Water colour, derived from chromophoric dissolved organic matter (cDOM), is a key indicator of water quality. Increasing water colour trends worldwide and in Australia have raised concerns, yet the drivers of colour variability in natural ecosystems remain poorly understood. We aimed to investigate the drivers of spatial and temporal variability of water colour generation across well-drained temperate forested catchments in south-eastern Australia and tested its use as a proxy for dissolved organic carbon (DOC). Baseflow colour was measured across a diverse topographical range to model spatial variability, while automatic samplers captured temporal variability during rainfall events. Our spatial model explained 87

Forest structure, through its three-dimensional arrangement of foliage and wood, moderates the climate, creating a microclimate that is more stable than the climate outside the forest in a process known as microclimate buffering. This study aimed to improve understanding of the relationship between forest structure and microclimate buffering of daily maximum temperature (T-max.) and vapour pressure deficit (VPDmax.) in temperate evergreen forests. Forest structure assessments and microclimate monitoring across eight sites in temperate Australia revealed significant variation in microclimate buffering, primarily driven by canopy closure, leaf area index (LAI), and tree stem density (>= 10-cm diameter). Compared to open sites, closed forests (>70 % canopy cover) reduced mean T-max. by 1.8 +/- 0.08 degrees C to 4.1 +/- 0.09 degrees C, and open forests (30-70 % canopy cover) by 0.2 +/- 0.08 degrees C to 0.4 +/- 0.06 degrees C. Only closed forests reduced mean VPDmax., by 0.15 +/- 0.01 kPa to 0.43 +/- 0.02 kPa, while mean VPDmax. in open forests and woodlands was 0.04 +/- 0.01 kPa to 0.38 +/- 0.02 kPa higher than open sites respectively, indicating net drying. Across the forest structure gradient, canopy closure, LAI and stem density had significant negative relationships with microclimate offsets of daily T-max. and VPDmax. Over the assessed forest structure range, T-max. offsets were negative (buffering) above 35 % canopy closure, 137 stems ha(-1), and LAI 0.36, while VPDmax. offsets were negative above 59 % canopy closure, 485 stems ha(-1), and LAI 0.82. These findings emphasize the role of forest structure in microclimate buffering and potential climate resilience.

South-eastern Australian forested catchments supply most of Melbourne's drinking water, and discoloured water poses significant challenges for authorities because of the need for complex and costly treatment procedures. Identifying the sources and mechanisms of colour production is therefore critical. We investigated the role of leaf litter from five common catchment tree species in generating water colour under three moisture conditions (Saturated, Moist and Air-dry) by conducting a laboratory leaching experiment. Results showed that leaf litter under Moist conditions (2871.2 +/- 383.24 PCU) produced significantly higher cumulative colour compared with Saturated (496 +/- 98.34 PCU) and Air-dry (452.2 +/- 62.67 PCU) conditions. This is likely due to optimal microbial decomposition under Moist conditions, where both oxygen and water availability are sufficient. In contrast, Saturated samples exhibited a faster initial rate of colour production that peaked earlier (Week 1) than Moist (Week 2) and Air-dry (Week 4) samples, likely driven by a combination of leaching and decomposition processes. In Moist and Saturated samples, decomposition was strongly correlated with the colour generation process. When species effects are considered, Eucalyptus radiata had the highest cumulative colour production (1711.33 +/- 892.61 PCU), whereas Eucalyptus regnans had the lowest (730 +/- 320.44 PCU). Our findings highlight the critical role of litter moisture in driving colour generation in drinking water catchments. Future research should focus on understanding how changes in rainfall patterns and subsequent litter moisture levels may influence colour production. Such insights could inform management strategies to mitigate water discolouration and reduce treatment costs.

