An offline coupling of fire spread models to simulate the 2021 Marshall Fire
Fernando Szasdi-Bardales![https://orcid.org/0000-0002-9643-5919](/media/client/orcid_16x16.png)
![https://orcid.org/0000-0003-3396-7683](/media/client/orcid_16x16.png)
![https://orcid.org/0000-0003-1992-6033](/media/client/orcid_16x16.png)
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Abstract
Existing fire spread models focus exclusively on wildland or urban fire simulation.
This study aims at an offline coupling of two fire spread models to enable a continuous simulation of a wildfire incident transitioning from wildland into wildland–urban interface (WUI) communities, evaluate the effects of wind input on simulation results and study the influence of building types on fire spread patterns.
The selected models are WRF-Fire, a wildland fire behaviour simulation platform, and SWUIFT, a model for fire spread inside the WUI. The 2021 Marshall Fire serves as the case study. A map of the fire’s timeline and location is generated using public information. Three simulation scenarios are analysed to study the effects of wind input resolution and building type on the predicted fire spread and damage.
The most accurate results are obtained using a high-resolution wind input and when incorporating different building types.
The offline coupling of models provides a reliable solution for fire spread simulation. Fire-resistant buildings likely helped limit community fire spread during the Marshall Fire.
The research is a first step toward developing simulation capabilities to predict the spread of wildfires within the wildland, WUI and urban environments.
Keywords: fire, Marshall Fire, modelling, offline coupling, SWUIFT, wildfire simulation, wildland–urban interface, WRF-Fire.
References
Benjamin SG, Weygandt SS, Brown JM, Hu M, Alexander CR, Smirnova TG, Olson JB, James EP, Dowell DC, Grell GA, Lin H, Peckham SE, Smith TL, Moninger WR, Kenyon JS (2016) A North American hourly assimilation and model forecast cycle: the rapid refresh. Monthly Weather Review 144(4), 1669-1694.
| Crossref | Google Scholar |
Benjamin SG, James EP, Szoke EJ, Schlatter PT, Brown JM (2023) The 30 December 2021 Colorado Front Range windstorm and Marshall Fire: evolution of surface and 3D structure, NWP guidance, NWS forecasts, and decision support. Weather and Forecasting 38, 2551-2573.
| Crossref | Google Scholar |
Boulder County (2022a) List of structures damaged or destroyed in the Marshall Fire. Available at https://assets.bouldercounty.gov/wp-content/uploads/2022/01/marshall-fire-damage-assessment-list.pdf [accessed February 2023]
Boulder County (2022b) Marshall Fire operational after-action report. Available at https://assets.bouldercounty.gov/wp-content/uploads/2022/06/marshall-fire-after-action-report.pdf [accessed February 2023]
Brenkert-Smith H, Champ P, Flores N (2012) Trying not to get burned: understanding homeowners’ wildfire risk–mitigation behaviors. Environmental Management 50, 1139-1151.
| Crossref | Google Scholar | PubMed |
Brennan N (2022) Firefighter shares photos, video from Marshall Fire front lines. Available at https://www.9news.com/article/news/local/wildfire/photos-video-marshall-fire-front-lines/73-ede64f54-2ec6-4403-aee3-dbf8100e8c10 [accessed June 2022]
Calkin DE, Cohen JD, Finney MA, Thompson MP (2014) How risk management can prevent future wildfire disasters in the wildland–urban interface. Proceedings of the National Academy of Sciences 111(2), 746-751.
| Crossref | Google Scholar | PubMed |
Chulahwat A, Mahmoud H (2024) The impact of wind characteristics on the spatial distribution of damage to the built environment during wildfire events: the 2022 Marshall Fire. Natural Hazards Review 25(1), 06023003.
| Crossref | Google Scholar |
Clark TL, Jenkins MA, Coen JL, Packham DR (1996a) A coupled atmosphere–fire model: convective feedback on fire-line dynamics. Journal of Applied Meteorology and Climatology 35(6), 875-901.
| Crossref | Google Scholar |
Clark TL, Jenkins MA, Coen JL, Packham DR (1996b) A coupled atmosphere-fire model: role of the convective Froude Number and dynamic fingering at the fireline. International Journal of Wildland Fire 6(4), 177-190.
| Crossref | Google Scholar |
Clifford E (2016) Predicting homeowner wildfire mitigation behaviors in the wildland–urban interface. Doctoral Dissertation, Arizona State University, Tempe, AZ, USA. Available at https://keep-dev.lib.asu.edu/items/155106
Coen JL (2013) Modeling wildland fires: a description of the Coupled Atmosphere–Wildland Fire Environment model (CAWFE). (No. NCAR/TN-500+STR). 10.5065/D6K64G2G
Coen JL, Cameron M, Michalakes J, Patton EG, Riggan PJ, Yedinak KM (2013) WRF-Fire: coupled weather–wildland fire modeling with the weather research and forecasting model. Journal of Applied Meteorology and Climatology 52(1), 16-38.
