{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T02:56:32Z","timestamp":1776135392607,"version":"3.50.1"},"reference-count":79,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T00:00:00Z","timestamp":1772928000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100009675","name":"Victoria Department of Energy Environment and Climate Action","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009675","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100022716","name":"Department of Energy, Environment and Climate Action","doi-asserted-by":"publisher","award":["TA301102"],"award-info":[{"award-number":["TA301102"]}],"id":[{"id":"10.13039\/100022716","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Environmental Modelling &amp; Software"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.envsoft.2026.106942","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T20:51:39Z","timestamp":1773003099000},"page":"106942","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Untethered from earthly constraints: A spatial seven-day ahead machine-learning forest fuel moisture forecasting system, independent of real-time sensor networks"],"prefix":"10.1016","volume":"200","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6084-1595","authenticated-orcid":false,"given":"Thomas","family":"Keeble","sequence":"first","affiliation":[]},{"given":"Christopher Sean","family":"Lyell","sequence":"additional","affiliation":[]},{"given":"Tim","family":"Gazzard","sequence":"additional","affiliation":[]},{"given":"Thomas James","family":"Duff","sequence":"additional","affiliation":[]},{"given":"Gary","family":"Sheridan","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"1\u20132","key":"10.1016\/j.envsoft.2026.106942_bib1","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.foreco.2005.01.034","article-title":"Basic principles of forest fuel reduction treatments","volume":"211","author":"Agee","year":"2005","journal-title":"For. Ecol. Manag."},{"issue":"4","key":"10.1016\/j.envsoft.2026.106942_bib2","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1007\/BF02588932","article-title":"Forest fuel ignitibility","volume":"6","author":"Anderson","year":"1970","journal-title":"Fire Technol."},{"key":"10.1016\/j.envsoft.2026.106942_bib3","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.cliser.2017.04.001","article-title":"Seasonal predictions of fire weather index: paving the way for their operational applicability in mediterranean Europe","volume":"9","author":"Bedia","year":"2018","journal-title":"Clim. Serv."},{"key":"10.1016\/j.envsoft.2026.106942_bib4","series-title":"Flammable Australia: the Fire Regimes and Biodiversity of a Continent","year":"2002"},{"key":"10.1016\/j.envsoft.2026.106942_bib5","doi-asserted-by":"crossref","DOI":"10.1016\/j.agrformet.2022.108857","article-title":"The sensitivity of fuel moisture to forest structure effects on microclimate","volume":"316","author":"Brown","year":"2022","journal-title":"Agric. For. Meteorol."},{"issue":"693","key":"10.1016\/j.envsoft.2026.106942_bib6","doi-asserted-by":"crossref","first-page":"3366","DOI":"10.1002\/qj.2619","article-title":"The forecast skill horizon","volume":"141","author":"Buizza","year":"2015","journal-title":"Q. J. R. Meteorol. Soc."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106942_bib7","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1071\/WF01011","article-title":"Estimating fuel response time and predicting fuel moisture content from field data","volume":"10","author":"Catchpole","year":"2001","journal-title":"Int. J. Wildland Fire"},{"key":"10.1016\/j.envsoft.2026.106942_bib8","first-page":"2079","article-title":"On over-fitting in model selection and subsequent selection bias in performance evaluation","volume":"11","author":"Cawley","year":"2010","journal-title":"J. Mach. Learn. Res."},{"issue":"8","key":"10.1016\/j.envsoft.2026.106942_bib9","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1007\/s10980-020-01055-z","article-title":"Exploring the key drivers of forest flammability in wet eucalypt forests using expert-derived conceptual models","volume":"35","author":"Cawson","year":"2020","journal-title":"Landsc. Ecol."