Potential heat release (PHR) is the theoretical maximum amount of heat releasable by wildland fuels during fire and is a key determinant of fireline intensity. Understanding its variability and dynamics is important for predicting fire behavior and effects on ecosystems. In this study, we sought to understand PHR and its drivers at the forest-stand scale. We quantified PHR for stands of wet sclerophyll forest in south-eastern Australia from field measurements of fine fuel loads, fuel moisture content, and calorific values for each fuel type. We determined the effects of species composition and live-to-dead ratio on stand-level PHR by integrating forest composition data from another study in the same forest type. PHR varied from 19.8 to 77.6 MJ m−2 between the sites surveyed. Large differences in PHR between forest stands were primarily due to substantial differences in fuel loads and the calorific values of eucalypt versus non-eucalypt litter. Litter and canopy fuels were the primary contributors to stand-level PHR ( 40

Soil erosion rates after wildfire are strongly controlled by intrinsic properties such as topography, weather, climate, soil, and vegetation. These landscape and hydroclimatic properties are important in determining postfire erosion rates; however, their influence on post-fire erosion and their interaction with the intensity of a wildfire remains uncertain. A key limitation in resolving this uncertainty is the lack of conceptual models and frameworks for organising data related to the geomorphic sensitivity of landscapes to wildfire. Our aim is to develop a framework for consolidating understanding of post-fire erosion in the context of hydroclimatic conditions which contribute to system states, for example soil and vegetation properties, and wildfire regime. The framework is developed around a simple conceptual model where the change in erosion due to wildfire is a product of change in runoff generation and sediment supply, which is strongly related to landscape net primary productivity (NPP). We hypothesised that geomorphic sensitivity to wildfire should vary as a unimodal humped relationship across a gradient of NPP, peaking at an intermediate level. To develop this framework and to test the hypothesis, we first review intrinsic soil and vegetation properties related to the supply and transport of sediment from burned and unburned hillslopes. Net primary productivity is systematically related to these intrinsic properties because it integrates many processes involved in soil and vegetation development. Empirical data indicate a trend in the change in surface runoff generation with NPP after wildfire, peaking at an NPP of approximately 15 Mg C ha-1 y-1. A simple model of fuel availability and soil heating are correlated with a similar "humped" trend in sediment supply. These results are consistent with our conceptual model, which indicates that sediment supply and runoff contribute towards a distinct peak in wildfire effects on erosion at an intermediate level of NPP. We propose that landscapes of intermediate NPP typically have the highest quantity of fuel available to burn, which cause large changes to the soil surface properties. Landscapes at intermediate NPP also tend to produce intrinsic soil and vegetation properties that promote erosion after wildfire. The interplay between these short and long-term landscape characteristics is strongest at intermediate levels of NPP. Our proposed biogeographic model of geomorphic sensitivity to wildfire was supported by erosion data from burned hillslope and zero-order catchments studies from a range fire-prone landscapes in Australia and North America. Our proposed conceptual model will help identify areas most vulnerable to post-fire erosion changes.

Post-fire debris flows pose a significant hazard in mountainous regions, but accurate assessment of the associated risk at large scales, particularly in the context of mega-fires, is limited. Although numerous models exist, few are functional at the landscape scale, and none integrate assessments of downstream effects with the likelihood of flow initiation to define both the frequency and magnitude of potential flows. The aim of this work, therefore, was to develop a post-fire debris flow model that could characterise both the occurrence frequency and associated runout of debris flow events and which could be rapidly applied to fire events at the landscape scale. We achieve this using a model integration approach that included the development of a reduced-complexity debris flow runout model, which was calibrated and independently tested for its application at large scales with a dataset of 1377 individual post-fire flows across south-eastern Australia. This model was then integrated with previously published methods determining debris flow source areas and likelihood of initiation specific to our study area. The developed model is intentionally designed for rapid response hazard management. Therefore, it predominantly incorporates only the fundamental, lowest parameter form drivers of debris flow initiation and runout termination, thus minimising computational complexity while ensuring prediction accuracy sufficient for hazard assessment even at application scales as large as mega-fires. Accounting for debris flows initiated from single headwaters and cases where flows simultaneously converge from multiple initiation points, our integrated model effectively characterises debris flow hazard across a geomorphologically diverse landscape encompassing >200,000km(2) (capturing similar to 640,000 potential debris flow initiation locations across Victoria, Australia). Model testing using an independent validation dataset resulted in debris flow runout predictions with root mean square error (RMSE) of 176 and 308 m for non-convergent and convergent flows respectively. Crucially, these predictions can be computed rapidly for large (up to landscape scale) fire events with minimal input requirements and the use of a remotely-sensed observation dataset for domain calibration. As such, the model provides a critical means of addressing the capacity gap in assessments of post-fire debris flow hazard by efficiently integrating measures of occurrence frequency and runout for functional application at large scales. This new work empowers land managers to rapidly predict the hazard arising from post-fire erosion processes and represents an important applied step towards better understanding and mitigating the impacts of wildfire-induced debris flows.

