The relevance of this study is determined by the increasing scale and damage caused by wildfires, despite a simultaneous decline in their overall number, which highlights the inadequacy of existing methods for calculating firefighting forces and resources in the face of modern challenges. Particular difficulties arise in combating fires in remote areas with limited access to water resources. This study analyzes statistical data from EMERCOM of Russia for 2020–2024, performs a taxonomic analysis of wildfires, and develops a regression model for predicting the demand for firefighting forces and equipment. The model was tested using a real wildfire case in the Tepe-Oba area (Republic of Crimea, 2024, with a burned area of 150 hectares), which demonstrated high predictive accuracy: the deviation from actual data did not exceed 2 % both in terms of the number of deployed firefighting units and the amount of material damage. The practical significance of the research lies in the possibility of applying the model for operational planning and decision support, including the justification for deploying mobile pipeline groups and retrofitted military off-road equipment (ARS-14, TMS-65). The limitations of the model are related to its inability to account for equipment failures and logistical difficulties in extinguishing fires in hard-to-reach areas, which define the directions for its further development.
Tatyana Protsenko (2025) studied this question.