DOI QR코드

DOI QR Code

A Simulation Model for the Study on the Forest Fire Pattern

산불확산패턴 연구를 위한 시뮬레이션 모델

  • 송학수 (국가수리과학 연구소 융복합수리과학부) ;
  • 전원주 (국가수리과학 연구소 융복합수리과학부) ;
  • 이상희 (국가수리과학 연구소 융복합수리과학부)
  • Received : 2012.12.20
  • Accepted : 2013.06.21
  • Published : 2013.06.30

Abstract

Because forest fires are predicted to increase in severity and frequency under global climate change with important environmental implications, an understanding of fire dynamics is critical for mitigation of these negative effects. For the reason, researchers with different background, such as ecologists, physicists, and mathematical biologists, have developed the simulation models to mimic the forest fire spread patterns. In this study, we suggested a novel model considering the wind effect. Our theoretical forest was comprised of two different tree species with varying probabilities of transferring fire that were randomly distributed in space at densities ranging from 0.0 (low) to 1.0 (high). We then studied the distributional patterns of burnt trees using a two-dimensional stochastic cellular automata model with minimized local rules. We investigated the time, T, that the number of burnt trees reaches 25% of the whole trees for different values of the initial tree density, fire transition probability, and the degree of wind strength. Simulation results showed that the values of T decreased with the increase of tree density, and the wind effect decreased in the case of too high or low tree density. We believe that our model can be a useful tool to explore forest fire spreading patterns.

최근 지구 온난화 현상으로 이상기후가 세계 곳곳 에서 발생하고 있으며, 이는 빈번한 산불 발생 및 산불의 대형화에 많은 기여를 하고 있다는 것이 보고되고 있다. 산불은 재산피해, 인명피해 뿐만 아니라 특히, 생태계 파괴를 촉진시키는 매우 심각한 요인 중의 하나이다. 산불로 인한 생태계 파괴 문제를 해결하기 위한 방안으로, 다양한 산불확산 및 패턴 수리모델이 개발되어져 왔다. 본 연구에서는, 바람 요인이 고려된 산불패턴을 시뮬레이션 할 수 있는 수리 모델을 제안하였다. 모델은 격자기반위에서 구성되었으며 셀룰라오토마타 방법을 사용하였다. 모델에서, 숲은 불이 쉽게 옮겨 붙는 나무와 그렇지 않은 나무 두 종류로 구성되었다. 산불이 확산되는 과정에서 연소된 나무의 개수가 전체 시뮬레이션 격자개수의 25% (= 10,000) 되는 시점(T)을 세 개의 독립변수인, 전체 나무밀도, 불 전이 확률이 큰 나무 밀도, 그리고 바람의 세기에 대해 어떤 영향을 받는지를 조사하였다. 나무 밀도가 커질수록, T의 값은 줄어들었고, 바람의 세기가 커질수록 T의 값이 줄어들었다. 나무밀도가 너무 크거나 작은 경우, 바람의 효과가 감소하였다. 본 연구에서, 제안한 산불확산모델은 실제 산불 문제에 적용되어 효과적 대응방안 마련에 많은 도움이 될 것으로 예상된다.

