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During the 2019–2020 Australian bushfire season, large expanses (~47%) of agricultural and forested land in the Upper Murray River catchment of southeastern (SE) Australia were burned. Storm activity and rainfall following the fires increased sediment loads in rivers, resulting in localized fish kills and widespread water‐quality deterioration. We collected water samples from the headwaters of the Murray River for sediment and contaminant analysis and assessed changes in water quality using long‐term monitoring data. A robust runoff routing model was used to estimate the effect of fire on sediment loads in the Murray River. Peak turbidity in the Murray River reached values of up to 4200 nephelometric turbidity units (NTU), shown as pitch‐black water coming down the river. The increase in suspended solids was accompanied by elevated nutrient concentrations during post‐bushfire runoff events. The model simulations demonstrated that the sediment load could be five times greater in the first year after a bushfire than in the prefire condition. It was estimated that Lake Hume, a large reservoir downstream from fire‐affected areas, would receive a maximum of 600 000 metric tonnes of sediment per month in the period immediately following the bushfire, depending on rainfall. Total zinc, arsenic, chromium, nickel, copper, and lead concentrations were above the 99% toxicant default guideline values (DGVs) for freshwater ecosystems. It is also likely that increased nutrient loads in Lake Hume will have ongoing implications for algal dynamics, in both the lake and the Murray River downstream. Information from this study provides a valuable basis for future research to support bushfire‐related policy developments in fire‐prone catchments and the mitigation of postfire water quality and aquatic ecosystem impacts. Integr Environ Assess Manag 2021;17:1203–1214. © 2021 Commonwealth of Australia. Integrated Environmental Assessment and Management © 2021 Society of Environmental Toxicology & Chemistry (SETAC). KEY POINTS: This study provides information useful to our understanding of bushfire impacts on water quality.Heavy rainfall after the fires discharged large volumes of ash and sediment into the Murray River, resulting in widespread deterioration of water quality and localized fish kills.Even six months after fires, runoff from the burned catchment was still carrying large amounts of sediments, nutrients, and carbon.The new modeling method can be applied elsewhere to prepare for the adverse effects of rain following a bushfire by minimizing sediment in runoffs. [ABSTRACT FROM AUTHOR]

A field-based experimental study was conducted in 50 × 50 m square plots to investigate the behaviour of free-spreading fires in wheat to quantify the effect of crop condition (i.e. harvested, unharvested and harvested and baled) on the propagation rate of fires and their associated flame characteristics, and to evaluate the adequacy of existing operational prediction models used in these fuel types. The dataset of 45 fires ranged from 2.4 to 10.2 km h−1 in their forward rate of fire spread and 3860 and 28 000 kW m−1 in fireline intensity. Rate of fire spread and flame heights differed significantly between crop conditions, with the unharvested condition yielding the fastest spreading fires and tallest flames and the baled condition having the slowest moving fires and lowest flames. Rate of fire spread in the three crop conditions corresponded directly with the outputs from the models of Cheney et al. (1998) for grass fires: unharvested wheat → natural grass; harvested wheat (~0.3 m tall stubble) → grazed or cut grass; and baled wheat (<0.1 m tall stubble) → eaten-out grass. These models produced mean absolute percent errors between 21% and 25% with reduced bias, a result on par with the most accurate published fire spread model evaluations. Field-scale fire experiments were conducted to quantify the effect of wheat crop condition on fire behaviour. Data were used to evaluate existing fire spread models applied operationally to forecast fire propagation in grass and croplands in Australia. These models were shown to adequately predict the rate of fire spread in wheat crops. [ABSTRACT FROM AUTHOR]

Electricity distribution infrastructure causes fewer wildfires than most other sources of ignition. However, these fires have been associated with more severe consequences than those from other causes. This paper examines whether fires caused by faults in electricity distribution infrastructure occur more often during periods of elevated fire danger, thereby increasing their consequence. The occurrence of wildfires caused by electricity distribution infrastructure were compared to those attributed to other causes during periods of elevated fire danger across the State of Victoria, Australia, where historically such fires have had significant impact on lives and assets of value. The results provided strong evidence that fires caused by electrical faults are more prevalent during elevated fire danger conditions and that they burn larger areas than fires ignited by most other causes. As a result the consequences of fires caused by electricity infrastructure are worse than fires from other causes. This knowledge highlights the importance of mitigating ignition-causing faults in the electricity network, particularly on days of elevated fire danger. [ABSTRACT FROM AUTHOR]

Fire behaviour and spread predictions guides suppression strategies and public warnings during wildfires. The scientific understanding of fire behaviour forms the core of these predictions, but is incomplete, and expert judgement and experience are required to augment the evidence based knowledge. Amicus is a new decision support system that implements contemporary, published and operationalised bushfire behaviour models (e.g. rate of spread, flame height, fireline intensity, spotting distance) in the Australian bushfire context. It enables the inclusion of expert judgement and local knowledge, allows users to analyse temporal trends and uncertainty in inputs, and facilitates reliable and practical predictions. This paper provides a comprehensive overview of Amicus, including its operation and functionality, identifies the boundaries of the current understanding of fire science, discusses the major limitations in existing knowledge, and provides a framework for allowing deterministic and anecdotal/local knowledge to be incorporated into formal fire behaviour predictions. [ABSTRACT FROM AUTHOR]

