BUSCADOR RECOLECTA

Embargado hasta 15/11/2025, Wind speed, which is significantly affected by terrain and vegetation, is one of the most crucial factors in terms of fire spread. Fire simulators compute wind speed as open 10-m wind speed multiplied by the Wind Adjustment Factor (WAF). In forested sites, the sub-canopy wind speed plays a fundamental role in low intensity fire or prescribed burn, and therefore, in prescribed burn plan. This research aims to estimate a WAF model based on in-stand wind speed at 2-m above ground and forest characteristics. We use Chi-square Automatic Interaction Detection to classify WAF according to the most influential stand variables.

Fifty-seven sampling sites were established for WAF training and testing. WAF ranged from 0.03 to 0.84, showing significant differences due to stand characteristics. Our findings showed that canopy cover is the variable with the greatest influence on WAF. On the one hand, the non-linear WAF model reached a coefficient of determination (R2) of 90 %. On the other hand, a decision tree performed four decision nodes based on canopy cover, stand height, and stand density. These approaches propose a novel method to the identification of WAF for fuel treatment and prescribed burning implementation, avoiding the errors that could be generated using fixed WAF for each fuel model. The proposed model can be used to simulate the effect of different canopy management alternatives, both fuel treatments and timber harvesting, in wind speed at 2-m height.

Background. Handcrews dig handlines to bare mineral soil for fire containment. Increasing the amount of firefighting resources is insufficient to mitigate wildfire damage or decrease the number of large fires. Aims. This study aims to empirically assess handcrew fireline production rates through direct monitoring of suppression actions on active wildfires. Methods. A database was created from information gathered by crew supervisors during wildfires in southern Spain between 2014 and 2019. Fireline production rates were calculated from working time and handline length. Key results. Mean fireline production rate during direct attack in chaparral was 0.33 m min−1 firefighter−1, whereas production in timber litter was 1.06 m min−1 firefighter−1. However, fireline production rate was considerably reduced during indirect attack, in fuel types with high fuel loading, on wildfires larger than 50 ha, after 3 h of sustained suppression action,
with crews of more than nine firefighters, in unsuccessful fire containment, and when the ground crews lacked aerial support. Conclusions. Our results suggest mean fireline production rates need to be modified by working conditions and psychological variables to better inform efficient acquisition and allocation of resources. Implications. Knowing the operating capability of firefighting resources is important to fire managers for reducing uncertainty and guaranteeing the safety and effectiveness of suppression