},{"issue":"6","key":"10.1016\/j.envsoft.2026.106942_bib10","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1071\/WF19061","article-title":"Estimation of surface dead fine fuel moisture using automated fuel moisture sticks across a range of forests worldwide","volume":"29","author":"Cawson","year":"2020","journal-title":"Int. J. Wildland Fire"},{"issue":"12","key":"10.1016\/j.envsoft.2026.106942_bib11","doi-asserted-by":"crossref","first-page":"1987","DOI":"10.1175\/JAMC-D-25-0068.1","article-title":"Machine learning\u2013based analysis and prediction of 10-h dead fuel moisture content using automated weather observations in Gangwon province, South Korea","volume":"64","author":"Chae","year":"2025","journal-title":"J. Appl. Meteorol. Climatol."},{"issue":"4","key":"10.1016\/j.envsoft.2026.106942_bib12","doi-asserted-by":"crossref","first-page":"288","DOI":"10.2307\/1313612","article-title":"Variations in local climate can be used to monitor and compare the effects of different management regimes","volume":"49","author":"Chen","year":"1999","journal-title":"Bioscience"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106942_bib13","doi-asserted-by":"crossref","first-page":"7161","DOI":"10.1038\/s41467-022-34966-3","article-title":"Forest fire threatens global carbon sinks and population centres under rising atmospheric water demand","volume":"13","author":"Clarke","year":"2022","journal-title":"Nat. Commun."},{"issue":"4","key":"10.1016\/j.envsoft.2026.106942_bib14","doi-asserted-by":"crossref","DOI":"10.1088\/1748-9326\/abeb9e","article-title":"The 2019\/2020 mega-fires exposed Australian ecosystems to an unprecedented extent of high-severity fire","volume":"16","author":"Collins","year":"2021","journal-title":"Environ. Res. Lett."},{"issue":"10","key":"10.1016\/j.envsoft.2026.106942_bib15","doi-asserted-by":"crossref","first-page":"1933","DOI":"10.1111\/geb.13514","article-title":"Warmer and drier conditions have increased the potential for large and severe fire seasons across south\u2010eastern Australia","volume":"31","author":"Collins","year":"2022","journal-title":"Global Ecol. Biogeogr."},{"key":"10.1016\/j.envsoft.2026.106942_bib16","doi-asserted-by":"crossref","DOI":"10.1016\/j.jenvman.2023.118171","article-title":"Fuel reduction burning reduces wildfire severity during extreme fire events in south-eastern Australia","volume":"343","author":"Collins","year":"2023","journal-title":"J. Environ. Manag."},{"issue":"5","key":"10.1016\/j.envsoft.2026.106942_bib17","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1175\/2011JHM1347.1","article-title":"A review of quantitative precipitation forecasts and their use in Short- to medium-range streamflow forecasting","volume":"12","author":"Cuo","year":"2011","journal-title":"J. Hydrometeorol."},{"issue":"4","key":"10.1016\/j.envsoft.2026.106942_bib19","doi-asserted-by":"crossref","first-page":"1544","DOI":"10.1111\/gcb.16006","article-title":"Global increase in wildfire risk due to climate-driven declines in fuel moisture","volume":"28","author":"Ellis","year":"2022","journal-title":"Glob. Change Biol."},{"issue":"7","key":"10.1016\/j.envsoft.2026.106942_bib20","doi-asserted-by":"crossref","first-page":"933","DOI":"10.3390\/f12070933","article-title":"A physics-guided deep learning model for 10-h dead fuel moisture content estimation","volume":"12","author":"Fan","year":"2021","journal-title":"Forests"},{"key":"10.1016\/j.envsoft.2026.106942_bib21","doi-asserted-by":"crossref","DOI":"10.3389\/ffgc.2023.1122087","article-title":"A comparison of five models in predicting surface dead fine fuel moisture content of typical forests in northeast China","volume":"6","author":"Fan","year":"2023","journal-title":"Front. For. Glob. Change"},{"issue":"3","key":"10.1016\/j.envsoft.2026.106942_bib22","doi-asserted-by":"crossref","first-page":"404","DOI":"10.5589\/m02-035","article-title":"The advanced scatterometer (ASCAT) on the meteorological operational (MetOp) platform: a follow on for European wind scatterometers","volume":"28","author":"Figa-Salda\u00f1a","year":"2002","journal-title":"Can. J. Rem. Sens."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106942_bib23","first-page":"44","article-title":"Impact of Australia's catastrophic 2019\/20 bushfire season on communities and environment. Retrospective analysis and current trends","volume":"1","author":"Filkov","year":"2020","journal-title":"J. Saf. Sci. Resil."