Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE (Open Access)

KAPAS II: simulation of peatland wildfires with daily variations of peat moisture content

Dwi M. J. Purnomo A , Sebastian Apers https://orcid.org/0000-0002-5566-4950 B , Michel Bechtold https://orcid.org/0000-0002-8042-9792 B , Parwati Sofan https://orcid.org/0000-0001-8115-7664 C and Guillermo Rein https://orcid.org/0000-0001-7207-2685 A *
+ Author Affiliations
- Author Affiliations

A Department of Mechanical Engineering, Leverhulme Centre for Wildfires, Environment and Society, Imperial College London, London, SW7 2AZ, UK.

B Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium.

C Research Center for Remote Sensing, National Research and Innovation Agency of Indonesia (BRIN), Jakarta, Indonesia.

* Correspondence to: g.rein@imperial.ac.uk

International Journal of Wildland Fire 32(6) 823-835 https://doi.org/10.1071/WF22109
Submitted: 29 June 2022  Accepted: 10 March 2023   Published: 21 April 2023

© 2023 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 4.0 International License (CC BY).

Abstract

Background: Peatland wildfires involve flaming vegetation and smouldering peat. The smouldering behaviour strongly depends on peat moisture, which can change significantly and quickly due to weather or human activities.

Aims: We simulated wildfire in peatlands at the field scale and, for the first time, included daily variations of peat moisture.

Methods: We developed KAPAS II, a cellular automaton that includes flaming and smouldering, and coupled it with PEATCLSM (Catchment Land Surface Model) for peatland hydrology.

Key results: Compared with the satellite observations over 90 days of a 2018 wildfire in Borneo, KAPAS II predictions provide good agreement for burn scars (79% accuracy) and for the number of smouldering hotspots (85% accuracy). For the same burn scar, the model predicts that 54 ha of peat would smoulder when considering daily moisture variations, but only 12 ha if moisture was constant. Simulations at the same Borneo location, but in different years from 2000 to 2019, show the importance of seasons and climate events like El Niño.

Conclusion: Temporal variations in peat moisture, which are strongly influenced by weather and climate, are important to predict the behaviour and severity of peatland wildfires.

Implications: This model improves our understanding of wildfire behaviour in peatlands and can contribute to its mitigation.

Keywords: cellular automaton, fire, KAPAS, modelling, moisture, peat, smouldering, soil, wildfire.


References

Alexander ME (1985) Estimating the length-to-breadth ratio of elliptical forest fire patterns. In ‘8th Conference on Fire and Forest Meteorology’, Detroit, MI. pp. 287–304. (Society of American Foresters: Detroit, MI)

Alexandridis A, Vakalis D, Siettos CI, Bafas G V (2008) A cellular automata model for forest fire spread prediction: The case of the wildfire that swept through Spetses Island in 1990. Applied Mathematics and Computation 204, 191–201.
A cellular automata model for forest fire spread prediction: The case of the wildfire that swept through Spetses Island in 1990.Crossref | GoogleScholarGoogle Scholar |

Alexandridis A, Russo L, Vakalis D, Bafas G V, Siettos CI (2011) Wildland fire spread modelling using cellular automata: Evolution in large-scale spatially heterogeneous environments under fire suppression tactics. International Journal of Wildland Fire 20, 633–647.
Wildland fire spread modelling using cellular automata: Evolution in large-scale spatially heterogeneous environments under fire suppression tactics.Crossref | GoogleScholarGoogle Scholar |

Apers S, De Lannoy GJM, Baird AJ, Cobb AR, Dargie GC, del Aguila Pasquel J, Gruber A, Hastie A, Hidayat H, Hirano T, Hoyt AM, Jovani‐Sancho AJ, Katimon A, Kurnain A, Koster RD, Lampela M, Mahanama SPP, Melling L, Page SE, Reichle RH, Taufik M, Vanderborght J, Bechtold M (2022) Tropical Peatland Hydrology Simulated With a Global Land Surface Model. Journal Of Advances In Modeling Earth Systems 14, e2021MS002784
Tropical Peatland Hydrology Simulated With a Global Land Surface Model.Crossref | GoogleScholarGoogle Scholar |

