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Wildfires are known to change post-fire watershed conditions such that hillslopes can become prone to increased erosion and sediment delivery. In this work, we coupled wildfire spread and erosion prediction modelling to assess the benefits of fuel reduction treatments in preventing soil runoff. The study was conducted in a 68000-ha forest area located in Sardinia, Italy. We compared no-treatment conditions v. alternative strategic fuel treatments performed in 15% of the area. Fire behaviour before and after treatments was estimated by simulating 25000 wildfires for each condition using the minimum travel time fire-spread algorithm. The fire simulations replicated historic conditions associated with severe wildfires in the study area. Sediment delivery was then estimated using the Erosion Risk Management Tool (ERMiT). Our results showed how post-fire sediment delivery varied among and within fuel treatment scenarios. The most efficient treatment alternative was that implemented near the road network. We also evaluated other factors such as exceedance probability, time since fire, slope, fire severity and vegetation type on post-fire sediment delivery. This work provides a quantitative assessment approach to inform and optimise proactive risk management activities intended to reduce post-fire erosion.

In the last two decades, several models were developed to provide temporal and spatial variations of fire spread and behaviour. The most common models (i.e. BEHAVE and FARSITE) are based on Rothermel's original fire spread equation and describe fire spread and behaviour taking into account the influences of fuels, terrain and weather conditions. The use of FARSITE on areas different from those where the simulator was originally developed requires a local calibration to produce reliable results. This is particularly true for Mediterranean ecosystems, where plant communities are characterised by high specific and structural heterogeneity and complexity. To perform FARSITE calibration, an appropriate fuel model or the development of a specific custom fuel model is needed. In this study, FARSITE was employed to simulate three fire events in Mediterranean areas using different fuel models and meteorological input data, and the accuracy of results was analysed. A custom fuel model designed and developed for shrubland vegetation (maquis) provided realistic values of rate of spread, when compared with estimated values obtained using standard fuel models. Our results confirm that the use of both wind field data and appropriate custom fuel models are crucial to obtain reasonable simulations of wildfire events occurring on Mediterranean vegetation during the drought season.