Articles citing this paper
Simple models for predicting dead fuel moisture in eucalyptus forests
Stuart Matthews A B C E , Jim Gould A C and Lachie McCaw C D
+ Author Affiliations
- Author Affiliations
A Climate Adaptation Flagship – CSIRO Sustainable Ecosystems, Bellenden St, Crace, ACT 2911, Australia.
B Faculty of Agriculture, Food, and Natural Resources, Woolley Building A20, The University of Sydney, NSW 2006, Australia.
C Bushfire Cooperative Research Centre, 340 Albert St, East Melbourne, VIC 3002, Australia.
D Western Australia Department of Environment and Conservation, Brain St, Manjimup, WA 6258, Australia.
E Corresponding author. Email: stuart.matthews@csiro.au
International Journal of Wildland Fire 19(4) 459-467 https://doi.org/10.1071/WF09005
Submitted: 16 January 2009 Accepted: 21 October 2009 Published: 24 June 2010
54 articles found in Crossref database.
Dead fuel moisture research: 1991–2012
Matthews Stuart
International Journal of Wildland Fire. 2014 23(1). p.78
Fire danger index efficiency as a function of fuel moisture and fire behavior
Torres Fillipe Tamiozzo Pereira,
Romeiro Joyce Machado Nunes,
Santos Ana Carolina de Albuquerque,
de Oliveira Neto Ricardo Rodrigues,
Lima Gumercindo Souza, Zanuncio José Cola
Science of The Total Environment. 2018 631-632 p.1304
Predicting hourly litter moisture content of larch stands in Daxinganling Region, China using three vapour-exchange methods
Sun Ping,
Yu Hongzhou, Jin Sen
International Journal of Wildland Fire. 2015 24(1). p.114
The influence of fuel moisture content on the combustion of Eucalyptus foliage
Possell Malcolm, Bell Tina L.
International Journal of Wildland Fire. 2013 22(3). p.343
Determining landscape fine fuel moisture content of the Kilmore East ‘Black Saturday’ wildfire using spatially-extended point-based models
Sullivan A.L., Matthews S.
Environmental Modelling & Software. 2013 40 p.98
Electrically caused wildfires in Victoria, Australia are over-represented when fire danger is elevated
Miller Claire,
Plucinski Matt,
Sullivan Andrew,
Stephenson Alec,
Huston Carolyn,
Charman Kay,
Prakash Mahesh, Dunstall Simon
Landscape and Urban Planning. 2017 167 p.267
Empirical-based models for predicting head-fire rate of spread in Australian fuel types
Cruz Miguel G.,
Gould James S.,
Alexander Martin E.,
Sullivan Andrew L.,
McCaw W. Lachlan, Matthews Stuart
Australian Forestry. 2015 78(3). p.118
Techniques for evaluating wildfire simulators via the simulation of historical fires using the AUSTRALIS simulator
Kelso Joel K.,
Mellor Drew,
Murphy Mary E., Milne George J.
International Journal of Wildland Fire. 2015 24(6). p.784
Fine fuel moisture for site- and species-specific fire danger assessment in comparison to fire danger indices
Schunk Christian,
Wastl Clemens,
Leuchner Michael, Menzel Annette
Agricultural and Forest Meteorology. 2017 234-235 p.31
Evaluating the 10% wind speed rule of thumb for estimating a wildfire's forward rate of spread against an extensive independent set of observations
Cruz Miguel G.,
Alexander Martin E.,
Fernandes Paulo M.,
Kilinc Musa, Sil Ângelo
Environmental Modelling & Software. 2020 133 p.104818
Eco-hydrological controls on microclimate and surface fuel evaporation in complex terrain
Nyman Petter,
Baillie Craig C.,
Duff Thomas J., Sheridan Gary J.
Agricultural and Forest Meteorology. 2018 252 p.49
Study on the Diurnal Dynamic Changes and Prediction Models of the Moisture Contents of Two Litters
Zhang Yunlin, Sun Ping
Forests. 2020 11(1). p.95
Recent advances and applications of WRF–SFIRE
Mandel J.,
Amram S.,
Beezley J. D.,
Kelman G.,
Kochanski A. K.,
Kondratenko V. Y.,
Lynn B. H.,
Regev B., Vejmelka M.
Natural Hazards and Earth System Sciences. 2014 14(10). p.2829
Forest Fuel Drying, Pyrolysis and Ignition Processes during Forest Fire: A Review
Baranovskiy Nikolay Viktorovich, Kirienko Viktoriya Andreevna
Processes. 2022 10(1). p.89
Rapid wind–terrain correction for wildfire simulations
Hilton James, Garg Nikhil
International Journal of Wildland Fire. 2021 30(6). p.410
An empirical-based model for predicting the forward spread rate of wildfires in eucalypt forests
Cruz Miguel G.,
Cheney N. Phillip,
Gould James S.,
McCaw W. Lachlan,
Kilinc Musa, Sullivan Andrew L.
