Academic literature on the topic 'Prescribed burning Australia Mathematical models'
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Journal articles on the topic "Prescribed burning Australia Mathematical models"
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Florec, Veronique, Michael Burton, David Pannell, Joel Kelso, and George Milne. "Where to prescribe burn: the costs and benefits of prescribed burning close to houses." International Journal of Wildland Fire 29, no. 5 (2020): 440. http://dx.doi.org/10.1071/wf18192.
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Prescribed burning is used in Australia as a tool to manage fire risk and protect assets. A key challenge is deciding how to arrange the burns to generate the highest benefits to society. Studies have shown that prescribed burning in the wildland–urban interface (WUI) can reduce the risk of house loss due to wildfires, but the costs and benefits of different arrangements for prescribed burning treatments have rarely been estimated. In this study, we use three different models to explore the costs and benefits of modifying the spatial arrangement of prescribed burns on public land, using the south-west of Western Australia as a case study. We simulate two hypothetical scenarios: landscape treatments and WUI treatments. We evaluate the long-term costs and benefits of each scenario and compare the results from the three models, highlighting the management implications of each model. Results indicate that intensifying prescribed burning treatments in public land in the WUI achieves a greater reduction in damages compared with applying the majority of the treatments in rural areas. However, prescribed burning in the WUI is significantly more expensive and, despite additional benefits gained from this strategy, in most cases it is not the most economically efficient strategy.
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Gould, JS, I. Knight, and AL Sullivan. "Physical Modelling of Leaf Scorch Height From Prescribed Fires in Young Eucalyptus Sieberi Regrowth Forests in South-Eastern Australia." International Journal of Wildland Fire 7, no. 1 (1997): 7. http://dx.doi.org/10.1071/wf9970007.
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Information on weather, fuel and fire behaviour were recorded on 56 experimental prescribed fires in young coastal silvertop ash (Eucalyptus sieberi) regrowth forest in south-east New South Wales, Australia. The thermal environment above the fire was measured in 14 of those fires. Existing plume models, based on the assumption of a uniformly burning line fire, were found to under-predict the temperature of the air rising into the canopy. An axially symmetric plume model, based on the observation that fires burning in non-uniform fuels are not uniformly burning line fires, was developed using standard plume rise equations. This model, called the Sporadic Axial Model (SAM), was calibrated using data from one fire. This model can be used to predict scorch height from known ambient temperature and Byram's fire line intensity. The SAM model suggests that scorch height will be greater for prescribed fires burnt under calm conditions than prescribed fires of the same intensity burnt under stronger wind conditions.
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Howard, Trevor, Neil Burrows, Tony Smith, Glen Daniel, and Lachlan McCaw. "A framework for prioritising prescribed burning on public land in Western Australia." International Journal of Wildland Fire 29, no. 5 (2020): 314. http://dx.doi.org/10.1071/wf19029.
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A risk-based framework for targeting investment in prescribed burning in Western Australia is presented. Bushfire risk is determined through a risk assessment and prioritisation process. The framework provides principles and a rationale for programming fuel management with indicators to demonstrate that bushfire risk has been reduced to an acceptable level. Indicators provide targets for fuel management that are applicable throughout the state and can be customised to meet local circumstances. The framework identifies eight bushfire risk management zones having broad consistency of land use, fire environment and management approach, which combine to create a characteristic risk profile. Thirteen fuel types based primarily on structural attributes of the vegetation that influence fire behaviour are recognised and used to assign models for fuel accumulation and fire behaviour prediction. Each bushfire risk management zone is divided into fire management areas, based on the management intent. These are areas where fuels will be managed primarily to minimise the likelihood of fire causing adverse impacts on human settlements or critical infrastructure, to reduce the risk of bushfire at the landscape scale or to achieve other land management outcomes. Indicators of acceptable bushfire risk are defined for each fire management area and are modified according to the distribution of assets and potential fire behaviour in the landscape. Risk criteria established in the framework can be converted to spatially represented targets for fuel management in each zone and can be reported against to measure the effectiveness of the fuel management program. In areas where the primary intent is to reduce the risk of bushfire at the landscape scale, managers have flexibility to apply prescribed fire in ways that maintain and enhance ecosystem services, nature conservation and landscape values through variation in the seasonality, intensity and scale of planned burning.