},{"key":"10.1016\/j.envsoft.2026.106942_bib24","series-title":"The Australian Landscape Water Balance Model (AWRA-L v7). Technical Description of the Australian Water Resources Assessment Landscape Model Version 7","author":"Frost","year":"2021"},{"issue":"3","key":"10.1016\/j.envsoft.2026.106942_bib25","doi-asserted-by":"crossref","first-page":"475","DOI":"10.3390\/atmos13030475","article-title":"Meteorological analysis of the 2021 extreme wildfires in Greece: lessons learned and implications for early warning of the potential for pyroconvection","volume":"13","author":"Giannaros","year":"2022","journal-title":"Atmosphere"},{"issue":"3","key":"10.1016\/j.envsoft.2026.106942_bib26","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1080\/01431161.2016.1266112","article-title":"A method for mapping Australian woody vegetation cover by linking continental-scale field data and long-term Landsat time series","volume":"38","author":"Gill","year":"2017","journal-title":"Int. J. Rem. Sens."},{"issue":"1\u20132","key":"10.1016\/j.envsoft.2026.106942_bib27","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.jhydrol.2009.02.013","article-title":"Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia","volume":"369","author":"Guerschman","year":"2009","journal-title":"J. Hydrol."},{"issue":"7","key":"10.1016\/j.envsoft.2026.106942_bib28","doi-asserted-by":"crossref","first-page":"1563","DOI":"10.1175\/2010JAMC2397.1","article-title":"An evaluation of the distribution of Remote Automated Weather Stations (RAWS)","volume":"49","author":"Horel","year":"2010","journal-title":"J. Appl. Meteorol. Climatol."},{"issue":"4","key":"10.1016\/j.envsoft.2026.106942_bib29","doi-asserted-by":"crossref","first-page":"233","DOI":"10.22499\/2.5804.003","article-title":"High-quality spatial climate data-sets for Australia","volume":"58","author":"Jones","year":"2009","journal-title":"Australian. Meteorol. Oceanographic. J."},{"key":"10.1016\/j.envsoft.2026.106942_bib30","series-title":"Encyclopedia of Wildfires and Wildland-Urban Interface (WUI) Fires","first-page":"1","article-title":"Fuel moisture","author":"Kane","year":"2018"},{"key":"10.1016\/j.envsoft.2026.106942_bib31","article-title":"LightGBM: a highly efficient gradient boosting decision tree","volume":"vol. 30","author":"Ke","year":"2017"},{"issue":"8","key":"10.1016\/j.envsoft.2026.106942_bib32","doi-asserted-by":"crossref","DOI":"10.1002\/ecs2.4203","article-title":"The effects of prolonged drought on vegetation dieback and megafires in southern California chaparral","volume":"13","author":"Keeley","year":"2022","journal-title":"Ecosphere"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106942_bib33","doi-asserted-by":"crossref","DOI":"10.1186\/s42408-021-00110-7","article-title":"Large California wildfires: 2020 fires in historical context","volume":"17","author":"Keeley","year":"2021","journal-title":"Fire Ecol."},{"issue":"6","key":"10.1016\/j.envsoft.2026.106942_bib34","doi-asserted-by":"crossref","DOI":"10.1111\/geb.13834","article-title":"Microclimate, an important part of ecology and biogeography","volume":"33","author":"Kemppinen","year":"2024","journal-title":"Global Ecol. Biogeogr."},{"issue":"9","key":"10.1016\/j.envsoft.2026.106942_bib35","doi-asserted-by":"crossref","first-page":"982","DOI":"10.3390\/f11090982","article-title":"Estimation of 10-Hour fuel moisture content using meteorological data: a model inter-comparison Study","volume":"11","author":"Lee","year":"2020","journal-title":"Forests"},{"issue":"13","key":"10.1016\/j.envsoft.2026.106942_bib36","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.adk4489","article-title":"Generative emulation of weather forecast ensembles with diffusion models","volume":"10","author":"Li","year":"2024","journal-title":"Sci. Adv."},{"issue":"4","key":"10.1016\/j.envsoft.2026.106942_bib37","doi-asserted-by":"crossref","DOI":"10.1111\/geb.70032","article-title":"\u2018Megafire\u2019\u2014You May not like It, but you cannot avoid it","volume":"34","author":"Linley","year":"2025","journal-title":"Global Ecol. Biogeogr."},{"key":"10.1016\/j.envsoft.2026.106942_bib38","doi-asserted-by":"crossref","DOI":"10.1016\/j.agrformet.2024.110217","article-title":"Forecasting dead fuel moisture content below forest canopies \u2013 a seven-day forecasting system","volume":"358","author":"Lyell","year":"2024","journal-title":"Agric. For. Meteorol."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106942_bib39","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1071\/WF05063","article-title":"A process-based model of fine fuel moisture","volume":"15","author":"Matthews","year":"2006","journal-title":"Int. J. Wildland Fire"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106942_bib40","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1071\/WF13005","article-title":"Dead fuel moisture research: 1991\u20132012","volume":"23","author":"Matthews","year":"2014","journal-title":"Int. J. Wildland Fire"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106942_bib41","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1139\/x06-207","article-title":"Testing a process-based fine fuel moisture model in two forest types","volume":"37","author":"Matthews","year":"2007","journal-title":"Can. J. For. Res."