An optimisation approach for fuel treatment planning to break the connectivity of high-risk regions

Abstract

Uncontrolled wildfires can lead to loss of life and property and destruction of natural resources. At the same time, fire plays a vital role in restoring ecological balance in many ecosystems. Fuel management, or treatment planning by way of planned burning, is an important tool used in many countries where fire is a major ecosystem process. In this paper, we propose an approach to reduce the spatial connectivity of fuel hazards while still considering the ecological fire requirements of the ecosystem. A mixed integer programming (MIP) model is formulated in such a way that it breaks the connectivity of high-risk regions as a means to reduce fuel hazards in the landscape. This multi-period model tracks the age of each vegetation type and determines the optimal time and locations to conduct fuel treatments. The minimum and maximum Tolerable Fire Intervals (TFI), which define the ages at which certain vegetation type can be treated for ecological reasons, are taken into account by the model. Previous work has been limited to using single vegetation types implemented within rectangular grids. In this paper, we significantly extend previous work by modelling multiple vegetation types implemented within a polygon-based network. Thereby a more realistic representation of the landscape is achieved. An analysis of the proposed approach was conducted for a fuel treatment area comprising 711 treatment units in the Barwon-Otway district of Victoria, Australia. The solution of the proposed model can be obtained for 20-year fuel treatment planning within a reasonable computation time of eight hours.

Optimizing prescribed fire allocation for managing fire risk in central Catalonia

“…Overall, these studies provide a number of methodological frameworks to solve the many challenges facing wildfire managers tasked with reducing wildfire risk. These challenges include identifying treatment spatial arrangement, treatment timing in long-term forest planning, suitability and combination with other treatments (thinning or mastication), and treatment integration into multi-functional forest management programs (González-Olabarria and Pukkala, 2011;Minas et al, 2014;Rachmawati et al, 2016;Vogler et al, 2015). In the current work we developed a multi-objective optimization approach to define optimal strategies and prioritize areas for implementing prescribed fire activities as part of larger fuel management programs.…”

Detecting critical nodes in forest landscape networks to reduce wildfire spread

“…Optimization has been widely used to support decisions about fire prevention and suppression [17][18][19][20]. Several linear programming models have been proposed to assist with the planning of wildfire prevention and fuel treatments aimed to reduce the severity of future fires in the landscape and their potential spread [20][21][22][23][24][25][26][27]. The proposed models featured an objective of fragmenting the landscape to minimize fire hazard (i.e., the combination of fire spread and intensity) [22] and were formulated as single-or multi-period site treatment problems with variable fuel accumulation rates [19,23].…”

“…Kabli et al [28] proposed a two-stage stochastic integer programming method to allocate fuel treatment to minimize the total treatment cost and expected future losses. The optimal fuel treatment models of Minas et al [19] and Rachmawati et al [27] considered a landscape with multiple land-cover types and estimated fuel loads as a function of vegetation age. Acuna et al [29] and Alonso-Ayuso et al [30] proposed a harvest planning model incorporating the creation of fire breaks to minimize wildfire risk while also achieving a desired harvesting objective.…”

“…Several of the proposed models minimized connectivity between forest patches with high wildfire risk as a way to reduce fire spread potential in a landscape [27]. Minas and Hearne [35] outlined a fuel treatment model that clustered sites where prescribed burns were scheduled.…”

A Landscape-Scale Optimisation Model to Break the Hazardous Fuel Continuum While Maintaining Habitat Quality

“…An early model addressing the fuel hazard problem only was formulated and illustrated on a regular grid [26]. The approach was then extended to include multiple vegetation classes in a real landscape [32]. The computational effort in this work limited the analysis to some extent.…”