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Dyer, Rodd, and Mark Stafford Smith. "Ecological and economic assessment of prescribed burning impacts in semi-arid pastoral lands of northern Australia." International Journal of Wildland Fire 12, no. 4 (2003): 403. http://dx.doi.org/10.1071/wf03026.
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Pastoral managers in savannas face difficult decisions about trading off short-term use of grass biomass for animal production against its longer term use as fuel to manage tree–grass balances with fire. This study develops a model to represent the interactions between seasonal variability, fire behaviour, tree response, pasture growth and condition, grazing utilisation and animal productivity in a grazed savanna ecosystem. It successfully integrates simplified versions of several existing models, results of local research and expert knowledge to permit economic evaluation of tradeoffs given various fire treatments. The modelling framework also enabled the effects of wildfire events to be simulated and allowed fire and livestock management costs and revenue to be quantified. Applied to one site and climate sequence, the initial results assuming constant stocking rates show the importance of burning for the long-term maintenance of productivity, and suggest that some level of late dry season fire is needed for this. Net present values of applying different fire regimes over different time horizons emphasise the factors that pastoralists must take into account in making decisions about preferred fire regimes.
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Storey, Michael, Owen Price, and Elizabeth Tasker. "The role of weather, past fire and topography in crown fire occurrence in eastern Australia." International Journal of Wildland Fire 25, no. 10 (2016): 1048. http://dx.doi.org/10.1071/wf15171.
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We analysed the influence of weather, time since fire (TSF) and topography on the occurrence of crown fire, as mapped from satellite imagery, in 23 of the largest wildfires in dry sclerophyll forests in eastern Australia from 2002 to 2013. Fires were analysed both individually and as groups. Fire weather was the most important predictor of crown consumption. TSF (a surrogate for fuel accumulation) had complex nonlinear effects that varied among fires. Crown fire likelihood was low up to 4 years post-fire, peaked at ~10 years post-fire and then declined. There was no clear indication that recent burning became more or less effective as fire weather became more severe. Steeper slope reduced crown fire likelihood, contrary to the assumptions of common fire behaviour equations. More exposed areas (ridges and plains) had higher crown fire likelihood. Our results suggest prescribed burning to maintain an average of 10 years’ TSF may actually increase crown fire likelihood, but burning much more frequently can be effective for risk reduction. Our results also suggest the effects of weather, TSF and slope are not adequately represented in the underlying equations of most fire behaviour models, potentially leading to poor prediction of fire spread and risk.
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Log, Torgrim. "Modeling Drying of Degenerated Calluna vulgaris for Wildfire and Prescribed Burning Risk Assessment." Forests 11, no. 7 (July 14, 2020): 759. http://dx.doi.org/10.3390/f11070759.
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Research highlights: Moisture diffusion coefficients for stems and branches of degenerated Calluna vulgaris L. have been obtained and a mathematical model for the drying process has been developed and validated as an input to future fire danger modeling. Background and objectives: In Norway, several recent wildland–urban interface (WUI) fires have been attributed to climate changes and accumulation of elevated live and dead biomass in degenerated Calluna stands due to changes in agricultural activities, i.e., in particular abandonment of prescribed burning for sheep grazing. Prescribed burning is now being reintroduced in these currently fire prone landscapes. While available wildfire danger rating models fail to predict the rapidly changing fire hazard in such heathlands, there is an increasing need for an adapted fire danger model. The present study aims at determining water diffusion coefficients and develops a numerical model for the drying process, paving the road for future fire danger forecasts and prediction of safe and efficient conditions for prescribed burning. Materials and methods: Test specimens (3–6 mm diameter) of dead Calluna stems and branches were rain wetted 48 h and subsequently placed in a climate chamber at 20 °C and 50% relative humidity for mass loss recordings during natural convection drying. Based on the diameter and recorded mass versus time, diffusion coefficients were obtained. A numerical model was developed and verified against recoded mass loss. Results: Diffusion coefficients were obtained in the range 1.66–10.4 × 10−11 m2/s. This is quite low and may be explained by the very hard Calluna “wood”. The large span may be explained by different growth conditions, insect attacks and a varying number of years of exposure to the elements after dying. The mathematical model described the drying process well for the specimens with known diffusion coefficient. Conclusions: The established range of diffusion coefficients and the developed model may likely be extended for forecasting moisture content of degenerated Calluna as a proxy for fire danger and/or conditions for efficient and safe prescribed burning. This may help mitigate the emerging fire risk associated with degenerated Calluna stands in a changing climate.