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106942_bib42","article-title":"Enhancing wildfire spread modelling by building a gridded fuel moisture content product with machine learning","volume":"1","author":"McCandless","year":"2020","journal-title":"Mach. Learn.: Sci. Technol."},{"key":"10.1016\/j.envsoft.2026.106942_bib43","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.foreco.2012.09.012","article-title":"Managing forest fuels using prescribed fire \u2013 a perspective from southern Australia","volume":"294","author":"McCaw","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"10.1016\/j.envsoft.2026.106942_bib44","doi-asserted-by":"crossref","DOI":"10.1016\/j.earscirev.2020.103225","article-title":"Machine learning methods for landslide susceptibility studies: a comparative overview of algorithm performance","volume":"207","author":"Merghadi","year":"2020","journal-title":"Earth Sci. Rev."},{"issue":"9","key":"10.1016\/j.envsoft.2026.106942_bib45","doi-asserted-by":"crossref","first-page":"732","DOI":"10.3390\/rs8090732","article-title":"Mapping daily air temperature for Antarctica based on MODIS LST","volume":"8","author":"Meyer","year":"2016","journal-title":"Remote Sens."},{"issue":"5","key":"10.1016\/j.envsoft.2026.106942_bib46","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1071\/WF22188","article-title":"Projecting live fuel moisture content via deep learning","volume":"32","author":"Miller","year":"2023","journal-title":"Int. J. Wildland Fire"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106942_bib47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2136\/vzj2016.10.0105","article-title":"Soil moisture remote sensing: state-of-the-science","volume":"16","author":"Mohanty","year":"2017","journal-title":"Vadose Zone J."},{"key":"10.1016\/j.envsoft.2026.106942_bib48","series-title":"Principles of Environmental Physics: Plants, Animals, and the Atmosphere","year":"2013"},{"key":"10.1016\/j.envsoft.2026.106942_bib49","doi-asserted-by":"crossref","DOI":"10.1016\/j.cageo.2024.105601","article-title":"SERT: a transformer based model for multivariate temporal sensor data with missing values for environmental monitoring","volume":"188","author":"Nejad","year":"2024","journal-title":"Comput. Geosci."},{"issue":"10","key":"10.1016\/j.envsoft.2026.106942_bib50","doi-asserted-by":"crossref","first-page":"1898","DOI":"10.1111\/geb.13588","article-title":"Increasing threat of wildfires: the year 2020 in perspective: a Global Ecology and Biogeography special issue","volume":"31","author":"Nolan","year":"2022","journal-title":"Global Ecol. Biogeogr."},{"issue":"7","key":"10.1016\/j.envsoft.2026.106942_bib51","doi-asserted-by":"crossref","first-page":"779","DOI":"10.3390\/f11070779","article-title":"Linking Forest flammability and plant vulnerability to drought","volume":"11","author":"Nolan","year":"2020","journal-title":"Forests"},{"key":"10.1016\/j.envsoft.2026.106942_bib52","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.rse.2015.12.010","article-title":"Predicting dead fine fuel moisture at regional scales using vapour pressure deficit from MODIS and gridded weather data","volume":"174","author":"Nolan","year":"2016","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.envsoft.2026.106942_bib53","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.agrformet.2017.12.255","article-title":"Eco-hydrological controls on microclimate and surface fuel evaporation in complex terrain","volume":"252","author":"Nyman","year":"2018","journal-title":"Agric. For. Meteorol."},{"issue":"8","key":"10.1016\/j.envsoft.2026.106942_bib54","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1071\/WF14195","article-title":"Quantifying the effects of topographic aspect on water content and temperature in fine surface fuel","volume":"24","author":"Nyman","year":"2015","journal-title":"Int. J. Wildland Fire"},{"issue":"2","key":"10.1016\/j.envsoft.2026.106942_bib55","doi-asserted-by":"crossref","first-page":"109","DOI":"10.22499\/2.6402.003","article-title":"Downscaling regional climate data to calculate the radiative index of dryness in complex terrain","volume":"64","author":"Nyman","year":"2014","journal-title":"Australian. Meteorol. Oceanographic. J."