Research on a Forest Fire Spread Simulation Driven by the Wind Field in Complex Terrain

Authors: Ying Shang, Chencheng Wang

Abstract:

The wind field is the main driving factor for the spread of forest fires. For the simulation results of forest fire spread to be more accurate, it is necessary to obtain more detailed wind field data. Therefore, this paper studied the mountainous fine wind field simulation method coupled with WRF (Weather Research and Forecasting Model) and CFD (Computational Fluid Dynamics) to realize the numerical simulation of the wind field in a mountainous area with a scale of 30 m and a small measurement error. Local topographical changes have an important impact on the wind field. Based on the Rothermel fire spread model, a forest fire in Idaho in the western United States was simulated. The historical data proved that the simulation results had a good accuracy. They showed that the fire spread rate will decrease rapidly with time and then reach a steady state. After reaching a steady state, the fire spread growth area will not only be affected by the slope, but will also show a significant quadratic linear positive correlation with the wind speed change.

Keywords: Wind field, numerical simulation, forest fire spread, fire behavior model, complex terrain.

References:

[1] Guo, T.; Zhou, Y. Forest fire and climate change. For. Fire Prev. 2015, 3, 34–37. (In Chinese)
[2] Zhou, S. R.; He, C.; Chen, F.; Shu, L. F. Evaluation and analysis of forest fire hazards in China. For. Fire Prev. 2018, 2, 33–36. (In Chinese)
[3] Zhu, J.J.; Zhou R.L.; Gao, J. J.; Long, T. T.; Shi, S. J.; Xu, B. D. Influence of slope on forest fire spread. J. Agric. Catastrophol. 2012, 2, 80–83. (In Chinese)
[4] Hu, R.; Zhu, H. Forest fire occurrence factors and preventive technical measures. Anhui Agric. Sci. Bull. 2013, 19, 113–114. (In Chinese)
[5] Zhang, S.; Zhu C.; Chen Z. Research on forest fire meteorological environmental elements and large forest fires. J. Nat. Disasters 2000, 2, 111–117. (In Chinese)
[6] Li, L. Research on the Relationship between Forest Fires and Meteorological Factors in Yunnan Province; Beijing Forestry University: Beijing, China, 2010. (In Chinese)
[7] Gemma, S.; Carlos, B.; Tomàs, M.; Cortés, A. Wind Field Uncertainty in Forest Fire Propagation Prediction. Procedia Comput. Sci. 2014, 29, 1535–1545.
[8] Li, R. The Research on Influence of Wind for Fire Spread Real-time Changes. Nat. Sci. J. Harbin Norm. Univ. 2011, 27, 30–33.
[9] Takanori, U.; Yuji, O. Micro-siting technique for wind turbine generators by using large-eddy simulation. J. Wind. Eng. Ind. Aerodyn. 2008, 96, 2121–2138.
[10] Griffiths, A. D.; Middleton, J. H. Simulations of separated flow over two-dimensional hills. J. Wind. Eng. Ind. Aerodyn. 2009, 98, 155–160.
[11] Zhang, J.; Cheng, X. Numerical Simulation of Wind Field in Complex Terrain based on CFD Downscaling. Plateau Meteorol. 2020, 39, 172–184.
[12] Chen, X. Numerical Simulation Study of Wind Load on Complex Mountainous Wind Field and Angle Steel Transmission Tower; Hefei University of Technology: Hefei, China, 2017.
[13] Pan, T. Simulation of Atmospheric Boundary Layer Wind Field Based on OpenFOAM; Chongqing University: Chongqing, China, 2015.
[14] Frandsen, W.H.; Rothermel, R.C. Measuring the Energy-Release Rate of a Spreading Fire; Elsevier: Amsterdam, The Netherlands, 1972; Volume 19.
[15] Butler, B.W.; Wagenbrenner, N.S.; Forthofer, J.M.; Lamb, B.K.; Shannon, K.S.; Finn, D.; Eckman, R.M.; Clawson, K.; Bradshaw, L.; Sopko, P.; Beard, S.; et al. High-resolution observations of the near-surface wind field over an isolated mountain and in a steep river canyon. Atmos. Chem. Phys. 2015, 15, 3785–3801.
[16] Prieto-Herráez, D.; Frías-Paredes, L.; Cascón, J.M.; Lagüela-López, S.; Gastón-Romeo, M.; Asensio-Sevilla, M.I.; Martín-Nieto, I.; Fernandes-Correia, P.M.; Laiz-Alonso, P.; Carrasco-Díaz, O.F.; et al. Local wind speed forecasting based on WRF-HDWind coupling. Atmos. Res. 2020, 248, 105219.
[17] Zhao, L., Liu, P., Zhou, Y.; Shi, J.; Tang, M. Wind field interpolation over complex terrain and its application in the simulation of forest fire spreading. J. Beijing For. Univ. 2010, 32, 12–16.
[18] Hong, S.; Lim, J. The WRF Single-Moment 6-Class Microphysics Scheme (WSM6). Asia-Pac. J. Atmos. Sci. 2006, 42,129–151.
[19] Rolf-Erik, K.; Niklas, S. Validation of uncertainty reduction by using multiple transfer locations for WRF–CFD coupling in numerical wind energy assessments. Wind. Energy Sci. 2020, 5,997–1005.
[20] Yang, Y.; Tan, J. C.; Jin, B. C.; Liu, M. G. Multi-Scale Simulation on the Wind Field for Complex Terrain Based on Coupled WRF and CFD Techniques. J. South China Univ. Technol. 2021, 49, 65–73, 83.
[21] Zachary, J.L.; Andrea, B. A 14,000-year record of fire, climate, and vegetation from the Bear River Range, southeast Idaho, USA. Holocene 2016, 26. https://doi.org/10.1177/0959683615622545.
[22] Cathy, W.; Christy, E.B.; Matias, C.F.; Gage, J. Holocene vegetation, fire and climate history of the Sawtooth Range, central Idaho, USA. Quat. Res. 2011, 75, 114–124.
[23] Natalie, S.W.; Jason, M.F.; Wesley, G.P.; Butler, B. Development and Evaluation of a Reynolds-Averaged Navier–Stokes Solver in Wind Ninja for Operational Wildland Fire Applications. Atmosphere 2019, 10, 672.
[24] Li, C. CFD Simulation Study of Turbulent Wind Field near the Ground; Harbin Institute of Technology: Harbin, China, 2010.
[25] Michal, F.; Július, P. Existence of solution of a forest fire spread model. Appl. Math. Lett. 2018, 83, 227–231.
[26] Zhu, L. Forest fire simulation comparison based on Wang Zhengfei model and Rothermel model. Agric. Sci.-Technol. Inf. 2019, 3, 85–88.
[27] Yang, S.; Li, N. Advances in Forest Fire Spread Models. Gansu Sci. Technol. 2021, 37, 45–47.