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Loh, Z. M., R. M. Law, K. D. Haynes, P. B. Krummel, L. P. Steele, P. J. Fraser, S. Chambers, and A. Williams. "Simulations of atmospheric methane for Cape Grim, Tasmania, to constrain South East Australian methane emissions." Atmospheric Chemistry and Physics Discussions 14, no. 15 (August 19, 2014): 21189–221. http://dx.doi.org/10.5194/acpd-14-21189-2014.
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Abstract. This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E). The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS) and the CSIRO Conformal-Cubic Atmospheric Model (CCAM). Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air samples that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September-October-November), rather than winter, maximum for wetland emissions.
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Loh, Z. M., R. M. Law, K. D. Haynes, P. B. Krummel, L. P. Steele, P. J. Fraser, S. D. Chambers, and A. G. Williams. "Simulations of atmospheric methane for Cape Grim, Tasmania, to constrain southeastern Australian methane emissions." Atmospheric Chemistry and Physics 15, no. 1 (January 13, 2015): 305–17. http://dx.doi.org/10.5194/acp-15-305-2015.
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Abstract. This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E). The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS) and the CSIRO Conformal-Cubic Atmospheric Model (CCAM). Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air samples that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a~methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September–October–November), rather than winter, maximum for wetland emissions.
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Sitters, Holly, Julian Di Stefano, Fiona J. Christie, Paul Sunnucks, and Alan York. "Bird diversity increases after patchy prescribed fire: implications from a before–after control–impact study." International Journal of Wildland Fire 24, no. 5 (2015): 690. http://dx.doi.org/10.1071/wf14123.
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Increasingly, patchy prescribed fire of low severity is used by land managers to mitigate wildfire risk, but there are relatively few experimental studies on the effects of low-severity fire on fauna. We used a before–after control–impact experiment to examine avian responses to prescribed fire at two scales in topographically variable, tall-open eucalypt forest in south-east Australia. We surveyed birds at control and impact areas twice before and twice after fire, and applied mixed models to investigate responses of avian turnover, richness and the occurrence of selected species. Approximately half of the impact area was burnt and topographic variation generated a finger-like configuration of burnt patches on ridges and unburnt patches in gullies. Our findings at the smaller scale (0.8 ha) indicated that the fire resulted in increased bird diversity because a patchwork of burnt and unburnt areas provided a mosaic of distinct successional states in which different species occurred. Additionally, we found that the effect of fire on species richness and occurrence was a function of the presence of unburnt topographic refuges. In contrast, we found no compelling evidence to suggest that birds responded to the fire at the larger scale (400 ha). We conclude that application of low-severity fire in a patchy manner enhanced avian diversity and facilitated the persistence of the birds detected in pre-fire surveys. Although the levels of patchiness required to sustain diverse taxa warrant further study, our findings highlight the importance of formally incorporating patchiness into prescribed burning for the ecologically sensitive management of contemporary landscapes.
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Kukkonen, J., J. Nikmo, M. Sofiev, K. Riikonen, T. Petäjä, A. Virkkula, J. Levula, S. Schobesberger, and D. M. Webber. "Applicability of an integrated plume rise model for the dispersion from wild-land fires." Geoscientific Model Development Discussions 7, no. 1 (January 16, 2014): 483–527. http://dx.doi.org/10.5194/gmdd-7-483-2014.
