Drought Index for Peatland Wildfire Management in Central Kalimantan, Indonesia During El Nino Phenomenon

Peatland wildfires, especially in tropical ecosystems, are often caused by drought, and lead to smoke and other related problems in all aspects of community life in Indonesia, especially in Central Kalimantan. Drought is worsened by the number of dry days in the dry season, known as the El Nino phenomenon, and the drainage system in a peatland. Additionally, drought decreases the water table and increases the probability of occurrence of wildfires in peatland areas. This study aims to modify the numerical formula of the drought factor (DFt) in the Keetch-Byram drought index (KBDI) based on tropical peatland wildfire conditions in Central Kalimantan during the El Nino phenomenon in 2015. Furthermore, it applies a revised peatland water table reference of 400 mm below the ground surface, based on previous research and the Government regulation on peatland ecosystem protection and management in Indonesia. These El Nino conditions caused a rain decline of approximately 35% in Block A, Ex-Mega Rice Project, Mantangai sub-District, Kapuas District, Central Kalimantan Province. The modified KBDI is compared with the Number of Fire Alerts (NFA) using NASA's Active Fire Data in 2015. The analysis results demonstrate that the modified DFt under tropical peatland conditions leads to an increase in the drought index value, beginning on the driest days between July and November 2015. The value of the KBDI drought index increases from the high to the extreme index from September to November 2015, when as many as 61 extreme drought indices became indicators for peatland wildfire risk assessment. The extreme KBDI is directly proportional to the NFA recorded during 2015, and the highest number of fire alerts is observed for October 2015, with 1746 fire alerts within 31 days and extreme drought indices from 27 days. Hence, this modified formula is suitable for wildfire conditions on this peatland in Central Kalimantan. Overall, the modified DFt can be successfully applied to the El Nino phenomenon in 2015.