Bechtold M, De Lannoy GJM, Koster RD, Reichle RH, Mahanama SP, Bleuten W, Bourgault MA, Brümmer C, Burdun I, Desai AR, Devito K, Grünwald T, Grygoruk M, Humphreys ER, Klatt J, Kurbatova J, Lohila A, Munir TM, Nilsson MB, Price JS, Röhl M, Schneider A, Tiemeyer B (2019) PEAT-CLSM: A Specific Treatment of Peatland Hydrology in the NASA Catchment Land Surface Model. Journal of Advances in Modeling Earth Systems 11, 2130–2162.
PEAT-CLSM: A Specific Treatment of Peatland Hydrology in the NASA Catchment Land Surface Model.Crossref | GoogleScholarGoogle Scholar |

Bechtold M, De Lannoy GJM, Reichle RH, Roose D, Balliston N, Burdun I, Devito K, Kurbatova J, Strack M, Zarov EA (2020) Improved groundwater table and L-band brightness temperature estimates for Northern Hemisphere peatlands using new model physics and SMOS observations in a global data assimilation framework. Remote Sensing of Environment 246, 111805
Improved groundwater table and L-band brightness temperature estimates for Northern Hemisphere peatlands using new model physics and SMOS observations in a global data assimilation framework.Crossref | GoogleScholarGoogle Scholar |

Belcher CM, Yearsley JM, Hadden RM, McElwain JC, Rein G (2010) Baseline intrinsic flammability of Earth’s ecosystems estimated from paleoatmospheric oxygen over the past 350 million years. Proceedings of the National Academy of Sciences 107, 22448–22453.
Baseline intrinsic flammability of Earth’s ecosystems estimated from paleoatmospheric oxygen over the past 350 million years.Crossref | GoogleScholarGoogle Scholar |

BMKG (2018) Data Online - Pusat Database. Available at https://dataonline.bmkg.go.id/data_iklim

Camps-Valls G, Campos-Taberner M, Moreno-Martínez Á, Walther S, Duveiller G, Cescatti A, Mahecha MD, Muñoz-Marí J, García-Haro FJ, Guanter L, Jung M, Gamon JA, Reichstein M, Running SW (2021) A unified vegetation index for quantifying the terrestrial biosphere. Science Advances 7, eabc7447
A unified vegetation index for quantifying the terrestrial biosphere.Crossref | GoogleScholarGoogle Scholar |

Christensen EG, Fernandez-Anez N, Rein G (2020) Influence of soil conditions on the multidimensional spread of smouldering combustion in shallow layers. Combustion and Flame 214, 361–370.
Influence of soil conditions on the multidimensional spread of smouldering combustion in shallow layers.Crossref | GoogleScholarGoogle Scholar |

Collin A, Bernardin D, Séro-Guillaume O (2011) A physical-based cellular automaton model for forest-fire propagation. Combustion Science and Technology 183, 347–369.
A physical-based cellular automaton model for forest-fire propagation.Crossref | GoogleScholarGoogle Scholar |

Copernicus (2022) Sentinel data, processed by the European Space Agency. Available at https://apps.sentinel-hub.com/eo-browser/?zoom=12&lat=-3.07853&lng=113.98528&themeId=DEFAULT-THEME&visualizationUrl=https%3A%2F%2Fservices.sentinel-hub.com%2Fogc%2Fwms%2Fbd86bcc0-f318-402b-a145-015f85b9427e&datasetId=S2L2A&fromTime=2018-09-28T00%3A00%3A00.000Z&toTime=2018-09-28T23%3A59%3A59.999Z&layerId=4-FALSE-COLOR-URBAN&demSource3D=%22MAPZEN%22

