Wind - terrain effects on the propagation of wildfires in rugged terrain: fire channelling

Sharples, Jason J.; McRae, Richard H. D.; Wilkes, Stephen R.

doi:10.1071/wf10055

Cited by 111 publications

(158 citation statements)

References 21 publications

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“…3c, 2.5 h earlier. The lateral fire propagation evident at GV-N is consistent with and best explained by the fire channelling phenomenon discussed by Sharples et al (2012). Indeed, the steep lee slopes of the numerous side spurs leading north to Carmarthen Ridge satisfy the preconditions necessary for fire channelling to occur .…”

Section: Fire Channelling Banks Ridge 22 Novembersupporting

confidence: 54%

“…In their analysis of the 2003 Canberra bushfires, Sharples et al (2012) demonstrated several cases where interactions between strong winds and rugged topography resulted in rapid wildfire development. The resulting process, which they termed "fire channelling", resulted in a transition from the usual frontal burning pattern to an areal burning pattern caused by a combination of rapid lateral fire propagation (transverse to the prevailing winds) and downwind infill by short-to medium-range spotting.…”

Section: R H D Mcrae Et Al: Linking Local Wildfire Dynamics To Pymentioning

confidence: 99%

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Linking local wildfire dynamics to pyroCb development

McRae¹,

Sharples

Fromm

2015

Nat. Hazards Earth Syst. Sci.

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Section: Fire Channelling Banks Ridge 22 Novembersupporting

confidence: 54%

Section: R H D Mcrae Et Al: Linking Local Wildfire Dynamics To Pymentioning

confidence: 99%

Linking local wildfire dynamics to pyroCb development

McRae¹,

Sharples

Fromm

2015

Nat. Hazards Earth Syst. Sci.

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“…Fire severity in these areas was primarily influenced by weather conditions on the day of the fire than by their physical and topographic properties. It is likely that the highly variable nature of fire weather was responsible for the range of fire severity responses observed across these moderate predicted classes (Bradstock et al 2010, Price and Bradstock 2012, Sharples et al 2012.…”

Section: Discussionmentioning

confidence: 99%

Identifying the location of fire refuges in wet forest ecosystems

Berry

Driscoll

Stein

et al. 2015

Ecological Applications

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The increasing frequency of large, high-severity fires threatens the survival of old-growth specialist fauna in fire-prone forests. Within topographically diverse montane forests, areas which experience less severe or fewer fires compared with those prevailing in the landscape may present unique resource opportunities enabling old-growth specialist fauna to survive. Statistical landscape models which identify the extent and distribution of potential fire refuges may assist land managers to incorporate these areas into relevant biodiversity conservation strategies. We used a case study in an Australian wet montane forest to establish how predictive fire simulation models can be interpreted as management tools to identify potential fire refuges. We examined the relationship between the probability of fire refuge occurrence as predicted by an existing fire refuge model and fire severity experienced during a large wildfire. We also examined the extent to which local fire severity was influenced by fire severity in the surrounding landscape. We used a combination of statistical approaches including generalised linear modelling, variogram analysis and receiver operating characteristics and area under the curve analysis (ROC AUC). We found that the amount of unburnt habitat and the factors influencing the retention and location of fire refuges varied with fire conditions. Under extreme fire conditions, the distribution of fire refuges was limited to only extremely sheltered, fire-resistant regions of the landscape. During extreme fire conditions, fire severity patterns were largely determined by stochastic factors that could not be predicted by the model. When fire conditions were moderate, physical landscape properties appeared to mediate fire severity distribution. Our study demonstrates that land managers can employ predictive landscape fire models to identify the broader climatic and spatial domain within which fire refuges are likely to be present. It is essential that within these envelopes, forest is protected from logging, roads and other developments so that the ecological processes related to the establishment and subsequent use of fire refuges are maintained. Abstract. The increasing frequency of large, high-severity fires threatens the survival of old-growth specialist fauna in fire-prone forests. Within topographically diverse montane forests, areas that experience less severe or fewer fires compared with those prevailing in the landscape may present unique resource opportunities enabling old-growth specialist fauna to survive. Statistical landscape models that identify the extent and distribution of potential fire refuges may assist land managers to incorporate these areas into relevant biodiversity conservation strategies. Disciplines Medicine and Health Sciences | Social and Behavioral SciencesEcological Applications, 25(8), 2015, pp. 2337-2348 Ó 2015 by the Ecological Society ofWe used a case study in an Australian wet montane forest to establish how predictive fire simulation models can be in...

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“…Fire occurrence is favoured by low humidity and high temperature, whereas wind speed has long been recognised as the crucial factor influencing the rate of spread of wildfires (Rothermel 1972;Fosberg 1978). In addition, interactions of fuels and weather with local topography can greatly influence fire activity (Moritz et al 2010;Sharples et al 2012). Fire behaviour models incorporate information on fuels, topography and weather to predict fire spread (Sullivan 2009a(Sullivan , 2009b(Sullivan , 2009c.…”

Section: Discussionmentioning

confidence: 99%

Mapping the daily progression of large wildland fires using MODIS active fire data

Veraverbeke

Sedano

Hook

et al. 2014

Int. J. Wildland Fire

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Abstract. High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the timing of burnt area for 16 large wildland fires. For each fire, parameters for the kriging model were defined using variogram analysis. The optimal number of observations used to estimate a pixel's time of burning varied between four and six among the fires studied. The median standard error from kriging ranged between 0.80 and 3.56 days and the median standard error from geolocation uncertainty was between 0.34 and 2.72 days. For nine fires in the south-western US, the accuracy of the kriging model was assessed using high spatial resolution daily fire perimeter data available from the US Forest Service. For these nine fires, we also assessed the temporal reporting accuracy of the MODIS burnt area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared with 33% for MCD45A1 and 53% for MCD64A1. Systematic application of this algorithm to wildland fires in the future may lead to new information about vegetation, climate and topographic controls on fire behaviour.

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Wind - terrain effects on the propagation of wildfires in rugged terrain: fire channelling

Cited by 111 publications

References 21 publications

Linking local wildfire dynamics to pyroCb development

Linking local wildfire dynamics to pyroCb development

Identifying the location of fire refuges in wet forest ecosystems

Mapping the daily progression of large wildland fires using MODIS active fire data

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