International Journal of Wildland Fire. 2021 31(1). p.81
Comparing the performance of daily forest fire danger summary metrics for estimating fire activity in southern Australian forests
Plucinski M. P.,
Sullivan A. L., McCaw W. L.
International Journal of Wildland Fire. 2020 29(10). p.926
Evaluation of a very simple model for predicting the moisture content of eucalypt litter
Sharples Jason J., McRae Richard H. D.
International Journal of Wildland Fire. 2011 20(8). p.1000
Estimation of 10-Hour Fuel Moisture Content Using Meteorological Data: A Model Inter-Comparison Study
Lee HoonTaek,
Won Myoungsoo,
Yoon Sukhee, Jang Keunchang
Forests. 2020 11(9). p.982
Regional estimation of dead fuel moisture content in southwest China based on a practical process-based model
Fan Chunquan,
He Binbin,
Yin Jianpeng, Chen Rui
International Journal of Wildland Fire. 2023 32(7). p.1148
Comparison of vapour-exchange methods for predicting hourly twig fuel moisture contents of larch and birch stands in the Daxinganling Region, China
Yu Hongzhou,
Shu Lifu,
Yang Guang, Deng Jifeng
International Journal of Wildland Fire. 2021 30(6). p.462
Predicting fire behaviour in dry eucalypt forest in southern Australia
Cheney N. Phillip,
Gould James S.,
McCaw W. Lachlan, Anderson Wendy R.
Forest Ecology and Management. 2012 280 p.120
Predicting the number of daily human-caused bushfires to assist suppression planning in south-west Western Australia
Plucinski M. P.,
McCaw W. L.,
Gould J. S., Wotton B. M.
International Journal of Wildland Fire. 2014 23(4). p.520
A Surrogate Model for Rapidly Assessing the Size of a Wildfire over Time
KC Ujjwal,
Aryal Jagannath,
Hilton James, Garg Saurabh
Fire. 2021 4(2). p.20
Linking fire behaviour and its ecological effects to plant traits, using FRaME in R
Zylstra Philip
Methods in Ecology and Evolution. 2021 12(8). p.1365
Dynamic changes in moisture content and applicability analysis of a typical litter prediction model in Yunnan Province
Zhang Yunlin, Tian Lingling
PeerJ. 2021 9 p.e12206
Modelling drying processes of fuelbeds of Scots pine needles with initial moisture content above the fibre saturation point by two-phase models
Jin Sen, Chen Pengyu
International Journal of Wildland Fire. 2012 21(4). p.418
Relationship between Forest Fuel Moisture Contents and Weather Factors During the Forest Fires Danger Season in Chuncheon, Gangwon
Han Songhee, Chae Heemun
Journal of the Korean Society of Hazard Mitigation. 2022 22(2). p.109
Impact of mechanical thinning on forest carbon, fuel hazard and simulated fire behaviour in Eucalyptus delegatensis forest of south-eastern Australia
Volkova Liubov,
Bi Huiquan,
Hilton James, Weston Christopher J.
Forest Ecology and Management. 2017 405 p.92
Accounting for among-sampler variability improves confidence in fuel moisture content field measurements
Little Kerryn,
Graham Laura J., Kettridge Nicholas
International Journal of Wildland Fire. 2023 33(1).
Modeling the drying process of Masson pine needle fuel beds under different packing ratios based on two-phase models in the laboratory
Zhang Yunlin
PeerJ. 2022 10 p.e14484
Improving the reliability and utility of operational bushfire behaviour predictions in Australian vegetation
Plucinski Matt P.,
Sullivan Andrew L.,
Rucinski Chris J., Prakash Mahesh
Environmental Modelling & Software. 2017 91 p.1
A model for assessing water quality risk in catchments prone to wildfire
Langhans Christoph,
Smith Hugh G.,
Chong Derek M.O.,
Nyman Petter,
Lane Patrick N.J., Sheridan Gary J.
Journal of Hydrology. 2016 534 p.407
Characterizing Forest Fuel Properties and Potential Wildfire Dynamics in Xiuwu, Henan, China
Shi Yan,
Feng Changping,
Zhang Liwei,
Huang Wen,
Wang Xin,
Yang Shipeng,
Chen Weiwei, Xie Wenjie
Fire. 2023 7(1). p.7
A Physics-Guided Deep Learning Model for 10-h Dead Fuel Moisture Content Estimation
Fan Chunquan, He Binbin
Forests. 2021 12(7). p.933
Moisture content estimation of forest litter based on remote sensing data
Yang Xiguang,
Yu Ying,
Hu Haiqing, Sun Long
Environmental Monitoring and Assessment. 2018 190(7).