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Abstract. We have presented an overview of a mathematical model, BUOYANT, that was originally designed for the evaluation of the dispersion of buoyant plumes originated from major warehouse fires. The model addresses the variations of the cross-plume integrated properties of a buoyant plume in the presence of a vertically varying atmosphere. The model also includes a treatment for a rising buoyant plume interacting with an inversion layer. We have compared the model predictions with the data of two prescribed wild-land fire experiments. For the SCAR-C experiment in Quinault (US) in 1994, the predicted vertical extents of the plume at maximum plume rise were between 500–800 m and 200–700 m, using two alternative meteorological datasets. The corresponding observed injection heights of the aerosol particles measured using an airborne LIDAR (LIght Detection And Ranging) ranged from 250 and 600 m. For the prescribed burning experiment in Hyytiälä (Finland) in 2009, the model predictions were compared with plume elevations and diameters, determined based on particulate matter number concentration measurements on board an aeroplane. The agreement of modelled and measured results was good, provided that one assumes the measured maximum convective heat fluxes as input data for the model. The results demonstrate that in field experiments on wild-land fires, there are substantial uncertainties in estimating both (i) the source terms for the atmospheric dispersion computations, and (ii) the relevant vertical meteorological profiles. The results provide more confidence that cross-plume integrated mathematical models, such as the BUOYANT model, can be used to fairly good accuracy for evaluating the dispersion from major wild-land fires.
Dissertations / Theses on the topic "Prescribed burning Australia Mathematical models"
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Sutherland, Elaine Kennedy. "The effect of prescribed burning on southwestern ponderosa pine growth." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184954.
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Study objectives included determining whether prescribed burning affected ponderosa pine growth; mathematically modeling the growth response to burning; and determining whether forest management history affected growth response. I sampled 188 trees from two areas near Flagstaff, Arizona; one area (Brannigan Flat) had been logged and thinned, and the other (Chimney Spring) had not; both were burned in 1976. Within each study area, control and burned plots were of similar age, vigor, height, and competition index. Trees at Chimney Spring were older, less vigorous, and taller, and had a higher competition index than at Brannigan. For each tree, periodic basal area increment (PBAI) was calculated for the years 1974-1984. To determine which variable would best model growth, postfire PBAI (individual years, 1977-1984) was correlated with previous growth (average PBAI 1974-1976); crown ratio; competition index; thinning index; and diameter. Two models of growth response were developed; one oriented toward satisfying theoretical and research goals, and the other, toward management applications. Growth was modeled using stepwise multiple linear regression, and the dependent variable was postfire PBAI. Research Model independent variables were previous growth, years (climate), and treatment-year interaction, and 72% of total variance was explained. Fire affected growth significantly and negatively for two years, and then burned trees grew similarly to control trees. Management Model independent variables were crown ratio, competition index, crown ratio, subject tree diameter, year, and treatment, and 52% of total variance was explained. This model, too, indicated a slight negative effect of burning on growth. Management history was not a significant determinant of growth response. Both models validated well; the ratio of observed-to-predicted residual mean square was 1.04 and 0.91 (Research and Management Models, respectively). Thinning index was not significantly related to postfire growth, but a change in carbohydrate allocation from stem wood to crown and root expansion could have resulted in observed burning effects. Management implications include (1) short-term growth decline may result from burning, (2) management history did not affect growth response, and (3) burning impact is greatest in dense stands of small trees.
Books on the topic "Prescribed burning Australia Mathematical models"
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Wright, Clinton S. Estimating volume, biomass, and potential emissions of hand-piled fuels. Portland, Or: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2010.
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Keane, Robert E. FIRE-BGC, a mechanistic ecological process model for simulating fire succession on coniferous forest landscapes of the northern Rocky Mountains. Ogden, UT: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1996.
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Keane, Robert E. FIRE-BGC, a mechanistic ecological process model for simulating fire succession on coniferous forest landscapes of the northern Rocky Mountains. Ogden, UT: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1996.
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Chinanzvavana, Stephen. Numerical analysis of heat transfer in soil as applied during open field burning. 1986.
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FIRE-BGC--a mechanistic ecological process model for simulating fire succession on coniferous forest landscapes of the northern Rocky Mountains. Ogden, UT (324 25th St., Ogden 84401): U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1996.
Find full textBook chapters on the topic "Prescribed burning Australia Mathematical models"
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Parkins, Kate, Brett Cirulis, Lauren Bennett, and Trent Penman. "Characterising and managing fire risks to plantations under changing climates." In Advances in Forest Fire Research 2022, 1423–29. Imprensa da Universidade de Coimbra, 2022. http://dx.doi.org/10.14195/978-989-26-2298-9_216.