},{"issue":"10","key":"10.1016\/j.envsoft.2026.106942_bib56","doi-asserted-by":"crossref","DOI":"10.1029\/2023WR036337","article-title":"Interpretable transformer neural network prediction of diverse environmental time series using weather forecasts","volume":"60","author":"Orozco L\u00f3pez","year":"2024","journal-title":"Water Resour. Res."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106942_bib57","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1002\/wcc.220","article-title":"Ensemble modeling, uncertainty and robust predictions","volume":"4","author":"Parker","year":"2013","journal-title":"WIREs Clim. Change"},{"key":"10.1016\/j.envsoft.2026.106942_bib58","doi-asserted-by":"crossref","DOI":"10.1016\/j.envsoft.2024.106254","article-title":"An adaptable dead fuel moisture model for various fuel types and temporal scales tailored for wildfire danger assessment","volume":"183","author":"Perello","year":"2025","journal-title":"Environ. Model. Software"},{"key":"10.1016\/j.envsoft.2026.106942_bib59","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.envsoft.2016.02.008","article-title":"Sensitivity analysis of environmental models: a systematic review with practical workflow","volume":"79","author":"Pianosi","year":"2016","journal-title":"Environ. Model. Software"},{"key":"10.1016\/j.envsoft.2026.106942_bib60","doi-asserted-by":"crossref","DOI":"10.1016\/j.agrformet.2020.108311","article-title":"Darker, cooler, wetter: forest understories influence surface fuel moisture","volume":"300","author":"Pickering","year":"2021","journal-title":"Agric. For. Meteorol."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106942_bib61","doi-asserted-by":"crossref","first-page":"28","DOI":"10.3390\/fire2020028","article-title":"The effect of ecophysiological traits on live fuel moisture content","volume":"2","author":"Pivovaroff","year":"2019","journal-title":"Fire"},{"issue":"2","key":"10.1016\/j.envsoft.2026.106942_bib62","doi-asserted-by":"crossref","first-page":"265","DOI":"10.22499\/2.6302.001","article-title":"Implementation of the initial ACCESS numerical weather prediction system","volume":"63","author":"Puri","year":"2013","journal-title":"Australian. Meteorol. Oceanographic. J."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106942_bib63","doi-asserted-by":"crossref","first-page":"71","DOI":"10.4996\/fireecology.0803071","article-title":"Monitoring live fuel moisture using soil moisture and remote sensing proxies","volume":"8","author":"Qi","year":"2012","journal-title":"Fire Ecol."},{"key":"10.1016\/j.envsoft.2026.106942_bib64","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.agrformet.2015.01.002","article-title":"A semi-mechanistic model for predicting the moisture content of fine litter","volume":"203","author":"Resco De Dios","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"10.1016\/j.envsoft.2026.106942_bib65","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2022.160320","article-title":"Drivers and implications of the extreme 2022 wildfire season in Southwest Europe","volume":"859","author":"Rodrigues","year":"2023","journal-title":"Sci. Total Environ."},{"issue":"10","key":"10.1016\/j.envsoft.2026.106942_bib66","doi-asserted-by":"crossref","first-page":"2005","DOI":"10.1111\/geb.13498","article-title":"The 2020 California fire season: a year like no other, a return to the past or a harbinger of the future?","volume":"31","author":"Safford","year":"2022","journal-title":"Global Ecol. Biogeogr."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106942_bib67","doi-asserted-by":"crossref","first-page":"403","DOI":"10.5194\/nhess-16-403-2016","article-title":"Comparison of different methods for the in situ measurement of forest litter moisture content","volume":"16","author":"Schunk","year":"2016","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"10.1016\/j.envsoft.2026.106942_bib68","series-title":"2024 5th International Conference on Data Intelligence and Cognitive Informatics (ICDICI)","first-page":"1348","article-title":"Rainfall prediction using random forest and XGBoost-A comparative study","author":"Sharma","year":"2024"},{"issue":"5","key":"10.1016\/j.envsoft.2026.106942_bib69","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.envsoft.2008.10.012","article-title":"A simple index for assessing fuel moisture