Dadap N (2020) Drainage Canals in Southeast Asian Peatland, Index Map. Stanford Digital Repository. Available at https://earthworks.stanford.edu/catalog/stanford-zy089tj2215

Favier C (2004) Percolation model of fire dynamic. Physics Letters A 330, 396–401.
Percolation model of fire dynamic.Crossref | GoogleScholarGoogle Scholar |

Fernandez-Anez N, Christensen K, Frette V, Rein G (2019) Simulation of fingering behavior in smoldering combustion using a cellular automaton. Physical Review E 99, 023314
Simulation of fingering behavior in smoldering combustion using a cellular automaton.Crossref | GoogleScholarGoogle Scholar |

Ferraz A, Saatchi S, Xu L, Hagen S, Chave J, Yu Y, Meyer V, Garcia M, Silva C, Roswintiarti O, Samboko A, Sist P, Walker S, Pearson T, Wijaya A, Sullivan F, Rutishauser E, Hoekman D, Ganguly S (2019) ‘Aboveground Biomass, Landcover, and Degradation, Kalimantan Forests, Indonesia, 2014.’ (Oak Ridge National Laboratory Distributed Active Archive Center: Oak Ridge, TN, USA)
| Crossref |

Finney MA (1998) FARSITE: Fire Area Simulator – Model Development and Evaluation. (USDA Forest Service: MT)

Frandsen WH (1997) Ignition probability of organic soils. Canadian Journal of Forest Research 27, 1471–1477.
Ignition probability of organic soils.Crossref | GoogleScholarGoogle Scholar |

Goldstein JE, Graham L, Ansori S, Vetrita Y, Thomas A, Applegate G, Vayda AP, Saharjo BH, Cochrane MA (2020) Beyond slash-and-burn: The roles of human activities, altered hydrology and fuels in peat fires in Central Kalimantan, Indonesia. Singapore Journal of Tropical Geography 41, 190–208.
Beyond slash-and-burn: The roles of human activities, altered hydrology and fuels in peat fires in Central Kalimantan, Indonesia.Crossref | GoogleScholarGoogle Scholar |

Hu Y, Fernandez-Anez N, Smith TEL, Rein G (2018) Review of emissions from smouldering peat fires and their contribution to regional haze episodes. International Journal of Wildland Fire 27, 293–312.
Review of emissions from smouldering peat fires and their contribution to regional haze episodes.Crossref | GoogleScholarGoogle Scholar |

Huang X, Rein G (2015) Computational study of critical moisture and depth of burn in peat fires. International Journal of Wildland Fire 24, 798–808.
Computational study of critical moisture and depth of burn in peat fires.Crossref | GoogleScholarGoogle Scholar |

Huang X, Rein G (2017) Downward spread of smouldering peat fire: The role of moisture, density and oxygen supply. International Journal of Wildland Fire 26, 907–918.
Downward spread of smouldering peat fire: The role of moisture, density and oxygen supply.Crossref | GoogleScholarGoogle Scholar |

Huang X, Restuccia F, Gramola M, Rein G (2016) Experimental study of the formation and collapse of an overhang in the lateral spread of smouldering peat fires. Combustion and Flame 168, 393–402.
Experimental study of the formation and collapse of an overhang in the lateral spread of smouldering peat fires.Crossref | GoogleScholarGoogle Scholar |

Huijnen V, Wooster MJ, Kaiser JW, Gaveau DLA, Flemming J, Parrington M, Inness A, Murdiyarso D, Main B, Van Weele M (2016) Fire carbon emissions over maritime southeast Asia in 2015 largest since 1997. Scientific Reports 6, 26886
Fire carbon emissions over maritime southeast Asia in 2015 largest since 1997.Crossref | GoogleScholarGoogle Scholar |

