EGU21-15159, updated on 04 Mar 2021
https://doi.org/10.5194/egusphere-egu21-15159
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Soil Moisture and Live Fuel Moisture Content as key remote sensing variables to unlock improved wildfire predictions

Florian Briquemont1 and Akli Benali2
Florian Briquemont and Akli Benali
  • 1Universidade de Lisboa, Instituto Superior de Agronomia, Centro de Estudos Florestais, Portugal (florianbriquemont@gmail.com)
  • 2Universidade de Lisboa, Instituto Superior de Agronomia, Centro de Estudos Florestais, Portugal (aklibenali@gmail.com)

Large wildfires are amongst the most destructive natural disasters in southern Europe, posing a serious threat to both human lives and the environment.

Although wildfire simulations and fire risk maps are already very a useful tool to assist fire managers in their decisions, the complexity of fire spread and ignition mechanisms can greatly hinder their accuracy. An important step in improving the reliability of wildfire prediction systems is to implement additional drivers of fire spread and fire risk in simulation models.

Despite their recognized importance as factors influencing fuel flammability and fire spread, soil moisture and live fuel moisture content are rarely implemented in the simulation of large wildfires due to the lack of sufficient and accurate data. Fortunately, new satellite products are giving the opportunity to assess these parameters on large areas with high temporal and spatial resolution.

The purpose of this study is twofold. First, we aimed to evaluate the capabilities of satellite data to estimate soil moisture and live fuel moisture content in different landcovers.  Secondly, we focused on the potential of these estimates for assessing fire risk and fire spread patterns of large wildfires in Portugal. Ultimately, the goal of this study is to implement these estimated variables in fire spread simulations and fire risk maps.

We compared datasets retrieved from Sentinel 1, SMAP (Soil Moisture Active Passive radiometer) and MODIS (Moderate Resolution Imaging Spectrometer) missions. Several estimators of LFMC based on spectral indices were tested and their patterns were compared with field data. Based on these estimators, we assessed the impact of LFMC and soil moisture on the extent and occurrence of large wildfires. Finally, we built a database of detailed historical wildfire progressions, which we used to evaluate the influence of soil moisture and LFMC on the velocity and direction of the fire spread.

How to cite: Briquemont, F. and Benali, A.: Soil Moisture and Live Fuel Moisture Content as key remote sensing variables to unlock improved wildfire predictions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15159, https://doi.org/10.5194/egusphere-egu21-15159, 2021.

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