Wind and slope effects on ROS during the fire propagation in East-Mediterranean pine forest litter
Introduction
Forest fires are a natural disaster causing a growing volume of damage both to environmental systems and infrastructure worldwide. European forest fires have occurred mainly in south Europe due to climatic peculiarities: high average annual temperatures, less number of rainy days and a large portion of wooded surfaces. Climate changes and the effects of human activity increase the risk of occurrence of forest fires and the damage caused to both nature and economy.
A long-term analysis of wildland fires in Greece shows that for the period between 1955 and 1999 up to 11,500 ha burned out on average per year up to the year 1973. Approximately a third of this area was forest, and the rest was partly brushland and partly grassland of various types [1]. Following 1974, significant increase in the surface area burned by fires was observed and this upward trend still continues nowadays. Human and ecological destruction had reached the largest official records since the 1950s in the 2007 summer. The country lost about 2,70,000 ha of vegetation. According to the European Forest Fire Information System (EFFIS) the vast majority, 1,83,987 ha, went in just 4 days between August 24 and 27. The total death toll reached 75 as wildfires swept though large swathes of the Peloponnese, Evia island and Mount Parnes and Penteli, forcing residents to abandon their villages (some 110 villages, 4100 homes destroyed and 16,000 homeless) and prompting an international aid effort.
One of the activities in support of efficient forest fire fighting is studying fire behaviour under various conditions: atmospheric conditions, topographic characteristics and vegetation characteristics. The rate of spread of fire occurring in a specific vegetation layer largely depends on wind velocity, fuel moisture content and slope of ground surface [2], [3], [5]. Studies of the effects of these factors are carried out in laboratory conditions or under controlled fires in real vegetation beds.
Statistical processing of experimental results provides an opportunity to establish relationships between variations in fire behaviour factors and characteristics, and to create empirical models [6], [7]. Rothermel [9] presents the variations in the fire front as a sum of the individual effects of wind velocity and slope of terrain. Vegetation characteristics and other conditions are considered for the rate of fire spread (ROS) baseline value determined for fire occurring in a horizontal terrain and under no-wind conditions. This approach has been further developed [3] considering also the effects of wind direction and the angle closed by the leading edge of the fire front.
The adoption of this approach allows drawing up fairly simple equations to present the relationship between ROS and the factors described using the increase in the rate of spread when modelling the isolated effects of wind and slope of terrain. The paper which follows presents the experimental results obtained when studying the rate of fire spread of fires occurring in vegetation beds comprising the species Pinus halepensis (PH) or Pinus pinaster (PP) needles. The samples were taken in the region Mt. Pelion, Magnesia, Central Greece.
Section snippets
Experimental equipment and methodology
Two separate fuel models for P. halepensis and P. pinaster pine needles of the relevant parameters were developed based on measurements of fuel particle characteristics [8]. In the laboratory experiments the spread of fire into the vegetation fuel bed, made up of each one of these two types of vegetation species, was simulated. The objectives for these experiments were to obtain data on the characteristics of fire behaviour, information also on flow parameters inside the fire zone and around,
Results
Fig. 3, Fig. 4 present the results from experiments and indicate the strong relations between ROS-wind velocity and terrain slope.
Data from experiments for fire spreading in a pine needle fuel bed have been given in Mendes-Lopes et al. [4], [11], [12], [13], [2]. These reports involve vegetation species from the Mediterranean types occurring in Portugal, Spain and France, not giving any consideration to the P. halepensis species. The latter is more representative for Greece and the eastern
Discussion
A major influence on ROS values, as found in the experiments was exerted by the availability and magnitude of wind velocity and the slope of the surface. In the experiments the direction of the two independent variables coincided and their individual effects were either aggregated or subtracted from the relevant values for both.
Conclusions
The rates of fire spread in PH fuel beds were higher than in PP beds and the combustion process took place mainly on the fuel top surface. In P. pinaster fire spread with lower rates although it reached deeper into the fuel bed providing fuller burning and less remains. ROS values ranged between 10 and 600 cm/min.
Ground surface slope, fire spread size and direction were determinant factors for the values of the front rates along the positive (upslope) slope gradient. The most severe case of fire
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2021, Fire Safety JournalCitation Excerpt :The rate of fire spreading will depend to a large extent on wind speed, fuel moisture content, and the inclination of the hillslope [38,39]. Boboulos and Purvis [40] insisted upon this idea when used the status of Pinus halepensis and Pinus pinaster forests, some geomorphologic features (mainly the slope), and climate characteristics (for example, wind) to assess the development of fire risks. In this way, we strongly agree that remote sensing images must be used to assess geology, soils, land-use changes, and estimation of topographic parameters [41,42].
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2020, Ecological InformaticsCitation Excerpt :Slopes with an inclination of 40–49° were assessed as danger class 5, since fire spreads faster on steeper slopes. Areas with an inclination of <10° and ≥ 50° were categorized as danger class 1, because of the lower propagation danger in flat surfaces (Boboulos and Purvis, 2009) and the lack of continuous forest cover in very steep areas. An overview of the classifications and thresholds of the data layers vegetation, slope and aspect is given in Table 2.
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