Simulation of Rice Stubble’s Arrangement Effect on Fire Intensity

Main Article Content

พงษ์ธร วิจิตรกูล


This article presents a study of the layout of the rice stubble on the severity of the fire from burning rice stubble left after harvest, farmers in the study area. By simulating the progression of the fire on the four themes of the layout of the rice stubble. Data was collected and the terrain is steep elevation from the sea. Information is the fuel characteristics, fuel density. The height of the fuel the specific energy consumption of fuels Climate data are speed wind direction, rainfall, wind and humidity. After the simulated burning the 4 patterns in the layout of the fuel. (1) Making a line of fire barrier about 1.5 meter as a horizontal with a fire spread (2) Making a spot of fire barrier dispersing in a field (3) Making a line of fire barrier about 1.5 meter in the same direction of fire spread and (4) Making a line of fire barrier to divide a field into 3 parts in the same direction of a fire spread. FARSITE was used for 10% of area of fire barrier for 1 unit area to simulate fire intensity with the same variables e.g. topography weather and fuel. It was found that the pattern 1 was the best way to reduce fire intensity and the pattern 4 presented the highest fire intensity.


Article Details

How to Cite
วิจิตรกูลพ. (2018). Simulation of Rice Stubble’s Arrangement Effect on Fire Intensity. Journal of Industrial Technology Ubon Ratchathani Rajabhat University, 8(2), 155-168. Retrieved from
Research Article


[1] Karakate N. A Study on the Future Image of Mass Media in the Role to Promote the Value of Thai Jasmine Rice [Complete report]. Rajamangala University of Technology Thanyaburi. 2011. (in Thai)
[2] Wichitkul P., Attathanakorn N., Tachajapong W. Examination of Factors Affecting Early Burning Fire Spread Rate in Dry Deciduous Dipterocarp Forest. The International Conference on Mechanical Engineering (ME-NETT 26 & TSME-ICoME 2012). Dusit Island Resort. Chiang Rai. 2012. (in Thai)
[3] Rothermel. R.C. A mathematical model for predicting fire spread in wild land fuels. USDA For. Serv. Res. Pap. 1972; INT-115.
[4] Richards G.D. An elliptical growth model of forest fire fronts and its numerical solution. Int. J. Numer. Meth. 1990; Eng. 30: 1163-1179.
[5] Rebecca A. Reed et al., Aboveground net primary production and leaf area index in initial post-fire vegetation communities in Yellowstone National Park. Ecosystem. 1999; 2: 88-94.
[6] Martin E Alexander, Miguel G Cruz. Evaluating a model for predicting active crown fire rate of spread using wildfire observations. Canadian Journal of Forest Research, 2006; 36(11): 3015-3028, 10.1139/x06-174.
[7] H.Aghajani., A. Fallah., S. Fazlollah Emadian. Modelling and analyzing the surface fire behaviour in Hyrcanian forest of Iran. Journal of Forest Science. 60. 2014 (9): 353-362.
[8] Jeremy Maestas et al., Fuel Breaks to Reduce Large Wildfire Impacts in Sagebrush Ecosystems. Technical Note No. 66, USDA – Natural Resources Conservation Service. Idaho; 2016: 114-116.
[9] Phillips, R. J., Waldrop, T. A., Simon, D. M., Assessment of the FARSITE model for predicting fire behavior in the Southern Appalachian Mountains. Proceedings of the 13th biennial Southern Silvicultural Research Conference. Gen. Tech. Rep. SRS-92. Asheville. NC: U.S. Department of Agriculture. Forest Service. Southern Research Station. 2006: 521-525.
[10] The Thai Meteorological Department. An up-to-date information of weather forecast 1 -1 5 March 2016 [Internet]. 2016 [cited 2016 March 30]. Available from: (in Thai)