- Hydrosat, Luxembourg
Soil moisture is an important variable in wildfire risk assessment, influencing fuel moisture content, fire ignition potential and fire spread dynamics. In the existing fire danger rating systems, soil moisture is largely overlooked while at the same time, wildfire seasons are increasingly becoming longer with larger burnt areas. Studies have shown that using, e.g., in situ or model soil moisture information in fire danger ratings could better help forecast wildfires and lead to earlier warnings of wildfire dangers. On the other hand, the availability of ground-based monitoring stations providing reliable soil moisture information is limited.
This study focuses on validating our in-house soil moisture models against ground-based measurements, ensuring the model’s reliability for wildfire risk modelling. The large-scale, spatially resolved soil moisture and related variables were derived using thermal infrared remote sensing combined with surface energy and soil water balance models. Ground-based soil moisture data were obtained from networks such as the International Soil Moisture Network for diverse land cover types. Validation was carried out using statistical performance metrics and correlation coefficients to identify discrepancies and to improve model accuracy.
While the modelling and validation processes are still ongoing, preliminary results suggest there is an acceptable agreement for crop fields and ground-based data, whereas forest land cover validation remains challenging, showing the need for further refinements in the soil moisture model. This work also highlights the importance of access to reliable and frequent ground-based soil moisture data. Application to wildfire seasons in Australia show that soil moisture and evapotranspiration have high feature importance, emphasising their relevance in accurately predicting fire risk.
This research is an important step forward for bridging the gap between soil moisture science and wildfire risk modelling, also creating effective discussion on the topic, advancing our understanding and potentially improving fire danger ratings in the future.
How to cite: Byckling Smith, K., Chartrand, R., Werner, F., Ziliani, M., and de Leede, I.: Validating soil moisture models for wildfire risk assessment , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13222, https://doi.org/10.5194/egusphere-egu25-13222, 2025.