I was actively engaged in research activities as part of the Indonesian Peat and Mangrove Restoration Agency (BRGM) project from 2022 to 2023 (ongoing for validation). Our primary objective was the development of the Fire Danger Rating System (FDRS), specifically designed for predicting the vulnerability of peatland fires over Borneo and Sumatra Islands (18,009,347 Ha). This process involved the utilization of hydrometeorological variables coupled with the Peat Fire Vulnerability Index (PFVI). We employed NCEP’s operational Global Forecast System (0.25° x 0.25° resolution), accessible at https://doi.org/10.5065/D65D8PWK. Additionally, dynamic downscaling methods were implemented, refining the resolution to 5 km x 5 km, utilizing the Weather Research and Forecasting (WRF) model. This dynamic downscaling incorporated various parameters, including cumulus, microphysics, planetary boundary layer, shortwave and longwave radiation, surface layers, and land surface. Subsequently, we applied this refined hydrometeorological (rainfall, maximum temperature, and soil moisture) data to the PFVI index formula (Taufik et al., 2023, 2022). In this research, forecasting was conducted up to 7 days ahead (D+7).
From July to November 2023, I was also Involved in the collaborative project between Center for Environmental Science (PPLH) IPB University and PLUM Project (Peat and Mangrove Restoration Company) as the lead project assistant. This project bears resemblance to the research conducted in partnership with BRGM, yet this project focused on developing FDRS in Pagatan, Central Borneo, covering an area of a 846,400 Ha to conduct up to 5 days forecast (D+5).This project posed a new challenge as it required downscaling the FDRS resolution to 1 km x 1 km for a narrow coverage area. In this project, I conducted research on updating the parameterization of the physical model of WRF, identified 3 suitable locations for Automatic Weather Station (AWS), and collected soil samples (9 points) using a ring sample and soil moisture (400 points) using a WET Sensor. Further, the data from AWS, soil physicochemical characteristics, and soil moisture formed the basis for calibration and validation.
The FDRS system has the capability for disaster management as a mitigation measure against peat-fires. Through what I have developed, I incorporate numerical modeling in predicting hydrometeorological variables and a drought-fire index for disaster mitigation. This showcases my expertise in research and underscores the interrelation between meteorology and climatology in applied to the various aspects. I hope it can be implemented not only for peatland fires but also for fires in other types of land and vegetation. My sincere hope is to conduct research and collaborate in related fields such as forecasting, numerical modeling, disaster management, and other environmental applications related to weather and climate.
Note: I utilize R computational language for research and prototype development in this portfolio, alongside fundamental FORTRAN programming and Linux commands for executing the WRF model.
Taufik, M., Haikal, M., Widyastuti, M.T., Arif, C., Santikayasa, I.P., 2023. The Impact of Rewetting Peatland on Fire Hazard in Riau, Indonesia. Sustainability 15, 2169. https://doi.org/10.3390/su15032169
Taufik, M., Widyastuti, M.T., Sulaiman, A., Murdiyarso, D., Santikayasa, I.P., Minasny, B., 2022. An improved drought-fire assessment for managing fire risks in tropical peatlands. Agricultural and Forest Meteorology 312, 108738. https://doi.org/10.1016/j.agrformet.2021.108738