded temperature increase and could potentially be able to adapt in future to even warmer climate conditions. The constructed tree-ring chronology could be utilized towards the implementation of further dendroclimatological analyses and climate reconstruction.

During the last few years, there is a growing concern about climate change and its negative effects on water availability. This study aims to evaluate the performance of regional climate models (RCMs) in simulating seasonal precipitation over the mountainous range of Central Pindus (Greece). To this end, observed precipitation data from ground-based rain gauge stations were compared with RCMs grid point’s simulations for the baseline period 1974–2000. Statistical indexes such as root mean square error (RMSE), mean absolute error (MAE), Pearson correlation coefficient, and standard deviation (SD) were used in order to evaluate the model’s performance. The results demonstrated that RCMs fail to represent the temporal variability of precipitation time series with exception of REMO. Although, concerning the model’s prediction accuracy, it was found that better performance was achieved by the RegCM3 model in the study area. In addition, regarding a future projection (2074–2100), it was highlighted that precipitation will significantly decrease by the end of the 21st century, especially in spring (−30%). Therefore, adaption of mountainous catchment management to climate change is crucial to avoid water scarcity.

In this study, the authors evaluated the spatial and temporal variability of rainfall over the central Pindus mountain range. To accomplish this, long-term (1961–2016) monthly rainfall data from nine rain gauges were collected and analyzed. Seasonal and annual rainfall data were subjected to Mann–Kendall tests to assess the possible upward or downward statistically significant trends and to change-point analyses to detect whether a change in the rainfall time series mean had taken place. Additionally, Sen’s slope method was used to estimate the trend magnitude, whereas multiple regression models were developed to determine the relationship between rainfall and geomorphological factors. The results showed decreasing trends in annual, winter, and spring rainfalls and increasing trends in autumn and summer rainfalls, both not statistically significant, for most stations. Rainfall non-stationarity started to occur in the middle of the 1960s for the annual, autumn, spring, and summer rainfalls and in the early 1970s for the winter rainfall in most of the stations. In addition, the average magnitude trend per decade is approximately −1.9%, −3.2%, +0.7%, +0.2%, and +2.4% for annual, winter, autumn, spring, and summer rainfalls, respectively. The multiple regression model can explain 62.2% of the spatial variability in annual rainfall, 58.9% of variability in winter, 75.9% of variability in autumn, 55.1% of variability in spring, and 32.2% of variability in summer. Moreover, rainfall spatial distribution maps were produced using the ordinary kriging method, through GIS software, representing the major rainfall range within the mountainous catchment of the study area.