The distributions of vegetation and fire activity are changing rapidly in response to climate warming. In many regions, climate effects on dead fuel moisture content (FMC) are expected to increase future wildfire activity. However, forest FMC is largely driven by microclimate conditions, which are moderated from open weather by vegetation canopies. As shifts in vegetation increase under climate warming, the extent to which future fire activity will be driven by climate directly or associated vegetation shifts remains unresolved. Here, we present a study aimed at quantifying the relative magnitudes of (i) direct climate warming, and (ii) vegetation change, on FMC. Field sites to evaluate these effects were established in a natural laboratory of altered forest states to mature wet temperate forest in south-eastern Australia. FMC was estimated using a process-based model and 48 years of reconstructed climate data. Canopy effects on microclimate were captured by transferring inputs from climate to microclimate using models parameterised with field observations. To evaluate the relative magnitude of climate and vegetation effects, we calculated the maximum difference in mean annual FMC across annual climate replicates and compared this to FMC differences across reorganising forest sites. Our results show vegetation effects on FMC can exceed those related to expected climate change. Changes to forest structure and composition increased (+15.7%) and decreased (-12.3%) mean annual FMC, with a larger negative effect when forest cover was completely removed (-18.5%). In contrast, the largest climate effect on FMC was -6.6% across 48-years of data. Our study demonstrates that the magnitude of vegetation effects on FMC can exceed expected climate change effects. Models of future fire activity that do not account for changing vegetation effects on microclimate are omitting a key biophysical control on FMC and therefore may not be accurately predicting future fire activity.

Post-fire debris flows pose a significant hazard in mountainous regions, but accurate assessment of the associated risk at large scales, particularly in the context of mega-fires, is limited. Although numerous models exist, few are functional at the landscape scale, and none integrate assessments of downstream effects with the likelihood of flow initiation to define both the frequency and magnitude of potential impact. The aim of this work, therefore, was to develop a post-fire debris flow impact model that could characterise both the frequency and magnitude of debris flow events and which could be rapidly applied to fire events at the landscape scale. We achieve this using a model integration approach. This included the development of a reduced-complexity debris flow runout model, which was calibrated and independently tested for its application at large scales with a debris flow dataset of 1377 individual flows across south-eastern Australia. This model was then integrated with previously published methods determining source areas and initiation likelihood specific to our study area. The developed models are intentionally designed for rapid response hazard management. Therefore, they incorporate only the fundamental, lowest parameter form drivers of debris flow initiation and runout termination, thus minimising computational complexity while ensuring prediction accuracy sufficient for risk assessment even at application scales as large as mega-fires. Accounting for debris flows initiated at single headwaters (magnitude one) and flows which converge from multiple initiation points (higher magnitude convergent flows). Our integrated model effectively characterises impact risk across a geomorphologically diverse landscape encompassing more than 200,000km2 (capturing ~640,000 potential debris flow initiation locations across Victoria, Australia). Model testing using an independent validation dataset resulted in debris flow impact predictions with a magnitude one root mean square error (RMSE) of 176m and 308 m for magnitude two convergent flows. Crucially, these predictions can be computed rapidly for large (up to landscape scale) fire events with minimal input requirements and the use of a simple observation dataset for domain calibration. As such, the model provides a critical means of addressing the capacity gap in assessments of post-fire debris flow risk by efficiently integrating measures of impact frequency and magnitude for functional application at large scales. This new work empowers land managers to rapidly predict risk arising from post-fire erosion processes and represents an important applied step towards better understanding and mitigating the impacts of wildfire-induced debris flows.