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Wildfires are a common threat to the sustainability of commercial plantations in fire-prone regions. Large losses of plantations from wildfires can lead to the disruption of forest yield, with flow-on impacts to downstream industries, resulting in significant social and economic impacts to local communities. Future climate projections indicate an increase in wildfire activity, including increases in fire extent, severity or frequency in many fire-prone ecosystems. Land and fire management agencies around the world invest significant resources to reduce the likelihood and impact of future fires and increase the capacity for fire suppression. However, we currently know very little about how commercial plantations will be impacted by fire as the climate changes, or if strategic management can mitigate some of these risks into the future. In this study we sought to quantify fire risks to plantations and nearby community assets under current and changing climates; and to evaluate the effectiveness of management options for mitigating some of these risks under changing climates. This research included the customisation of a fire simulation tool for use in plantation landscapes by developing plantation-specific fuel functions (derived from field-sampling in hardwood and softwood plantations around Australia) that were integrated into fire spread models. To quantify longer-term risks, these advancements were also integrated into a stochastic fire regime simulator (FROST– Fire Regimes and Operation Simulation Tool) that is proposed for future use in operational risk assessments. Fire risks to both environmental and community assets were evaluated under current and changing climates to support evidence-based management to help guide investment, insurance negotiations, and fire mitigation in the plantation sector. The fire regime simulator (FROST) was also used to evaluate a range of different management options for reducing risk as a basis for efficient allocation of fire prevention and response resources both by plantation growers and by broader fire regions. We found that reducing suppression response times (to 15 minutes or less for all ignitions) and the current approach to management (a construction rate of 2km/h for suppression and 15-minute response times, with 4000ha/year of prescribed burning) were consistently the best management strategies for reducing fire risks to plantations and adjacent communities, regardless of the climate model used. These strategies offer the greatest scope for reducing future wildfire risks to plantation assets and adjacent communities as the climate changes. High pruning in strategic locations may also be worthy of future investment but should be considered in combination with more rapid suppression and prescribed burning. Plantation owners currently have little influence over the amount and location of prescribed burning adjacent to plantations, and fuel reduction burning is not regularly undertaken in Australian plantations. Therefore, rapid suppression response times is the single best investment for minimising impact to plantation assets under a hotter or drier climate.
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Lyell, Christopher Sean, Usha Nattala, Rakesh Chandra Joshi, Zaher Joukhadar, Jonathan Garber, Simon Mutch, Assaf Inbar, et al. "A forest fuel dryness forecasting system that integrates an automated fuel sensor network, gridded weather, landscape attributes and machine learning models." In Advances in Forest Fire Research 2022, 21–27. Imprensa da Universidade de Coimbra, 2022. http://dx.doi.org/10.14195/978-989-26-2298-9_1.
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Accurate and timely forecasting of forest fuel moisture is critical for decision making in the context of bushfire risk and prescribed burning. The moisture content in forest fuels is a driver of ignition probability and contributes to the success of fuel hazard reduction burns. Forecasting capacity is extremely limited because traditional modelling approaches have not kept pace with rapid technological developments of field sensors, weather forecasting and data-driven modelling approaches. This research aims to develop and test a 7-day-ahead forecasting system for forest fuel dryness that integrates an automated fuel sensor network, gridded weather, landscape attributes and machine learning models. The integrated system was established across a diverse range of 30 sites in south-eastern Australia. Fuel moisture was measured hourly using 10-hour automated fuel sticks. A subset of long-term sites (5 years of data) was used to evaluate the relative performance of a selection of machine learning (Light Gradient Boosting Machine (LightGBM) and Recurrent Neural Network (RNN) based Long-Short Term Memory (LSTM)), statistical (VARMAX) and process-based models. The best performing models were evaluated at all 30 sites where data availability was more limited, demonstrating the models' performance in a real-world scenario on operational sites prone to data limitations. The models were driven by daily 7-day continent-scale gridded weather forecasts, in-situ fuel moisture observation and site variables. The model performance was evaluated based on the capacity to successfully predict minimum daily fuel dryness within the burnable range for fuel reduction (11 – 16%) and bushfire risk (