Islami N, Irianti M, Azhar , Nor M, Fakhrudin (2018) Geophysical survey for groundwater potential investigation in peat land area, Riau, Indonesia. IOP Conference Series: Earth and Environmental Science 144, 012001
Geophysical survey for groundwater potential investigation in peat land area, Riau, Indonesia.Crossref | GoogleScholarGoogle Scholar |

Karafyllidis I, Thanailakis A (1997) A model for predicting forest fire spreading using cellular automata. Ecological Modelling 99, 87–97.
A model for predicting forest fire spreading using cellular automata.Crossref | GoogleScholarGoogle Scholar |

Khayal MSH, Khan A, Bashir S, Khan FH, Aslam S (2011) Modified new algorithm for seed filling. Journal of Theoretical and Applied Information Technology 26, 28–32.

Lautenberger C (2013) Wildland fire modeling with an Eulerian level set method and automated calibration. Fire Safety Journal 62, 289–298.
Wildland fire modeling with an Eulerian level set method and automated calibration.Crossref | GoogleScholarGoogle Scholar |

Lin S, Sun P, Huang X (2019) Can peat soil support a flaming wildfire? International Journal of Wildland Fire 28, 601–613.
Can peat soil support a flaming wildfire?Crossref | GoogleScholarGoogle Scholar |

Lin S, Liu Y, Huang X (2021) How to build a firebreak to stop smouldering peat fire: Insights from a laboratory-scale study. International Journal of Wildland Fire 30, 454–461.
How to build a firebreak to stop smouldering peat fire: Insights from a laboratory-scale study.Crossref | GoogleScholarGoogle Scholar |

Null J (2021) ‘El Niño and La Niña Years and Intensities.’ (Golden Gate Weather Service)

Page SE, Siegert F, Rieley JO, Boehm HD V, Jaya A, Limin S (2002) The amount of carbon released from peat and forest fires in Indonesia during 1997. Nature 420, 61–65.
The amount of carbon released from peat and forest fires in Indonesia during 1997.Crossref | GoogleScholarGoogle Scholar |

Prat-Guitart N, Rein G, Hadden RM, Belcher CM, Yearsley JM (2016) Propagation probability and spread rates of self-sustained smouldering fires under controlled moisture content and bulk density conditions. International Journal of Wildland Fire 25, 456–465.
Propagation probability and spread rates of self-sustained smouldering fires under controlled moisture content and bulk density conditions.Crossref | GoogleScholarGoogle Scholar |

Prat-Guitart N, Belcher CM, Thompson DK, Burns P, Yearsley JM (2017) Fine-scale distribution of moisture in the surface of a degraded blanket bog and its effects on the potential spread of smouldering fire. Ecohydrology 10, e1898
Fine-scale distribution of moisture in the surface of a degraded blanket bog and its effects on the potential spread of smouldering fire.Crossref | GoogleScholarGoogle Scholar |

Purnomo DMJ (2022) Cellular Automata Simulations of Field-Scale Flaming and Smouldering Wildfires in Peatlands. PhD thesis, Imperial College London, United Kingdom.

Purnomo DMJ, Bonner M, Moafi S, Rein G (2021) Using cellular automata to simulate field-scale flaming and smouldering wildfires in tropical peatlands. Proceedings of the Combustion Institute 38, 5119–5127.
Using cellular automata to simulate field-scale flaming and smouldering wildfires in tropical peatlands.Crossref | GoogleScholarGoogle Scholar |

Rein G (2013) Smouldering Fires and Natural Fuels. In ‘Fire Phenomena and the Earth System’. (Ed. CM Belcher) pp. 15–33. (Wiley and Sons)
| Crossref |

Rein G, Huang X (2021) Smouldering wildfires in peatlands, forests and the arctic: Challenges and perspectives. Current Opinion in Environmental Science & Health 24, 100296
Smouldering wildfires in peatlands, forests and the arctic: Challenges and perspectives.Crossref | GoogleScholarGoogle Scholar |