Climate models predict more frequent droughts and more severe fire weather. Wildfires in wet forests, while historically uncommon, can have catastrophic impacts on forest values and services. Therefore, it is important to ask whether climate change is increasing the frequency of fires in wet forests. Long-term fire histories and weather records were compared in wet Eucalyptus forests supplying water to Melbourne, Australia, to identify the combination of dryness and fire weather under which stand-replacing fires occur. The effect of climate change on stand replacement frequency was predicted using down-scaled regional climate change projections for RCP4.5 and RCP8.5. An index of surface soil dryness (SSD), which is a proxy for live and dead fuel moisture, and daily maximum vapor pressure deficit (D-max), which is a proxy for daily fire weather, were used to rank each day of each fire season from 1900/01 to 2019/20, within 898 km(2) of water supply catchments. The two indices were compared for days with and without stand-replacing fire activity within the study area. Threshold values for the combination of both indices were identified. Damaging fires occurred on about 10 % of days falling above this threshold. The two worst fires, between them burning 86 % of the wet forest in the study area, occurred on days with moderate rather than severe SSD (within the top 2 % of days but only about half of the maximum SSD) but with the most extreme Dmax (highest and second highest ranked out of 43,920 days). The frequency of long fire seasons (SSD > 65 mm for 30 or more days) increased from 1 in similar to 30 years during the 20th century to 1 in 4 years in the past 15 years, due to a doubling in the number of warm dry days (D-max > 2.0 kPa) per fire season. The frequency of extreme fire weather days (D-max > 5.5 kPa) was also higher in the past 15 years than for most of the previous century. These observations suggest that fire frequency and severity are likely to increase in these wet forests, potentially threatening a suite of ecosystem services. Based on regional climate change projections, increases in the frequency of stand replacing fire will be driven more by increases in maximum temperature than by reductions in rainfall. Under RCP4.5, stand replacing fire frequency in the study area could increase from 1 in similar to 140 years historically to 1 in similar to 40 years by 2050 and 1 in similar to 22 years by 2090 (1 in similar to 6 years under RCP8.5), which would result in widespread loss of these iconic forests, including Eucalyptus regnans, the world's tallest Angiosperm.

Seasonal forecast of soil moisture at large spatial scale over forested landscape has numerous implications in forest hydrology and bushfire risk planning. Remotely sensed plant response to rainfall, input meteorological forcing, and site-specific landscape attributes were integrated into a data-driven Gradient Boosting Machine Learning (ML) model to forecast summer season (December to February) soil moisture equivalent to those from Australian Water Resource Assessment-Landscape (AWRA-L) at root-zone (0-1 m) and deep (1-6 m) layers of the soil.Multispectral and thermal infrared bands from MODIS (Band 1-12, LST (day, night)) and meteorological forcing for 2000 - 2018 during and prior to winter (before August) and site-specific landscape attributes were used to generate the explanatory input variables to the model. Spatial and temporal forecasting skills of the model were evaluated using two types of cross-validation: two-fold cross-validation by space over the entire period (2000-2018) and two-fold cross-validation by time for all grid cells (2160 cells). In the first method, the model showed a high skill to forecast deep soil moisture (R2 = 0.81, NSE = 0.79, RMSE = 58.01 mm) and root-zone soil moisture (R2 = 0.65, NSE = 0.63, RMSE = 24.34 mm). In comparison, the second evaluation resulted in more accurate forecast deep-soil moisture (R2 = 0.88, NSE = 0.86, RMSE = 47.39 mm) but in lower performance for root-zone soil (R2 = 0.55, NSE = 0.47, RMSE = 29.2 mm). These outcomes have highlighted that the (>80%) variability in summers deep (1-6 m) soil moisture and (>50%) variability in root-zone (0-1 m) soil moisture over forested landscape can be explained at the end of winters. Furthermore, integrating remotely sensed observations has improved the results by showing an enhancement in the RMSE by 22.8-33.3% in the deep (1-6 m) soil moisture and 8.8-14.3% in root-zone (0-1 m) soil moisture.Overall, the integrated system using remotely sensed plant response, climate forcing and machine learning exhibit great potential to forecast summer soil moisture three months ahead in the Mediterranean climates.

