Rothermel SFIRE

Workflow information

  • Documentation page:

  • Version: 1.0

  • Date of record creation: 2024-11-24

  • Date of upload to firebench: 2024-11-24

  • Version/tag/commit firebench: 0.3.0a1

Configuration

  • Rate of spread model: Rothermel using firebench.ros_models.Rothermel_SFIRE implementation.

  • Input dataset: firebench/data/ros_model_validation/Anderson_2015, Table A1

  • Complementary fuel data from Scott and Burgan 40.

  • If fuel data is missing, use firebench.tools.find_closest_fuel_class_by_properties to retrieve the closest fuel category using total fuel load and fuel height with default weights.

  • Use Baughman_generalized_wind_reduction_factor_unsheltered to compute wind reduction factor considering that the input wind height is above vegetation.

Specific inputs

Some fuel properties are considered as constant:

  • fuel_density: 32 lb ft-3

  • fuel_chaparral_flag: 0 [-]

  • fuel_mineral_content_total: 0.0555 [-]

  • fuel_mineral_content_effective: 0.01 [-]

Results

Fig.1 shows that Rothermel_SFIRE is over predicting the rate fo spread in most cases.

blockdiagram

Fig. 1 : Comparison of expected and computed rate of spread for Anderson 2015 dataset.

Data

  • 01_generate_data.py: 4ca260cf49fec8d05b61043017cdaf63d472e1705d09c25493e49de1b2577d0a

  • 02_plot_data.py: b9804b1d5097942017552992e6eedaa44dff1ea96cae3955e5d708e5a6d05ad9

  • 03_create_record.py: df451fa016231e232db32602f0f3e2668be9a235c648db5729239194471e982a

  • firebench.log: 4206228406a4c0fe4fdf329eea1c81f104cdbfe2ce7ed1a057b84fc1bc55c452

  • output_data.h5: 8aaff1cde3f1af1cde427e179ec9cd16b97aa039156a1faa1a1b488583ee9b1d

  • anderson_2015_validation.png: da54b344f9cf71efb97cb06fc9444cacb12fc0bec8f66c31b49c13426c6ba803