Browsing by Author "Ertugrul M."

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Influence of climatic factor of changes in forest fire danger and fire season length in Turkey
(2021-01-01) Ertugrul M.; Varol T.; Ozel H.B.; Cetin M.; Sevik H.
In contrast to the expectations of an increase in annual fire activity and the severity of fire season due to climate change and large fires, which have been occurring in recent years, a downtrend has been identified in fire activity in many studies conducted for the whole of Europe in recent years. Similarly, in Turkey, according to the General Directorate of Forestry statistics, while there is an increase in the number of annual fires, the burnt area has a downtrend pattern. In this study, fire activity and climate data statistics for Turkey were examined along with the fire season length and severity. The results obtained conform with the studies conducted in places from Spain at the westernmost part of Mediterranean Europe to Israel at the easternmost part of the Mediterranean. Considering the changes in temperatures, temperature rise of 2 to 3 °C was detected at all stations in the study area. No decrease was observed in the average temperatures at any of the stations within the study period between 1940 and 2018. On the other hand, the precipitation trend varied according to the stations. Although there have been increases in precipitation in Fethiye, Isparta, and Marmaris since 1960, the decrease in precipitation by 132 mm in Afyon since 1970 and the decrease in precipitation by 137 mm in Bodrum since 1940 are attention-grabbing. These stations are followed by Izmir station with 66 mm and Cesme station with 37 mm of decrease, despite being smaller decreases. In the study, the long-term (1940–2018) data of the meteorological stations discussed within the study, the Canadian Fire Weather Index (FWI) and the Fine Fuel Moisture Code (FFMC) values were calculated. According to the FWI results used in determining the severity and length of fire season on the coastline of Turkey from the northern Aegean to Antalya, the likelihood of large fires decreased by about 52% in 2018 compared to 1970. This decrease in FWI value indicates that the fire severity is reduced. The specified decrease in fire severity also explains the reason of the decrease in the burnt area that occurred over the years in Turkey. No significant change was observed in the FFMC values indicating the possibility of human-induced fires between 1970 and 2018.
Investigation of the relationship between burned areas and climate factors in large forest fires in the Çanakkale region
(2019-12-01) Ertugrul M.; Ozel H.; Varol T.; Cetin M.; Sevik H.
Fires pose a serious threat to the forests that lay on the western and southern coastline of Turkey that start with North Aegean coasts and end with the provincial boundaries of Hatay. Çanakkale, a western province of Turkey, is located in the North Aegean boundary and its topography (Dardanelles Strait), climate, and vegetation cover combine to form an inviting recipe to forest fires. Although the province is located in a transitional zone in terms of climate and vegetation, each year it witnesses highly dry and hot fire seasons. Thus, large forest fires occur periodically. In this research, the relationship between the large periodic fires (larger than 100 ha) and the climate data was investigated, with a particular focus on the most severe 8 fire seasons from 1969 to 2007. We established that there is a relationship between 1977, 1985, and 1986 fire seasons and the climate data for the corresponding periods. The remaining 5 seasons in which conflagrations occurred were also found to coincide with the days with high daily severity indices (DSR). These are 1969, 1977, 1985, 1987, and 2008. Additionally, 2008 was determined as the year with the highest fire risk, followed by year 1969.
Prediction of soil-bearing capacity on forest roads by statistical approaches
(2021-08-01) Varol T.; Ozel H.B.; Ertugrul M.; Emir T.; Tunay M.; Cetin M.; Sevik H.
The soil-bearing capacity is one of the important criteria in dimensioning the superstructure. In Turkey, predictability of California Bearing Ratio values, which may be used in the planning and dimensioning of forest roads, of which about 26% lacks the superstructure, by using soil mechanical properties (cost and time efficient parameters that are easier to determine) is investigated. Simple linear regression, multiple linear regression, artificial neural networks and adaptive network–based fuzzy inference system methods were utilized. Two hundred sixty-four California Bearing Ratio values obtained from the project carried out on the forest roads of Bartin Forest Operation Directorate were used in both the production of training-test data and the creation of models. Statistical performance of the models was assessed by means of parameters such as root-mean-square error, mean absolute error and R2. The obtained results show that the bearing capacity values predicted by artificial neural networks and adaptive network based fuzzy inference system models display significantly better performance than the simple linear regression and multiple linear regression models. While the highest prediction capacity belongs to adaptive network based fuzzy inference system (0.969–0.991), it is followed by artificial neural networks (R2 = 0.796–0.974), multiple linear regression (R2 = 0.796) and simple linear regression (R2 = 0.554). What makes the algorithms superior than the traditional statistical models is the fact that they have many processing neurons, each with local connections, and thus have higher error tolerance. On the other hand, for the forest and rural roads, which play an important role in rural development of the forest peasants, to be able to operate all-seasons, superstructure should be immediately built in order to minimize the wear on the roads.