ABSTRACT The Murray-Darling River system is perhaps Australia’s most important, with significant social, cultural and environmental values including 16 Ramsar listed wetlands. The MDB is home to 2.6 million people and produces about $24 billion worth in agricultural production each year (about one-third of total value for Australia). Hydrologic issues, typified by water availability and quality, have existed for many years, peaking during the Millennium drought from 1997 to 2010. Competing interests (i.e. irrigation, tourism, environmental heath), and the declining flows and water quality during droughts, led governments and water management agencies to consider the risks to water resources in the system in the early-mid 2000s. This paper reviews changes to risks associated with forest dynamics, as identified by - afforestation and bushfire – and considers new issues that have emerged since that analysis. It was found that the potential impacts of bushfire on stream flows were over-estimated in past studies, and that a planned significant afforestation expansion into agricultural and grazing land that was projected to reduce stream flows did not occur. While these two risks now do not seem likely to have significant future impacts on flows, or consequent effects on downstream users, the interaction of elevated CO2 and increasing temperatures on vegetation functioning and subsequent hydrologic consequences at catchment scale require further research and analysis. Reduced rainfall and increased temperatures under future climate change are likely to have an impact on inputs and flows. Uncertainties in how these changes, and feedbacks between climate, drought, more frequent fire and vegetation responses, impact on system hydrology also require further investigation.

That streamflow from even-aged forests is a function of forest age (the Kuczera curve) is an accepted paradigm in Australian forest hydrology and less commonly in the Northern Hemisphere. However, none of a dozen stand replacement experiments in Australian obligate seeder forests have faithfully reproduced the Kuczera curve. Here we test an alternative model based on the self-thinning line, showing that both the Kuczera curve and results of subsequent stand replacement experiments can be explained by observed changes in self-thinning after disturbance.Self-thinning in even-aged forests is dictated by the rate of reduction in stocking density as mean tree size increases. Comparison of stand basal area and stocking densities in stands of Eucalyptus regnans F. Muell, re-generated after wildfires in 1851 and 1939, suggested significant differences in self-thinning lines between age cohorts. In three large catchments, a simple forest growth and water use model only reproduced observed substantial long-term reductions in streamflow after stand replacement (mean reduction from 1940 to 1982 of 233 mm year-1) when observed cohort-specific changes in the intercept of the self-thinning line (STL) were incorporated (modelled mean reduction 235 mm year-1). Use of a single STL intercept in both pre-and post -disturbance simulations did not produce the observed streamflow responses (modelled mean reduction 37 mm year-1). Averaged over six E. regnans experimental catchments in which the dominant forest was either partly or completely removed and replaced with the same species, the observed decadal maximum streamflow reduction was only 7 mm year-1, compared to 22 mm year-1 using the model with observed STL intercepts but 200 mm year -1 using the Kuczera curve. Consequently, hydrological responses to disturbance are less predict-able than previously assumed, as the reasons for changes in self-thinning behaviour are not yet understood. We speculate that in this case it is related to variability in seed supply and competition with shorter-lived under -storey species in the early stages of regeneration.

In forest systems, direct shortwave radiation (SWR) plays a vital role in fundamental energy and water processes that require high-resolution modelling at the landscape scale. We propose an alternative approach to modelling high resolution, landscape scale, direct SWR transmittance through forest canopies. This approach utilises airborne LiDAR (AB LiDAR) to calibrate a modified Beer-Lambert Law. Over a three-year period, we established the most comprehensive spatial and temporal sub-canopy dataset of 1-minute pyranometer measurements over 31 diverse sites with varying forest densities and age classes in south-eastern Australia. Measuring below canopy SWR at sub-daily and seasonal variations in zenith angle, as well as peak daily and accumulative radiation loads. The modified Beer-Lambert Law (Rbc = Race-kL), utilises path length through the canopy (L) and AB LiDAR as a representation of the sun's beam to measure transmittance (Rbc/Rac) of above canopy (Rac) to below canopy (Rbc) radiation; To calculate a site-specific extinction coefficient (k). This approach links the theoretical framework of the Beer-Lambert law with the canopy penetrating properties of AB LiDAR, allowing for large-scale spatial extrapolation of SWR transmittance in forest canopies. This differs from previous studies, which either: apply the Beer-Lambert law or the LiDAR penetrating properties separately, use AB LiDAR to represent the vegetation structure from which a Leaf Area Index (LAI) is calculated and transmittance modelled using specific leaf projection functions, or use computationally intense approaches such as ray tracing. These approaches have limitations as they either require site-specific calibration at the point scale, don’t account for seasonal variations in beam penetration angle, are difficult to parameterise across the landscape, or are too computationally intense to feasibly run at the landscape scale. The proposed model combined with LiDAR calibration addresses these limitations as the path length changes with zenith angle, and the calibration of the extinction using LiDAR allows for landscape-level parameterisation in a computationally friendly workflow. With the expanding availability of AB and spaceborne LiDAR, the linking of the penetrating properties of LiDAR with the theoretical concept of the Beer-Lambert law will allow below canopy direct SWR to be modelled with improved accuracy at large scales over daily and seasonal timespans. This improves our ability to model radiation loading below forest canopies across diverse landscapes and terrains, improving the modelling of hydrological, micro-climate, energy and water processes.

