Wildfires have become more destructive and are seriously threatening societies and our ecosystems throughout the world. Once a wildfire escapes from its initial suppression attack, it can easily develop into a destructive huge fire that can result in significant loss of lives and resources. Some human-caused wildfires may be prevented; however, most nature-caused wildfires cannot. Consequently, wildfire suppression and contain- ment becomes fundamentally important; but suppressing and containing wildfires is costly. Since the budget and resources for wildfire management are constrained in reality, it is imperative to make important decisions such that the total cost and damage associated with the wildfire is minimized while wildfire containment effectiveness is maximized. To achieve this objective, wildfire attack-bases should be optimally located such that any wildfire is suppressed within the effective attack range from some bases. In addition, the optimal fire-fighting resources should be deployed to the wildfire location such that it is efficiently suppressed from an economic perspective. The two main uncertain/stochastic factors in wildfire management problems are fire occurrence frequency and fire growth characteristics. In this thesis two models for wildfire management planning are proposed. The first model is a strategic model for the optimal location of wildfire-attack bases under uncertainty in fire occurrence. The second model is a tactical model for the optimal deployment of fire-fighting resources under uncertainty in fire growth. A stochastic mixed-integer programming approach is proposed in order to take into account the uncertainty in the problem data and to allow for robust wildfire management decisions under uncertainty. For computational results, the tactical decision model is numerically experimented by two different approaches to provide the more efficient method for solving the model.

The United States of America (US) has a long-standing history of fire management through the United States Forest Service. Despite this history of fire management, the US faces significant increases in fire potential across the 21st Century owing to future climate change and due to a legacy of past fuel management policies. Since the 1970s the US Forest Service (USFS) has operated a fire danger rating system, known as the National Fire Danger Rating System (NFDRS), which has aimed to portray, anticipate, and mitigate wildfires across the country. Fire danger ratings essentially aim to describe how dangerous a fire would be if it were to ignite and are used to inform not only the general public about wildfire risk but are also used by forest and fire managers to determine their actions in regards to fire suppression. The US Forest Service’s NFDRS currently produces 1-day forecasts of fire danger through the Wildland Fire Assessment System, and other state-focused outlets. The system quantifies common aspects of fire behaviour over wide spatial extents through a number of fire danger indices. These indices represent aspects of fire danger in terms of the likelihood of ignitions, rate of spread, potential heat release, and difficulty of control. Despite the NFDRS’s long-standing utility across the US, relatively few studies have sought to relate fire danger observations and forecasts to records of wildfire activity across its operational spatial extent. The majority of assessments of the NFDRS have been conducted at either single sites or on small spatial scales, despite it being a nation-wide system. This thesis analyses the NFDRS in respect to the occurrence of wildland fires and the final fire sizes they attain over an eight year period (2006-2013) through a number of analyses that; (i) examine the system’s ability to portray wildfire activity across the conterminous US; (ii) assess the NFDRS 1-day forecast’s accuracy; (iii) explore the impact of forecasting inaccuracy on wildfire activity across the conterminous US; and (iv) ascertain what outputs from the NFDRS relate most strongly to the formation of large wildfires. Firstly, this thesis shows that different regions of the US display different levels of correspondence between each observed fire danger indices and recorded fire activity. Areas in the Southern and Eastern Geographic Area Coordination Centers (GACCs) exhibit weaker correlations than those in the Northwest, Northern Rockies, Great Basin and Northern California GACCs. Peaks in fire occurrence are shown to occur at mid–low values of fire danger whereas final fire sizes increase monotonically with each fire danger index. Secondly, it is shown that the 1-day NFDRS forecasts have a strong correspondence with observed fire danger indices across the USA in the majority of locations. However, it is clear that there are multiple instances when these 1-day forecasts either over- or under-predict fire danger conditions, where there is systematic over-prediction of low-end fire danger values and under-prediction of high-end fire danger values. These predictive errors likely stem from errors in forecasted fire weather conditions, the subsequent derived fuel state and the reporting time of daily observations. Thirdly, when the inaccuracy of these forecasts was assessed spatially and temporally, the regions with the highest percentage of inaccurate forecasts were found to be in the Northern Rockies and Great Basin Geographic Area Coordination Centers (GACCs). Over-prediction was found to mainly occur between February and May, whilst peaks in the under-prediction of fire danger were found to be in spring and late summer. Finally, large wildfires appear to occur when fire danger indices are highly variable throughout the lifetime of a fire. As such this highlights the importance of considering daily variations in specific fire danger indices and that current understanding of variable fire danger conditions does not allow for the near-term prediction of large wildfire potential.

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There is growing recognition of the importance of preserving Canada’s forests. Canada’s 348 million hectares of forest land cover 35% of its land area, representing 9% of the world’s forests and 24% of the world’s boreal forests. As a renewable resource, forests offer significant environmental, economic and recreational benefits and innumerable services contributing to the quality of life. Canada has recently entered an era of increased frequency and severity of natural disasters. Ecosystems and communities especially in western Canada have recently undergone a trend of increasing pressures from natural disturbances. These disturbances include wildfires associated with increased fuel load levels from past fire suppression regimes and a widely spread infestation of the mountain pine beetle in addition to changes in weather patterns. Wildfire activity has reached extreme levels in many of the recent years. This thesis profiles an area of western Canada within the Montane Cordillera covering the Nechako Lakes Electoral District in central British Columbia and assesses its vulnerability to the specific hazard of wildfires caused by natural and man-made sources. The objectives of this research are to review, simulate and assess the impact of various fuel management strategies in a sub-section of the Nechako Lakes Electoral District called the Southside. Values at risk include private property and old growth forest in respectively timber supply areas, provincial parks, woodlots and community forests. Simulation results show that firebreaks are effective in significantly reducing the area burned in different parts of the landscape. The performance of different strategies shows large variation. Although this has not been investigated further, such variation has likely been caused by topographic aspects and the positioning of firebreaks in the landscape in relation to climatic parameters. These results can therefore not be extrapolated beyond the simulated area, but do give an indication of the performance variation that may be expected when similar firebreaks are applied elsewhere. The results also show that model performance of all firebreak strategies is heavily and fairly consistently influenced by weather stream parameters. Sensitivity analyses of weather stream parameters show that although the reduction in total area burned varies, the ranking between strategies in their overall performance is consistent regardless of the weather pattern. Combined dry, warm and windy weather conditions lead to a 3.44-fold increase in total area burned as compared to the scenario with average weather conditions. In favourable weather conditions represented by wet, cold and nearly windless conditions, the model shows an 85% reduction in total burned area as compared to the average scenario. These results illustrate the significant impact of uncontrollable variables on the overall result.