Monitoring and Predicting Wildfire Using Fire Indices and CIMP5 Data (Case study: Golestan National Park)

Abstract:

Fire occurrence in fields and forest, is quite high in Iran which has intensified recently and it may be due to climate changes. Golestan National Park, is the first national park in Iran which is registered in the list of UNESCO World Heritage as one of the 50 Earth ecological reserves. In 2014, a number of fire occurred in this park. In this study, attempt to monitor Angstrom and Nestrov indexes in order to forecast future fire in the study area. For this purpose, Atmosphere General Circulation model data; Miroc4h, in 0.562*0.562 scale in CIMP5, are used for fire occurred during 4 days in this area. Calculations show that these indicators provide suitable results in fire forecasting, generally. Angstrom index, decreases to 1 or lower almost in 3 fire, in the starting day or one day before; while critical index values is lower than 2. In recent days before first fire, Nestrov index increases above 10000, which is the critical value. It also increases to 25000 during the other fires. Nestrov index increases during the happening of 4 fire without any decrease. The results show that Angstrom index can forecast the day of starting fires better than Nestrov. Conclusively, the results showed that outputs of CIMP5 can be used in forecasting fire, well. It seems that the value index better not to be dependent on daily precipitation but on consecutive and continues precipitations during serial days.