Keywords

References

  1. Malamud BD, Morein G, Turcotte DL., "Forest-fires: an example of self-organized critical behavior," Science. Vol. 281, pp. 1840-1842, 1998. https://doi.org/10.1126/science.281.5384.1840
  2. Ratz A., "Long-term spatial patterns created by fire: a model oriented towards boreal forests," International Journal of Wildland Fire. Vol. 5, pp. 25-34, 1995. https://doi.org/10.1071/WF9950025
  3. Diaz DR, Lloret F, Pons X, Terradas J., "Satelite evidence of decreasing resilience in Mediterranean plant communities after recurrent wildfires," Ecol. Vol. 83, pp. 2293-2303, 2002. https://doi.org/10.1890/0012-9658(2002)083[2293:SEODRI]2.0.CO;2
  4. Pinol J, Terradas J, and Lloret F., "Climate Warming, Wildfire Hazard, and Wildfire Occurrence in Coastal Eastern Spain," Climatic Change. Vol. 38, pp. 345-357, 1998. https://doi.org/10.1023/A:1005316632105
  5. Flannigan MD, Stocks BJ, Wotton BM., "Climate change and forest fires," Science of the Total Environment. Vol. 262, pp. 221-230, 2000. https://doi.org/10.1016/S0048-9697(00)00524-6
  6. McCoy VM, and Burn CR., "Potential alteration by climate change of the forest fire regime in the boreal forest of central Yukon Territory," Arctic. Vol. 58, pp. 276-285, 2005.
  7. Clark TL, Jenkins MA, Coen J and David P., "A Coupled Atmospheric Fire Model: Convective Feedback on Fire Line Dynamics," Journal of Applied Meteorology. Vol. 35, pp. 875-901, 1996. https://doi.org/10.1175/1520-0450(1996)035<0875:ACAMCF>2.0.CO;2
  8. Burgan RE, and Rothermel RC., "fire behavior prediction and fuel modeling system FUEL subsystem," General Technical Report INT-167. pp. 126, 1984.
  9. Ioannis K, and Adonios T., "A model for predictiong forest fire spreading using cellular automata," Ecological Modelling Vol. 99, pp. 87-97, 1997. https://doi.org/10.1016/S0304-3800(96)01942-4
  10. Hargrove WW, Gardner RH, Turner MG, Romme WH, Despain DG., "Simulating fire patterns in heterogencous landscapes," Ecological Modelling. Vol. 135, pp. 243-263, 2000. https://doi.org/10.1016/S0304-3800(00)00368-9
  11. Pitts WM, "Wind Effects on Fires" Progress in Energy and Combustion Science. Vol. 17, pp. 83-134, 1991. https://doi.org/10.1016/0360-1285(91)90017-H
  12. Beer T., "Bushfire rate-of-spread forecasting: Deterministic and statistical approaches to fire modelling," Journal of Forecasting. Vol. 10, pp. 301, 1991. https://doi.org/10.1002/for.3980100306
  13. Halada L, Weisenpacher P., "Principles of forest fire spread models and their simulation", Journal of the Applied Mathematics, Statistics and Informatics. Vol. 1, pp. 3-13, 2005.
  14. Boychuk D, Braun WJ, Kulperger RJ, Krougly ZL, Stanford DA., "A stochastic forest fire growth model", Environmental and Ecological Statistics. Vol. 16, pp. 133-151, 2009. https://doi.org/10.1007/s10651-007-0079-z
  15. Ball GL and Guertin DP., "Improved re growth modelling", International Journal of Wildland Fire. Vol. 2, pp. 47-54, 1992. https://doi.org/10.1071/WF9920047
  16. Vasconcelos MJ, Geurtin GP., "Firemap simulation of fire growth with a geographic information system", International Journal of Wildland Fire. Vol. 2, pp. 87-96, 1992. https://doi.org/10.1071/WF9920087
  17. Feunekes U., "Error analysis in fire simulation models", MS. Thesis, University of New Brunswick, Fredericton, NB, 1991.
  18. Eastman JR., "guide to GIS and image processing", Clark Lab, Clark University, Worcestar, MA, USA. Vol. 2, 1999.
  19. Berjak SG, Hearne JW., "An improved cellular automaton model for simulating fire in a spatially heterogeneous Savanna system", Ecological Modelling. Vol. 148, pp. 133-151, 2002. https://doi.org/10.1016/S0304-3800(01)00423-9
  20. Matsinos YG, Troumbis AY., "Modelling spatiotemporal dynamics of a community of annual plant species: implications for management of biodiversity",Ecological Modelling. Vol. 149, pp 71. 2002. https://doi.org/10.1016/S0304-3800(01)00515-4
  21. Loibl W, Toetzer T, "Modeling growth and densification processes in suburban regions-simulation of landscape transition with spatial agents", Environmental Modelling and Software. Vol. 18, pp. 553-563, 2003. https://doi.org/10.1016/S1364-8152(03)00030-6
  22. Encinas AH, Encinas LH, White SH, del Rey AM, Sanchez GR., "Simulation of forest fire fronts using cellular automata", Advances in Engineering Software. Vol. 38, pp. 372-378, 2007. https://doi.org/10.1016/j.advengsoft.2006.09.002

Cited by

  1. Effects of Geological Structure and Tree Density on the Forest Fire Patterns vol.16, pp.4, 2014, https://doi.org/10.5532/KJAFM.2014.16.4.259