content","volume":"24","author":"Sharples","year":"2009","journal-title":"Environ. Model. Software"},{"issue":"6","key":"10.1016\/j.envsoft.2026.106942_bib70","doi-asserted-by":"crossref","DOI":"10.1071\/WF23120","article-title":"Evaluation and comparison of simple empirical models for dead fuel moisture content","volume":"33","author":"Sharples","year":"2024","journal-title":"Int. J. Wildland Fire"},{"key":"10.1016\/j.envsoft.2026.106942_bib71","doi-asserted-by":"crossref","DOI":"10.1016\/j.foreco.2021.119897","article-title":"Machine-Learning-based evaluation of the time-lagged effect of meteorological factors on 10-hour dead fuel moisture content","volume":"505","author":"Shmuel","year":"2022","journal-title":"For. Ecol. Manag."},{"key":"10.1016\/j.envsoft.2026.106942_bib72","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.foreco.2014.09.040","article-title":"Evaluating models to predict daily fine fuel moisture content in eucalypt forest","volume":"335","author":"Slijepcevic","year":"2015","journal-title":"For. Ecol. Manag."},{"issue":"6","key":"10.1016\/j.envsoft.2026.106942_bib73","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1525\/bio.2012.62.6.6","article-title":"The effects of forest fuel-reduction treatments in the United States","volume":"62","author":"Stephens","year":"2012","journal-title":"Bioscience"},{"issue":"17","key":"10.1016\/j.envsoft.2026.106942_bib74","doi-asserted-by":"crossref","first-page":"4362","DOI":"10.3390\/rs14174362","article-title":"A Forest fire susceptibility modeling approach based on light gradient boosting machine algorithm","volume":"14","author":"Sun","year":"2022","journal-title":"Remote Sens."},{"key":"10.1016\/j.envsoft.2026.106942_bib75","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.agrformet.2017.01.013","article-title":"A model for simulating the moisture content of standardized fuel sticks of various sizes","volume":"236","author":"Van Der Kamp","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"10.1016\/j.envsoft.2026.106942_bib76","series-title":"Evaluation Against Observations [Technical Report]. CSIRO: Water for a Healthy Country National Research Flagship","article-title":"The Australian water resources assessment system. Technical report 4. Landscape model","author":"Van Dijk","year":"2010"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106942_bib77","doi-asserted-by":"crossref","first-page":"16","DOI":"10.3390\/fire5010016","article-title":"Megafires in a warming world: what wildfire risk factors led to california's largest recorded wildfire","volume":"5","author":"Varga","year":"2022","journal-title":"Fire"},{"issue":"2","key":"10.1016\/j.envsoft.2026.106942_bib78","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/s40725-015-0012-x","article-title":"The flammability of Forest and woodland litter: a synthesis","volume":"1","author":"Varner","year":"2015","journal-title":"Current Forestry Reports"},{"key":"10.1016\/j.envsoft.2026.106942_bib80","article-title":"Model upgrade plan and initial results from a prototype ncep global forecast system version 16","volume":"100","author":"Yang","year":"2020","journal-title":"American Meteorological Society Meeting Abstracts"},{"key":"10.1016\/j.envsoft.2026.106942_bib81","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.rse.2018.04.053","article-title":"A fuel moisture content and flammability monitoring methodology for continental Australia based on optical remote sensing","volume":"212","author":"Yebra","year":"2018","journal-title":"Rem. Sens. Environ."}],"container-title":["Environmental Modelling &amp; Software"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815226000897?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815226000897?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T02:07:39Z","timestamp":1776132459000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1364815226000897"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":79,"alternative-id":["S1364815226000897"],"URL":"https:\/\/doi.org\/10.1016\/j.envsoft.2026.106942","relation":{},"ISSN":["1364-8152"],"issn-type":[{"value":"1364-8152","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Untethered from earthly constraints: A spatial seven-day ahead machine-learning forest fuel moisture forecasting system, independent of real-time sensor networks","name":"articletitle","label":"Article Title"},{"value":"Environmental Modelling & Software","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.envsoft.2026.106942","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"106942"}}