PEAT-FWI: Improving the Fire Weather Index for peatlands with Hydrological Modeling and L-band Microwave Observations
- 1Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium (jonas.mortelmans@kuleuven.be)
- 2Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- 3Department of Physics and Applied Mathematics, Columbia University, New York, USA
- 4NASA Goddard Institute for Space Studies, New York, USA
- 5School of Earth and Environmental Sciences, Cardiff University, Cardiff, Wales
The Fire Weather Index (FWI) is used worldwide to estimate the danger of wildfires. The FWI system integrates meteorological parameters and empirically combines them into several moisture codes, each representing a different fuel type. These moisture codes are then used in combination with wind speed to estimate a fire danger. Originally, the FWI system was developed for a standard jack pine forest, however, it is widely used by fire managers to assess the fire danger in different environments as well. Furthermore, it is often also used to assess the vulnerability of organic soils, such as peatlands, to ignition and depth of burn. The utility of which is often questioned.
This research aims at improving the original FWI for northern peatlands by replacing parts of the original, purely weather-based FWI system with satellite-informed model estimates of peat moisture and water level. These come from a data assimilation output combining the NASA catchment model, including the peat modules PEATCLSM, and Soil Moisture and Ocean Salinity (SMOS) L-band brightness temperature observations. The predictive power of the new, peat-specific FWI (PEAT-FWI) is evaluated against the original FWI against fire data of the global fire atlas from 2010 through 2018 over the major northern peatlands areas. For the evaluation, the fires are split up in early and late season fires, as it is hypothesized that late fires are more hydrological driven, and the predictive power of the PEAT-FWI will thus differ between the two types of fires. Our results indeed indicate that the PEAT-FWI improves the predictive capability of estimating fire risk over northern peatlands in particular for late fires. By using a receiver operating characteristics (ROC) curve to evaluate the predictive power of the FWI against a random estimate, the area under the curve increases by up to 10% for the PEAT-FWI compared to the original FWI. The recent version 7 release of the operational Soil Moisture Active Passive (SMAP) Level-4 Soil Moisture Data Assimilation Product now includes PEATCLSM, thus, the proposed PEAT-FWI is straightforward to include in operational FWI products.
How to cite: Mortelmans, J., Felsberg, A., De Lannoy, G., Veraverbeke, S., Field, R., Andela, N., and Bechtold, M.: PEAT-FWI: Improving the Fire Weather Index for peatlands with Hydrological Modeling and L-band Microwave Observations, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3310, https://doi.org/10.5194/egusphere-egu23-3310, 2023.