Modification of the Rothermel model parameters – the rate of surface fire spread of Pinus koraiensis needles under no-wind and various slope conditions

Daotong Geng; Guang Yang; Jibin Ning; Ang Li; Zhaoguo Li; Shangjiong Ma; Xinyu Wang; Hongzhou Yu

doi:10.1071/WF23118

RESEARCH ARTICLE (Open Access)

Modification of the Rothermel model parameters – the rate of surface fire spread of Pinus koraiensis needles under no-wind and various slope conditions

Daotong Geng ^A , Guang Yang ^A ^* , Jibin Ning ^A , Ang Li ^B ^* , Zhaoguo Li ^A , Shangjiong Ma ^A , Xinyu Wang ^A and Hongzhou Yu

^A

+ Author Affiliations

- Author Affiliations

^A Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, College of Forestry, Northeast Forestry University, Harbin, Heilongjiang 150040, China.

^B College of Forestry, Inner Mongolia Agricultural University, Hohhot 010019, China.

^* Correspondence to: lx_yg@163.com, fcla@imau.edu.cn

International Journal of Wildland Fire 33, WF23118 https://doi.org/10.1071/WF23118

Submitted: 18 July 2023 Accepted: 19 March 2024 Published: 8 April 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Background

The prediction accuracy for the rate of surface fire spread varies in different regions; thus, increasing the prediction accuracy for local fuel types to reduce the destructive consequences of fire is critically needed.

Aims

The objective of this study is to improve the Rothermel model’s accuracy in predicting the ROS for surface fuel burning in planted forests of Pinus koraiensis in the eastern mountains of north-east China.

Methods

Fuel beds with various fuel loads and moisture content was constructed on a laboratory burning bed, 276 combustion experiments were performed under multiple slope conditions, and the ROS data from the combustion experiments were used to modify the related parameters in the Rothermel model.

Results

The surface fire spread rate in Pinus koraiensis plantations was directly predicted using the Rothermel model but had significant errors. The Rothermel model after modification predicted the following: MRE = 25.09%, MAE = 0.46 m min⁻¹, and R² = 0.80.

Conclusion

The prediction accuracy of the Rothermel model was greatly enhanced through parameter tuning based on in-lab combustion experiments

Implications

This study provides a method for the local application of the Rothermel model in China and helps with forest fire fighting and management in China.

Keywords: fuel loads, fuel moisture, modified parameters, Pinus koraiensis, ROS, Rothermel model, slope, surface fire.

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