Inovasi Model Prediksi Titik Api Menggunakan Consecutive Dry Days (CDD) pada Wilayah Lahan Gambut Provinsi Riau

Abstract

Riau Province, which has a peatland area of ​​5.09 million hectares or 56.42% of the area of ​​peatlands on the island of Sumatra, is one of the provinces in Indonesia which has the greatest potential for forest fires to devastate hundreds of hectares of forest and gardens and increase home gas emissions glass in the atmosphere. Forest fires that occur are closely related to Consecutive Dry Days (CDD) or consecutive days without rain (HTH) which result in low humidity, thereby affecting the potential for hotspots to emerge, especially around peatlands. CDD, which is the result of the accumulation of the amount of HTH in one period between rainy day events, is calculated using CMORPH precipitation data (CPC MORPHing technique). Hotspot data is obtained from NOAA and Hotspot event data with a confidence level of more than 70% in the eastern region of Riau province where there is a peatland. The probability of a Hotspot occurring is calculated based on the CDD for each grid that will produce a CDD value with a significant probability for the occurrence of a Hotspot on the grid each month. The level of density of Hotspots in each season period with a high category is in the JJA and MAM periods. An early warning system for the emergence of a Hotspot based on the level of Hotspot and CDD density is carried out the day before the opportunity arises with a value less than or equal to 0.5. With an average CDD value for early warning in MAM is 13 days and in JJA is eight days. This research is expected to be able to be applied in early warning of forest and land fires in Riau.