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

Abstract

Wildfires have demonstrated their destructive powers in several parts of the world in recent years. In an effort to mitigate the hazard of large catastrophic wildfires a common practice is to reduce fuel loads in the landscape. This can be achieved through prescribed burning or mechanically. Prioritising areas to treat is a challenge for landscape managers. To help deal with this problem we present a spatially explicit, multi-period mixed integer programming model. The model is solved to yield a plan to generate a dynamic landscape mosaic that optimally fragments the hazardous fuel continuum while meeting ecosystem considerations. We demonstrate that such a multi-period plan for fuel management is superior to a myopic strategy. We also show that a range of habitat quality values can be achieved without compromising the optimal fuel reduction objective. This suggests that fuel management plans should also strive to optimise habitat quality. We illustrate how our model can be used to achieve this even in the special case where a faunal species requires mature habitat that is also hazardous from a wildfire perspective. The challenging computational effort required to solve the model can be overcome with either a rolling horizon approach or lexicographically. Typical Australian heathland landscapes are used to illustrate the model but the approach can be implemented to prioritize treatments in any fire-prone landscape where preserving habitat connectivity is a critical constraint.

Fuel management operations planning in fire management: A bilevel optimisation approach

“…In Minas et al (2015) a model that integrates fuel management decisions and fire suppression preparedness operations is proposed, while in Minas et al (2014) they introduce a temporal dimension, analysing the strategic implications of multi-period fuel treatment plans. Rachmawati et al (2018) and León et al (2019) build on the latter contribution by incorporating objectives and constraints dealing with…”

Probability-Based Wildfire Risk Measure for Decision-Making

“…This assumption is the cornerstone of the methodology presented. It is a usual simplification taken both by researchers and firefighters [12,13,[17][18][19]22]. Although fire and landscape are naturally seen as a continuous phenomenon, preventive actions used to be taken within finite set of possible places and a network is an appropriate framework for these decisions.…”

“…Therefore, there are multiple solution for F 1 , specifically there are 2 6 = 64 different set satisfying inequality (20). If one of them is chosen, F 2 is determined from the second equation of system (13), obtaining so a different solution for each of the solutions of F 1 .…”

“…In a later study, Ref. [13] take additional considerations into account for preserving habitat quality. Finally, to obtain robust models against uncertainty, as can be seen for instance in [14] for other fields, stochasticity is included in the model.…”

Foreword to the Special Issue on Natural Resource Mathematics

“…The first addressed the optimal management of natural resources given extreme system complexity and uncertainty. In the first paper [25] of this issue, the authors present the problem of managing wildfires with controlled burns to not only protect the environment but also limit accumulating fuel load that can spark massive wildfires with major economic consequences. The work is representative of the types of competing objectives one must often consider in nearly all natural resource management problems.…”