A suite of models was used to examine the links between climate, fuels and fire behaviour in dry eucalypt forests in south-eastern Australia. Predictions from a downscaled climate model were used to drive models of fuel amount, the moisture content of fuels and two models of forest fire behaviour at a location in western Sydney in New South Wales, Australia. We found that a warming and drying climate produced lower fine fuel amounts, but greater availability of this fuel to burn due to lower moisture contents. Changing fuel load had only a small effect on fuel moisture. A warmer, drier climate increased rate of spread, an important measure of fire behaviour. Reduced fuel loads ameliorated climate-induced changes in fire behaviour for one model. Sensitivity analysis of the other fire model showed that changes in fuel amount induced changes in fire behaviour of a similar magnitude to that caused directly by sensitivity to climate. Projection of changes in fire risk requires modelling of changes in vegetation as well as changes in climate. Better understanding of climate change effects on vegetation structure is required. [ABSTRACT FROM AUTHOR]

Abstract Environmental cycling of the toxic metal mercury (Hg) is ubiquitous, and still not completely understood. Volatilisation and emission of mercury from vegetation, litter and soil during burning represents a significant return pathway for previously-deposited atmospheric mercury. Rates of such emission vary widely across ecosystems as they are dependent on species-specific uptake of atmospheric mercury as well as fire return frequencies. Wildfire burning in Australia is currently thought to contribute between 1 and 5% of the global total of mercury emissions, yet no modelling efforts to date have utilised local mercury emission factors (mass of emitted mercury per mass of dry fuel) or local mercury emission ratios (ratio of emitted mercury to another emitted species, typically carbon monoxide). Here we present laboratory and field investigations into mercury emission from burning of surface fuels in dry sclerophyll forests, native to the temperate south-eastern region of Australia. From laboratory data we found that fire behaviour — in particular combustion phase — has a large influence on mercury emission and hence emission ratios. Further, emission of mercury was predominantly in gaseous form with particulate-bound mercury representing <1% of total mercury emission. Importantly, emission factors and emission ratios with respect to carbon monoxide and carbon dioxide, from both laboratory and field data all show that gaseous mercury emission from biomass burning in Australian dry sclerophyll forests is currently overestimated by around 60%. Based on these results, we recommend a mercury emission factor of 28.7 ± 8.1 μ g Hg kg−1 dry fuel, and emission ratio of gaseous elemental mercury relative to carbon monoxide of 0.58 ± 0.01 × 10−7, for estimation of mercury release from the combustion of Australian dry sclerophyll litter. Highlights • Wildfire mercury release from eucalypt forests is currently overestimated by 60%. • Under natural wildfire fuel moistures, 99% of release is elemental mercury. • Fire progression impacts heavily; most mercury is released during flaming stage. • Recommended emission ratio for GEM/CO is 0.58 ± 0.01 × 10−7. [ABSTRACT FROM AUTHOR]

Analysis of growth and biomass turnover in natural forests of Eucalyptus regnans, the world's tallest angiosperm, reveals it is also the world's most productive forest type, with fire disturbance an important mediator of net primary productivity (NPP). A comprehensive empirical database was used to calculate the averaged temporal pattern of NPP from regeneration to 250 years age. NPP peaks at 23.1 ± 3.8 (95% interquantile range) Mg C ha -1  year -1 at age 14 years, and declines gradually to about 9.2 ± 0.8 Mg C ha -1  year -1 at 130 years, with an average NPP over 250 years of 11.4 ± 1.1 Mg C ha -1  year -1 , a value similar to the most productive temperate and tropical forests around the world. We then applied the age-class distribution of E. regnans resulting from relatively recent historical fires to estimate current NPP for the forest estate. Values of NPP were 40% higher (13 Mg C ha -1  year -1 ) than if forests were assumed to be at maturity (9.2 Mg C ha -1  year -1 ). The empirically derived NPP time series for the E. regnans estate was then compared against predictions from 21 global circulation models, showing that none of them had the capacity to simulate a post-disturbance peak in NPP, as found in E. regnans. The potential importance of disturbance impacts on NPP was further tested by applying a similar approach to the temperate forests of conterminous United States and of China. Allowing for the effects of disturbance, NPP summed across both regions was on average 11% (or 194 Tg C/year) greater than if all forests were assumed to be in a mature state. The results illustrate the importance of accounting for past disturbance history and growth stage when estimating forest primary productivity, with implications for carbon balance modelling at local to global scales., (© 2018 John Wiley & Sons Ltd.)