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http://dx.doi.org/10.5532/KJAFM.2013.15.3.178

Sensitivity Analysis on Ecological Factors Affecting Forest Fire Spreading: Simulation Study  

Song, Hark-Soo (KT Daeduk 2 Research Center)
Lee, Sang-Hee (KT Daeduk 2 Research Center)
Publication Information
Korean Journal of Agricultural and Forest Meteorology / v.15, no.3, 2013 , pp. 178-185 More about this Journal
Abstract
Forest fires are expected to increase in severity and frequency under global climate change and thus better understanding of fire dynamics is critical for mitigation and adaptation. Researchers with different background, such as ecologists, physicists, and mathematical biologists, have developed various simulation models to reproduce forest fire spread dynamics. However, these models have limitations in the fire spreading because of the complicated factors such as fuel types, wind, and moisture. In this study, we suggested a simple model considering the wind effect and two different fuel types. The two fuels correspond to susceptible tree and resistant tree with different probabilities of transferring fire. The trees were randomly distributed in simulation space with a density ranging from 0.0 (low) to 1.0 (high). The susceptible tree had higher value of the probability than the resistant tree. Based on the number of burnt trees, we then carried out the sensitivity analysis to quantify how the forest fire patterns are affected by wind and tree density. The statistical analysis showed that the total tree density had greatest effect on the forest fire spreading and wind had the next greatest effect. The density of the susceptible tree was relatively lower factor affecting the forest fire. We believe that our model can be a useful tool to explore forest fire spreading patterns.
Keywords
Forest fire model; Fire spreading dynamics; Forest ecosystem; Sensitivity analysis;
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1 Malamud, B. D., G. Morein, and D. L. Turcotte, 1998: Forest fires: an example of self-organized critical behavior. Science 281(5384), 1840-1842. doi: 10.1126/science. 281.5384.1840   DOI   ScienceOn
2 Malamud, B. D., G. Morein, and D. L. Turcotte, 2005: Log-periodic behavior in a forest-fire model. Nonlinear Processes in Geophysics 12, 575-585. doi: 10.5194/npg-12-575-2005   DOI
3 Matsinos, Y. G., and A. Y. Troumbis, 2002: Modelling spatiotemporal dynamics of a community of annual plant species: implications for management of biodiversity. Ecological Modelling 149(2), 71-83.   DOI   ScienceOn
4 McCoy, V. M., and C. R. Burn, 2005: Potential alteration by climate change of the forest-fire regime in the boreal forest of central Yukon Territory. Arctic 58(3), 276-285.
5 Ntaimo, L., B. P. Zeigler, M. J. Vasconcelos, and B. Khargharia, 2004: Forest fire spread and suppression in DEVS. Simulation 80(10), 479-500.   DOI
6 Piñol, J., J. Terradas, and F. Lloret, 1998: Climate warming, wildfire hazard, and wildfire occurrence in coastal eastern spain. Climatic Change 38(3), 345-357.   DOI   ScienceOn
7 Pitts, W. M., 1991: Wind effects on fires. Progress in Energy and Combustion Science 17(2), 83-134.   DOI   ScienceOn
8 Ratz, A., 1995: Long-term spatial patterns created by fire: a model oriented towards boreal forests. International Journal of Wildland Fire 5(1), 25-34. doi: 10.1071/WF9950025   DOI
9 Vasconcelos, M. J., and D. P. Guertin, 1992: Firemap - simulation of fire growth with a geographic information system. International Journal Wildland Fire 2(2), 87-96. doi: 10.1071/WF9920087   DOI
10 Diaz-Delgado, R., F. Lloret, X. Pons, and J. Terradas, 2002: Satellite evidence of decreasing resilience in mediterranean plant communities after recurrent wildfires. Ecology 83(8), 2293-2303.   DOI
11 Grievank, A., and A. Walther, 2008: Evaluating derivatives: Principles and techniques of algorithmic differentiation (2nd ed.). SIAM publisher. Philadelphia. USA.
12 Eastman, J. R., 2003: IDRISI Kilimanjaro Guide to GIS and Image Processing. Clark Labs Clark University, 13-19.
13 Encinas, A. H., L. H. Encinas, S. H. White, A. M. del Rey, and G. R. Sanchez, 2007: Simulation of forest fire fronts using cellular automata. Advances in Engineering Software 38(6), 372-378.   DOI   ScienceOn
14 Feunekes, U., 1991: Error analysis in fire simulation models. Master of Science Thesis, University of New Brunswick, Canada.
15 Flannigan, M. D., B. J. Stocks, and B. M. Wotton, 2000: Climate change and forest fires. Science of the Total Environment 262(3), 221-229.   DOI   ScienceOn
16 Karafyllidis, I., A. Thanailakis, 1997: A model for predicting forest fire spreading using cellular automata. Ecological Modelling 99(1), 87-97.   DOI   ScienceOn
17 Grassberger, P., 2002: Critical behavior of the Drossel-Schwabl forest fire model. New Journal of Physics 4(17), 1-15. doi: 10.1088/1367-2630/4/1/317   DOI   ScienceOn
18 Halada, L., and P. Weisenpacher, 2005: Principles of forest fire spread models and their simulation. Journal of the Applied Mathematics, Statistics and Informatics 1(1), 3-13.
19 Hargrove, W. W., R. H. Gardner, M. G. Turner, W. H. Romme, and D. G. Despain, 2000: Simulating fire patterns in heterogeneous landscapes. Ecological Modelling 135(2-3), 243-263.   DOI   ScienceOn
20 Loibl, W., and T. Toetzer, 2003: Modeling growth and densification processes in suburban regions-simulation of landscape transition with spatial agents. Ecological Modelling & Software 18(6), 553-563.   DOI   ScienceOn
21 Ball, G. L., and D. P. Guertin, 1992: Improved fire growth modeling. International Journal Wildland Fire 2(2), 47-54. doi: 10.1071/WF9920047   DOI
22 Babak, P., A. Bourlioux, and T. Hillen, 2009: The effect of wind on the propagation of an idealized forest fire. SIAM Journal of Applied Mathematics 70(4), 1364-1388.   DOI   ScienceOn
23 Cacuci, D. G., M. Ionescu-Bujor, and M. Navon, 2005: Sensitivity and Uncertainty Analysis, Volume II: Applications to Large-Scale Systems, Chapman & Hall/CRC Press. Boca Raton.
24 Beer, T., 1991: Bushfire rate-of-spread forecasting: Deterministic and statistical approaches to fire modeling. Journal of Forecasting 10(3), 301-317. doi: 10.1002/for.3980100306   DOI
25 Berjak, S. G., and J. W. Hearne, 2002: An improved cellular automaton model for simulating fire in a spatially heterogeneous Savanna system. Ecological Modelling 148(2), 133-151.   DOI   ScienceOn
26 Boychuk, D., W. J. Braun, R. J. Kulperger, Z. L. Krougly, and D. A. Stanford, 2009: A stochastic forest fire growth model. Environmental and Ecological Statistics 16(2), 133-151. doi: 10.1007/s10651-007-0079-z   DOI
27 Clark, T. L., M. A. Jenkins, J. Coen, and D. Packham, 1996: A coupled atmospheric fire model: convective feedback on fire-line dynamics. Journal of Applied Meteorology 35(6), 875-901.   DOI   ScienceOn