Abstract
Forest fire spread prediction is a crucial issue to mitigate forest fire effects. Forest fire propagation models require several input parameters describing the conditions where the fire is taking place. However, some parameters, such as wind, present a different value on each point of the terrain due to topography. So, it is necessary to couple a wind field model that evaluates the wind on each terrain point. However, calculating the wind for each point on large maps is a time consuming task that can make the prediction unfeasible. So, it is necessary to parallelize the wind field computation. One approach is to apply a map partitioning technique, so that the wind field is calculated for each map part. The wind field obtained is lightly different from the one obtained with a single global map, and it is necessary to evaluate the effect of such difference on forest fire spread prediction.
This work was supported by Ministerio de Ciencia e Innovación (MICINN - Spain) under contract TIN2011-28689-C02-01.
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References
Artés, T., Cencerrado, A., Cortés, A., Margalef, T.: Relieving the effects of uncertainty in forest fire spread prediction by hybrid mpi-openmp parallel strategies. Procedia Computer Science 18, 2278–2287 (2013)
Cencerrado, A., Cortés, A., Margalef, T.: Response time assessment in forest fire spread simulation: An integrated methodology for efficient exploitation of available prediction time. Environmental Modelling & Software 54, 153–164 (2014)
Chapman, B., Jost, G., Van Der Pas, R.: Using OpenMP: portable shared memory parallel programming, vol. 10. The MIT Press (2007)
Finney, M.A.: FARSITE, Fire Area Simulator–model development and evaluation. Res. Pap. RMRS-RP-4, Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station (1998)
Forthofer, J.M., Shannon, K., Butler, B.W.: Simulating diurnally driven slope winds with windninja. In: 8th Symposium on Fire and Forest Meteorological Society (2009)
Forthofer, J.M., Shannon, K., Butler, B.W.: Initialization of high resolution surface wind simulations using nws gridded data. In: Proceedings of 3rd Fire Behavior and Fuels Conference, October 25-29 (2010)
Gropp, W.: MPICH2: A new start for MPI implementations. In: Kranzlmüller, D., Kacsuk, P., Dongarra, J., Volkert, J. (eds.) PVM/MPI 2002. LNCS, vol. 2474, pp. 7–42. Springer, Heidelberg (2002)
Lopes, A.M.G., Cruz, M.G., Viegas, D.X.: Firestation–an integrated software system for the numerical simulation of fire spread on complex topography. Environmental Modelling & Software 17(3), 269–285 (2002)
William, C., Skamarock, J.B.: Klemp, Jimy Dudhia, David O Gill, Dale M Barker, Wei Wang, and Jordan G Powers. A description of the advanced research wrf version 2. Technical report, DTIC Document (2005)
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Sanjuan, G., Brun, C., Cortés, A., Margalef, T. (2014). Effect of Wind Field Parallelization on Forest Fire Spread Prediction. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8582. Springer, Cham. https://doi.org/10.1007/978-3-319-09147-1_39
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DOI: https://doi.org/10.1007/978-3-319-09147-1_39
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