FUEL MODELLING AND POTENTIAL FIRE BEHAVIOR IN TURKEY

Abstract

Opis karakteristika goriva je nužan podatak za modele ponašanja požara koji mogu dati podršku odlukama za požarno upravljanje. Modeli goriva opisuju karakteristike goriva za sustave modeliranja požara koji se temelje na Rothermelovom modelu širenja požara. U ovoj studiji, podaci o ponašanju požara prikupljeni u terenskim eksperimentima u različitim kompleksima goriva u Turskoj korišteni su u procesu razvoja modela goriva. Napravljeno je devet modela goriva za nisku i visoku makiju, anatolski crni bor (P. nigra J.F. Arnold subsp. nigra var. caramanica (Loudon) Rehder), stelju te otpad, varijable u starosti i težini. BehavePlus simulacije stope širenja požara, duljine plamena i intenziteta požarne fronte za tipične ljetne vremenske uvjete naglašavaju potpuno drukčiji potencijal požara između izučavanih tipova goriva. Iz simulacija su očite teškoće u bavljenju kompleksom goriva kojima dominira živo gorivo. Nasuprot tomu, model je točno predvidio privremeno smanjenje ponašanja požara u otpadu. Ova studija pokazuje ključnu važnost eksperimentalnih podataka o požaru, kako bi se izvršila parametrizacija modela goriva.Description of fuel characteristics is an essential input to fire behavior models that can provide decision-support for fire management. Fuel models describe fuel characteristics for fire modeling systems based on Rothermel’s fire spread model. In this study, fire behavior data collected in field experiments in different fuel complexes in Turkey is used in the process of fuel model development. Nine fuel models were built for low and tall maquis, Anatolian black pine (P. nigra J.F. Arnold subsp. nigra var. caramanica (Loudon) Rehder), litter, and slash variable in age and load. BehavePlus simulations of fire rate of spread, flame length and fireline intensity for typical summer weather conditions highlight the quite different fire potential between the studied fuel types. The difficulty in dealing with fuel complexes dominated by live fuels was evident from the simulations. On the contrary, the model correctly predicted the observed temporal decrease of fire behavior in slash. This study shows the crucial importance of experimental fire data to parameterize fuel models.