| Crossref | Google Scholar |
Colorado Division of Fire Prevention and Control (DFPC) (2022) Marshall Fire facilitated learning analysis. Available at https://storymaps.arcgis.com/stories/83af63bd549b4b8ea7d42661531de512 [accessed June 2022]
DeCastro AL, Juliano TW, Kosovic B, Ebrahimian H, Balch JK (2022) A computationally efficient method for updating fuel inputs for wildfire behavior models using sentinel imagery and random forest classification. Remote Sensing 14(6), 1447.
| Crossref | Google Scholar |
Dennison PE, Brewer SC, Arnold JD, Moritz MA (2014) Large wildfire trends in the western United States, 1984–2011. Geophysical Research Letters 41(8), 2928-2933.
| Crossref | Google Scholar |
Federal Emergency Management Agency (FEMA) (2008) Home builder’s guide to construction in wildfire zones. technical fact sheet series, FEMA P-737. Availble at https://www.govinfo.gov/content/pkg/GOVPUB-HS5-PURL-gpo60104/pdf/GOVPUB-HS5-PURL-gpo60104.pdf
Federal Emergency Management Agency (FEMA) (2022) Hazus inventory technical manual, Hazus 6.0. Available at https://www.fema.gov/sites/default/files/documents/fema_hazus-6-inventory-technical-manual.pdf [accessed June 2023]
Finney MA (1998) FARSITE: Fire Area Simulator – model development and evaluation. Research Paper RMRS-RP-4. (USDA Forest Service, Rocky Mountain Research Station: Ogden, UT) 10.2737/RMRS-RP-4
Finney MA, McHugh CW, Grenfell IC, Riley KL, Short KC (2011) A simulation of probabilistic wildfire risk components for the continental United States. Stochastic Environmental Research and Risk Assessment 25(7), 973-1000.
| Crossref | Google Scholar |
Fischer E, Wham B, Dashti S, Javernick-Will A, Liel A, Whelton A, Berty N, Klingaman J, Metz A, Ramos J, Rose H (2022) ‘The 2021 Marshall Fire, Boulder County, Colorado (Version 1.0).’ (GEER Association) 10.18118/G6KT04
Fovell RG, Brewer MJ, Garmong RJ (2022) The December 2021 Marshall Fire: predictability and gust forecasts from operational models. Atmosphere 13(5), 765.
| Crossref | Google Scholar |
Google Maps (2019) Street view images, Boulder County, CO. Available at https://www.google.com/maps [accessed September 2023]
Headwaters Economics (2022) Wildfires destroy thousands of structures each year. Available at https://headwaterseconomics.org/natural-hazards/structures-destroyed-by-wildfire/ [accessed February 2023]
International Code Council (ICC) (2017) ‘2018 International Wildland–Urban Interface Code.’ (Washington, DC, USA) Available at https://codes.iccsafe.org/content/IWUIC2018P3 [accessed June 2023]
International Code Council (ICC) (2019) ‘2019 California Referenced Standards Code. California Code of Regulations, Title 24, Part 12.’ (Washington, DC, USA) Available at https://codes.iccsafe.org/content/CRSC2019P1 [accessed June 2023]
Jiang W, Wang F, Linghang F, Zheng X, Qiao X, Li Z, Meng Q (2021) Modelling of wildland–urban interface fire spread with the heterogeneous cellular automata model. Environmental Modelling & Software 135, 104895.
| Crossref | Google Scholar |
Juliano TW, Lareau N, Frediani ME, Shamsaei K, Eghdami M, Kosiba K, Wurman J, DeCastro A, Kosovic B, Ebrahimian H (2023) Toward a better understanding of wildfire behavior in the wildland–urban interface: a case study of the 2021 Marshall Fire. Geophysical Research Letters 50(10), e2022GL101557.
| Crossref | Google Scholar |
Juliano TW, Szasdi-Bardales F, Lareau NP, Shamsaei K, Kosovic B, Elhami-Khorasani N, James EP, Ebrahimian H (2024) Brief communication: the Lahaina Fire disaster – how models can be used to understand and predict wildfires. Natural Hazards and Earth System Sciences 24(1), 47-52.
| Crossref | Google Scholar |
KUSA-TV (2022) Burned: the story behind the Marshall Fire. Available at https://www.marshallfiremap.com/ [accessed July 2023]
Landscape Fire and Resource Management Planning Tools (LANDFIRE) (2020) ‘13 Fire Behavior Fuel Models Anderson. LANDFIRE 2.0.0.’ (US Department of the Interior, Geological Survey, and US Department of Agriculture) Available at https://www.landfire.gov/viewer/ [accessed November 2022]
Lareau NP, Donohoe A, Roberts M, Ebrahimian H (2022) Tracking wildfires with weather radars. Journal of Geophysical Research: Atmospheres 127(11), e2021JD036158.
| Crossref | Google Scholar |
Lautenberger C (2013) Wildland fire modeling with an Eulerian level set method and automated calibration. Fire Safety Journal 62, 289-298.
