A review of wildland fire spread modelling, 1990-present 3: Mathematical analogues and simulation models

In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behvaiour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one dimensional models to two dimensions and then propagate a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical conceit (rather than a physical representation of fire spread) that coincidentally simulates the spread of fire. Other papers in the series review models of an physical or quasi-physical nature and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.Comment: 20 pages + 9 pages references + 1 page figures. Submitted to the International Journal of Wildland Fir

A review of wildland fire spread modelling, 1990-present, 1: Physical and quasi-physical models

In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behaviour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a physical or quasi-physical nature. These models are based on the fundamental chemistry and/or physics of combustion and fire spread. Other papers in the series review models of an empirical or quasi-empirical nature, and mathematical analogues and simulation models. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.Comment: 31 pages + 8 pages references + 2 figures + 5 tables. Submitted to International Journal of Wildland Fir

A wildland fire model with data assimilation

A wildfire model is formulated based on balance equations for energy and fuel, where the fuel loss due to combustion corresponds to the fuel reaction rate. The resulting coupled partial differential equations have coefficients that can be approximated from prior measurements of wildfires. An ensemble Kalman filter technique with regularization is then used to assimilate temperatures measured at selected points into running wildfire simulations. The assimilation technique is able to modify the simulations to track the measurements correctly even if the simulations were started with an erroneous ignition location that is quite far away from the correct one.Comment: 35 pages, 12 figures; minor revision January 2008. Original version available from http://www-math.cudenver.edu/ccm/report

Forest Fire Occurrence and Modeling in Southeastern Australia

Forest fire is one of the major environmental disturbances for the Australian continent. Identification of occurrence patterns of large fires, fire mapping, determination of fire spreading mechanisms, and fire effect modeling are some of the best measures to plan and mitigate fire effects. This chapter describes fire occurrence in New South Wales (Australia), the Australian National Bushfire Model Project (ANBMP), fire propagation modeling methods, the McArthur’s model and current forest fire modeling approaches in the state of New South Wales of Australia. Among the established fire models, PHOENIX Rapidfire predicts fire spread and facilitates loss and damage assessments as the model considers many environmental and social variables. Two fire spread models, SPARK and Amicus, have been developed and facilitated fire spread mapping and modeling in Australia

Fire behaviour simulation in Mediterranean maquis using FARSITE (fire area simulator)

In the last two decades several simulation systems were developed to provide information about temporal and spatial variations of fire spread and behaviour. FARSITE (Fire Area Simulator), one of the most common simulators, is a spatially and temporally explicit fire simulation system. The simulator is based on Rothermel's fire spread model, and describes the fire spread and behaviour as a function of relationships among fuels, topography and weather conditions. The use of FARSITE on areas different from those where the simulator was originally developed requires a local calibration in order to produce reliable results. This is particularly true for the Mediterranean ecosystems, where plant communities are characterized by high specific and structural heterogeneity and complexity, determined by the interaction of sub-arid Mediterranean climate and human factors. Therefore, to perform FARSITE calibration, the choice of the appropriate standard fuel models or the development of specific custom fuel models are required. In addition, the capabilities of FARSITE simulator can be affected by other environmental characteristics, as complex steep terrains with the resulting high spatial and temporal variability of wind speed and direction. In this work, FARSITE was employed to simulate spread and behaviour of four real fires occurred in North Sardinia during 2003, 2004 and 2006 summer seasons. The effect of fuel models, weather conditions and topography on the accuracy of FARSITE simulations was evaluated in order to assess the capabilities of the simulator in accurately forecasting the fire spread and behaviour in areas covered by Mediterranean maquis. A custom fuel model, designed and developed by our working group for maquis, provided realistic values of simulated fire behaviour. Improvements on the accuracy of both fire spread and behaviour were also obtained using raster maps of wind speed and direction. The results confirm that the use of both accurate wind field data and appropriate custom fuel models is crucial to obtain accurate simulations of fire behaviour occurring on Mediterranean vegetation during the drought season, when most wildfires occur

Research progress of forest fires spread trend forecasting in Heilongjiang Province

In order to further grasp the scientific method of forecasting the spreading trend of forest fires in Heilongjiang Province, which is located in Northeast China, the basic concepts of forest fires, a geographical overview of Heilongjiang Province, and an overview of forest fire forecasting are mainly introduced. The calculation and computer simulation of various forest fire spread models are reviewed, and the selected model for forest fires spread in Heilongjiang Province is mainly summarized. The research shows that the Wang Zhengfei-Mao Xianmin model has higher accuracy and is more suitable for the actual situation of Heilongjiang Province. However, few studies over the past three decades have updated the formula. Therefore, this empirical model is mainly analyzed in this paper. The nonlinear least squares method is used to re-fit the wind speed correction coefficient, which gets closer results to the actual values, and the Wang Zhengfei-Mao Xianmin model is rewritten and evaluated for a more precise formula. In addition, a brief overview of the commonly used Rothermel mathematical-physical model and the improved ellipse mathematical model is given, which provides a basis for the improvement of the forest fires spread model in Heilongjiang Province

A High-resolution Large-eddy Simulation Framework for Wildfire Predictions using TensorFlow

As the impact of wildfires has become increasingly more severe over the last decades, there is continued pressure for improvements in our ability to predict wildland fire behavior over a wide range of conditions. One approach towards this goal is through coupled fire/atmosphere modeling tools. While significant progress has been made on advancing their physical fidelity, existing modeling tools have not taken full advantage of emerging programming paradigms and computing architectures to enable high-resolution wildfire simulations. By addressing this gap, this work presents a new wildfire simulation framework that enables landscape-scale wildfire simulations with physical representation of the combustion at affordable computational cost. This is achieved by developing a coupled fire/atmosphere model in the TensorFlow programming paradigm, which enables highly efficient and scalable computations on Tensor Processing Unit (TPU) hardware architecture. To validate this simulation framework and demonstrate its efficiency, simulations of the prescribed fire experiment FireFlux II (Clements et al., 2019) are performed. By considering a parametric study on the mesh resolution, we show that the global quantities such as volumetric heat release and fire-spread rate are insensitive to the horizontal mesh resolution within a range between 0.5 m and 2 m, which is sufficient for predicting fire intermittency and dynamic fire properties associated with fine-scale turbulent structures in the atmospheric boundary layer.Comment: 10 figures, 2 tables, 4559 word

A review of wildland fire spread modelling, 1990-present 2: Empirical and quasi-empirical models

In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behaviour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of an empirical or quasi-empirical nature. These models are based solely on the statistical analysis of experimentally obtained data with or without some physical framework for the basis of the relations. Other papers in the series review models of a physical or quasi-physical nature, and mathematical analogues and simulation models. The main relations of empirical models are that of wind speed and fuel moisture content with rate of forward spread. Comparisons are made of the different functional relationships selected by various authors for these variables.Comment: 22 pages + 7 pages references + 2 pages tables + 2 pages figures. Submitted to International Journal of Wildland Fir