2026-06-27T01:51:10Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/726962024-11-25T15:05:29Zcom_20.500.14352_14col_20.500.14352_15

León Caballero, Javier Vitoriano Villanueva, Begoña Hearne, John 2023-06-22T12:30:06Z 2023-06-22T12:30:06Z 2023-11-02 León, J., Vitoriano, B., Hearne, J.: A risk-averse solution for the prescribed burning problem. Safety Science. 158, 105951 (2023). https://doi.org/10.1016/j.ssci.2022.105951 0925-7535 10.1016/j.ssci.2022.105951 https://hdl.handle.net/20.500.14352/72696 https://doi.org/10.1016/j.ssci.2022.105951 Hazard reduction is a complex task involving important efforts to prevent and mitigate the consequences of disasters. Many countries around the world have experienced devastating wildfires in recent decades and risk reduction strategies are now more important than ever. Reducing contiguous areas of high fuel load through prescribed burning is a fuel management strategy for reducing wildfire hazard. Unfortunately, this has an impact on the habitat of fauna and thus constrains a prescribed burning schedule which is also subject to uncertainty. To address this problem a mathematical programming model is proposed for scheduling prescribed burns on treatment units on a landscape over a planning horizon. The model takes into account the uncertainty related to the conditions for performing the scheduled prescribed burns as well as several criteria related to the safety and quality of the habitat. This multiobjective stochastic problem is modelled from a riskaverse perspective whose aim is to minimize the worst achievement of the criteria on the different scenarios considered. This model is applied to a real case study in Andalusia (Spain) comparing the solutions achieved with the risk-neutral solution provided by the simple weighted aggregated average. The results obtained show that our proposed approach outperforms the risk-neutral solution in worst cases without a significant loss of quality in the global set of scenarios. eng https://creativecommons.org/licenses/by/3.0/es/ open access Atribución 3.0 España A risk-averse solution for the prescribed burning problem journal article