Process-based and geostationary meteorological satellite-enhanced dead fuel moisture content estimation
Fan Chunquan,
He Binbin,
Yin Jianpeng,
Chen Rui, Zhang Hongguo
GIScience & Remote Sensing. 2024 61(1).
Modelling the dead fuel moisture content in a grassland of Ergun City, China
Chang Chang,
Chang Yu,
Guo Meng, Hu Yuanman
Journal of Arid Land. 2023 15(6). p.710
Numerical study on effect of relative humidity (and fuel moisture) on modes of grassfire propagation
Moinuddin Khalid,
Khan Nazmul, Sutherland Duncan
Fire Safety Journal. 2021 125 p.103422
Modeling surface fuels moisture content in Pinus brutia stands
Bilgili Ertugrul,
Coskuner Kadir Alperen,
Usta Yetkin, Goltas Merih
Journal of Forestry Research. 2019 30(2). p.577
The influence of soil moisture on surface and sub-surface litter fuel moisture simulation at five Australian sites
Zhao Li,
Yebra Marta,
van Dijk Albert I.J.M.,
Cary Geoffrey J.,
Matthews Stuart, Sheridan Gary
Agricultural and Forest Meteorology. 2021 298-299 p.108282
Managing forest fuels using prescribed fire – A perspective from southern Australia
McCaw W. Lachlan
Forest Ecology and Management. 2013 294 p.217
Diurnal variation models for fine fuel moisture content in boreal forests in China
Zhang Ran,
Hu Haiqing,
Qu Zhilin, Hu Tongxin
Journal of Forestry Research. 2021 32(3). p.1177
Prediction model of moisture content of dead fine fuel in forest plantations on Maoer Mountain, Northeast China
Masinda Maombi Mbusa,
Li Fei,
Liu Qi,
Sun Long, Hu Tongxin
Journal of Forestry Research. 2021 32(5). p.2023
Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia
Cruz M.G.,
McCaw W.L.,
Anderson W.R., Gould J.S.
Environmental Modelling & Software. 2013 40 p.21
Representing vapour and capillary rise from the soil improves a leaf litter moisture model
Zhao Li,
Yebra Marta,
van Dijk Albert I.J.M., Cary Geoffrey J.
Journal of Hydrology. 2022 612 p.128087
Equilibrium moisture content and timelag of dead Pinus pinaster needles
Lopes Sérgio,
Viegas Domingos Xavier,
Teixeira de Lemos Luís, Viegas Maria Teresa
International Journal of Wildland Fire. 2014 23(5). p.721
A generic, empirical-based model for predicting rate of fire spread in shrublands
Anderson Wendy R.,
Cruz Miguel G.,
Fernandes Paulo M.,
McCaw Lachlan,
Vega Jose Antonio,
Bradstock Ross A.,
Fogarty Liam,
Gould Jim,
McCarthy Greg,
Marsden-Smedley Jon B.,
Matthews Stuart,
Mattingley Greg,
Pearce H. Grant, van Wilgen Brian W.
International Journal of Wildland Fire. 2015 24(4). p.443
A comparison of five models in predicting surface dead fine fuel moisture content of typical forests in Northeast China
Fan Jiale,
Hu Tongxin,
Ren Jinsong,
Liu Qi, Sun Long
Frontiers in Forests and Global Change. 2023 6
Modelling the determinants of ignition in the Sydney Basin, Australia: implications for future management
Penman T. D.,
Bradstock R. A., Price O.
International Journal of Wildland Fire. 2013 22(4). p.469
Indoor Experiments on the Moisture Dynamic Response to Wind Velocity for Fuelbeds with Different Degrees of Compactness
Zhang Yunlin
Fire. 2023 6(3). p.90
Testing existing models for predicting hourly variation in fine fuel moisture in eucalypt forests
Slijepcevic A.,
Anderson W.R., Matthews S.
Forest Ecology and Management. 2013 306 p.202
Quantifying the effects of topographic aspect on water content and temperature in fine surface fuel
Nyman Petter,
Metzen Daniel,
Noske Philip J.,
Lane Patrick N. J., Sheridan Gary J.
International Journal of Wildland Fire. 2015 24(8). p.1129
Modifying the Canadian Fine Fuel Moisture Code for masticated surface fuels
Schiks T. J., Wotton B. M.
International Journal of Wildland Fire. 2015 24(1). p.79
