Optimisation models for planning in fuel management

Rachmawati, R 2016, Optimisation models for planning in fuel management, Doctor of Philosophy (PhD), Mathematical and Geospatial Sciences, RMIT University.

Document type: Thesis
Collection: Theses

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Title Optimisation models for planning in fuel management
Author(s) Rachmawati, R
Year 2016
Abstract Uncontrolled wildfires can lead to loss of life and property and destruction of natural resources. Fuel management, or treatment planning by way of controlled burning or mechanical clearing, is an important tool used in many countries to reduce the risk of large wildfires. Management for fuel reduction should not be done in isolation of the ecological requirements of the ecosystem. Maintaining the ecological integrity of the landscape should also be considered. However, reducing fuel load in the landscape while maintaining ecological balance presents land managers with seemingly conflicting objectives. In this thesis, Mixed Integer Programming (MIP) models are developed to determine when and where fuel reduction activities should take place while maintaining vital ecological requirements of the landscape. The approaches are multi-period fuel treatment scheduling that tracks the age of each vegetation type and takes into account both the frequency of fire that it can tolerate and the frequency of fire necessary for fire-dependent species. The first model determines a long-term scheduling of the location for fuel treatment activities each year to minimise total fuel load over the planning horizon. The second 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. The efficacy of the first two models was tested using randomised data from 711 public treatment units in the Barwon-Otway district of Victoria. The third model optimally schedules fuel treatment to fragment high-risk regions while ensuring sufficient habitat connectivity over time and space. This is critical for the conservation of fauna. This model is demonstrated in a series of computational experiments with a hypothetical landscape represented in grid cells. The formulation, however, is valid for real landscapes and provides the means to an integrated approach to ecosystem conservation and reducing the risk of large wildfires.
Degree Doctor of Philosophy (PhD)
Institution RMIT University
School, Department or Centre Mathematical and Geospatial Sciences
Subjects Environmental Management
Operations Research
Keyword(s) Mixed integer programming
Fragmenting contiguous high-risk fire areas
Controlled burning
Habitat connectivity and fuel reduction
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Created: Wed, 18 May 2016, 11:51:42 EST by Keely Chapman
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