| Crossref | Google Scholar |
Linn RR (1997) ‘A transport model for prediction of wildfire behavior’. LA-13334-T. (Los Alamos National Laboratory: Los Alamos, NM, USA) 10.2172/505313
Martin W, Martin I, Kent B (2009) The role of risk perceptions in the risk mitigation process: the case of wildfire in high risk communities. Journal of Environmental Management 91(2), 489-498.
| Crossref | Google Scholar | PubMed |
Masoudvaziri N, Szasdi Bardales F, Keskin O, Sarreshtehdari A, Sun K, Elhami Khorasani N (2021) Streamlined wildland–urban interface fire tracing (SWUIFT): modeling wildfire spread in communities. Environmental Modelling and Software 143, 105097.
| Crossref | Google Scholar |
Masoudvaziri N, Elhami-Khorasani N, Sun K (2023) Toward probabilistic risk assessment of wildland–urban interface communities for wildfires. Fire Technology 59, 1379-1403.
| Crossref | Google Scholar |
Mastorakos E, Gkantonas S, Efstathiou G, Giusti A (2022) A hybrid stochastic Lagrangian–cellular automata framework for modelling fire propagation in inhomogeneous terrains. Proceedings of the Combustion Institute 39(3), 3853-3862.
| Crossref | Google Scholar |
Meldrum J, Champ P, Warziniack T, Brenkert-Smith H, Barth CM, Falk LC (2014) Cost shared wildfire risk mitigation in Log Hill Mesa, Colorado: survey evidence on participation and willingness to pay. International Journal of Wildland Fire 23(4), 567-576.
| Crossref | Google Scholar |
Mell W, Jenkins MA, Gould J, Cheney P (2007) A physics-based approach to modelling grassland fires. International Journal of Wildland Fire 16(1), 1-22.
| Crossref | Google Scholar |
Microsoft (2022) US Building Footprints (2022 release). Available at https://github.com/microsoft/USBuildingFootprints [accessed February 2023]
Moritz MA, Batllori E, Bradstock RA, Malcolm Gill A, Handmer J, Hessburg PF, Leonard J, McCaffrey S, Odion DC, Schoennagel T, Syphard A (2014) Learning to coexist with wildfire. Nature 515, 58-66.
| Crossref | Google Scholar | PubMed |
Munoz-Esparza D, Kosovic B, Jimenez PA, Coen JL (2018) An accurate fire-spread algorithm in the Weather Research and Forecasting Model using the level-set method. Journal of Advances in Modeling Earth Systems 10(4), 908-926.
| Crossref | Google Scholar |
National Fire Protection Association (NFPA) (2017) Standard for reducing structure ignition hazards from wildland fire. NFPA 1144-2018. Available at https://www.nfpa.org/codes-and-standards/1/nfpa-1/4/nfpa-1144
National Weather Service (NWS) (2022) Summary of the Marshall Fire and high wind event on December 30, 2021. Available at https://www.weather.gov/bou/HighWinds12_30_2021 [accessed February 2023]
Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. Research Paper INT-115. (USDA Forest Service, Intermountain Forest and Range Experiment Station: Ogden, UT) Available at https://www.fs.usda.gov/rm/pubs_int/int_rp115.pdf
Shamsaei K, Juliano TW, Roberts M, Ebrahimian H, Kosovic B, Lareau NP, Taciroglu E (2023) Coupled fire–atmosphere simulation of the 2018 Camp Fire using WRF-Fire. International Journal of Wildland Fire 32(2), 195-221.
| Crossref | Google Scholar |
Skamarock WC, Klemp JB (2008) A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. Journal of Computational Physics 227(7), 3465-3485.
| Crossref | Google Scholar |
Skamarock WC, Klemp JB, Dudhia J, Gill DO, Liu Z, Berner J, Wang W, Powers JG, Duda MG, Barker D, Huang X (2021) A Description of the Advanced Research WRF Version 4.3. (NCAR/TN-556+STR) 10.5065/1dfh-6p97
Spyratos V, Bourgeron P, Ghil M (2007) Development at the wildland–urban interface and the mitigation of forest-fire risk. Proceedings of the National Academy of Sciences 104(36), 14272-14276.
| Crossref | Google Scholar | PubMed |
Szasdi-Bardales F, Shamsaei K, Lareau NP, Juliano TW, Kosovic B, Ebrahimian H, Elhami-Khorasani N (2024) Integrating dynamic wildland fire position input with a community fire spread simulation: a case study of the 2018 Camp Fire. Fire Safety Journal 143, 104076.
| Crossref | Google Scholar |
Thomas CM, Sharples JJ, Evans JP (2017) Modelling the dynamic behaviour of junction fires with a coupled atmosphere–fire model. International Journal of Wildland Fire 26(4), 331.
| Crossref | Google Scholar |
Western Regional Climate Center [WRCC] (2021) Sugarloaf Colorado Daily Summary. Available at https://wrcc.dri.edu/cgi-bin/wea_daysum2.pl [accessed February 2023]