Rezanezhad F, Price JS, Quinton WL, Lennartz B, Milojevic T, Van Cappellen P (2016) Structure of peat soils and implications for water storage, flow and solute transport: A review update for geochemists. Chemical Geology 429, 75–84.
Structure of peat soils and implications for water storage, flow and solute transport: A review update for geochemists.Crossref | GoogleScholarGoogle Scholar |

Ritzema H, Limin S, Kusin K, Jauhiainen J, Wösten H (2014) Canal blocking strategies for hydrological restoration of degraded tropical peatlands in Central Kalimantan, Indonesia. Catena 114, 11–20.
Canal blocking strategies for hydrological restoration of degraded tropical peatlands in Central Kalimantan, Indonesia.Crossref | GoogleScholarGoogle Scholar |

Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper INT-RP-115. (Ogden, UT) Available at https://www.fs.usda.gov/treesearch/pubs/32533

Scholten RC, Jandt R, Miller EA, Rogers BM, Veraverbeke S (2021) Overwintering fires in boreal forests. Nature 593, 399–404.
Overwintering fires in boreal forests.Crossref | GoogleScholarGoogle Scholar |

Sofan P, Bruce D, Jones E, Khomarudin MR, Roswintiarti O (2020) Applying the tropical peatland combustion algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery. Remote Sensing 12, 3958
Applying the tropical peatland combustion algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery.Crossref | GoogleScholarGoogle Scholar |

Stavrakoudis D, Katagis T, Minakou C, Gitas IZ (2020) Automated Burned Scar Mapping Using Sentinel-2 Imagery. Journal of Geographic Information System 12, 221–240.
Automated Burned Scar Mapping Using Sentinel-2 Imagery.Crossref | GoogleScholarGoogle Scholar |

Sun L, Xu C, He Y, Zhao Y, Xu Y, Rui X, Xu H (2021) Adaptive forest fire spread simulation algorithm based on cellular automata. Forests 12, 1431
Adaptive forest fire spread simulation algorithm based on cellular automata.Crossref | GoogleScholarGoogle Scholar |

Turetsky MR, Benscoter B, Page S, Rein G, Van Der Werf GR, Watts A (2015) Global vulnerability of peatlands to fire and carbon loss. Nature Geoscience 8, 11–14.
Global vulnerability of peatlands to fire and carbon loss.Crossref | GoogleScholarGoogle Scholar |

von Neumann J (1967) In ‘Theory of Self-Reproducing Automata’. (Ed. AW Burks) (University of Illinois Press: Urbana)
| Crossref |

Waddington JM, Morris PJ, Kettridge N, Granath G, Thompson DK, Moore PA (2015) Hydrological feedbacks in northern peatlands. Ecohydrology 8, 113–127.
Hydrological feedbacks in northern peatlands.Crossref | GoogleScholarGoogle Scholar |

Widyastuti K, Imron MA, Pradopo ST, Suryatmojo H, Sopha BM, Spessa A, Berger U (2021) PeatFire: an agent-based model to simulate fire ignition and spreading in a tropical peatland ecosystem. International Journal of Wildland Fire 30, 71–89.
PeatFire: an agent-based model to simulate fire ignition and spreading in a tropical peatland ecosystem.Crossref | GoogleScholarGoogle Scholar |

Wolfram S (1984) Cellular automata as models of complexity. Nature 311, 419–424.
Cellular automata as models of complexity.Crossref | GoogleScholarGoogle Scholar |

Yuan H, Restuccia F, Rein G (2021) Spontaneous ignition of soils: A multi-step reaction scheme to simulate self-heating ignition of smouldering peat fires. International Journal of Wildland Fire 30, 440–453.
Spontaneous ignition of soils: A multi-step reaction scheme to simulate self-heating ignition of smouldering peat fires.Crossref | GoogleScholarGoogle Scholar |