Climate-induced fire regimes may change species abundance and species composition in affected forest types, potentially altering pyro-eco-hydrologic feedbacks. In some fire-prone forests across the globe, eco-hydrologic thresholds (changing points, or tipping points, in ecohydrology when vegetation shifts from one steady vegetation to another) are being exceeded due to changes in relationships between climate, fire and vegetation. Following compound disturbances, forests may fail to maintain ecological resilience. Under multiple burn conditions, Eucalyptus regnans F. Muell. forests in south east Australia are highly vulnerable to ecological tipping points. In Victoria, over 189 000 ha of obligate seeder forests have been burned two or more times within 18 years. These short return-interval fires allow Acacia dealbata to become the dominant overstorey species. Such a dramatic species replacement may result in a new evapotranspiration (ET) regime, leading to a new hydrologic state. Stand scale dynamic models were combined with field estimated ET in E. regnans and A. dealbata forests aged 10, 35 and 75/80 years. We found that long-term forest structure, ET and water yield significantly diverge between E. regnans and A. dealbata forests with increasing age. These divergences imply a non-equilibrium state after A. dealbata replaces E. regnans under high-frequency fire conditions. In senescing A. dealbata, understorey transpiration contribution of 29.8% to system ET was similar to that of overstorey transpiration (31.2%), indicating the understorey and overstorey contribute equally to total ET at the final stage of Acacia forests. In contrast, in 75-year-old E. regnans forests, understorey contribution to the total system evapotranspiration is about 16%. This suggests that, after the Acacia life cycle finishes, the ET regime will transit into a new state that will be dominated by shrubby understorey species. Our findings suggest that this climate-induced species replacement would decrease long-term ET, inferring an increase in streamflow.

Management of water resources in the Murray-Darling Basin has historically focussed on water security and the allocation of water for users with competing needs. This focus was reflected in the seminal paper on multiple risks to shared water across the basin by the Commonwealth Scientific and Industrial Research Organisation 15 years ago. That paper captured key concerns that were at the forefront for decision-makers, managers and policy-makers who were, at that time, experiencing the early impacts of the Millennium Drought. Water quality, then, was secondary to the issues of water security. Across the following years, new water quality risks have emerged along with a more nuanced understanding of the complex interplay between climate, floodplain/catchment vegetation, hydrology, and water quality. Critically, this improved understanding applies to the systemic shocks of extreme events, such as the 2020 bushfires and hypoxic blackwater events, as well as the variability, duration and volumes of natural and regulated river flows. In this paper, we explore the key water quality issues that currently face the Basin, and reframe water quality as an integral rather than incidental component of the risks to shared water in the Basin, with the associated implications for policy development that this implies.

Risks to shared water resources in the Murray-Darling Basin are reviewed after the report by CSIRO on the same topic in 2006. CSIRO outlined six major risks to shared water resources in the Basin. Herein, six groups of researchers have reviewed the risks of climate change, forest growth, groundwater, water infrastructure, water quality, and governance. These reviews bring an updated understanding of risk assessment and management that can contribute to the forthcoming reviews of the Water Act and Basin Plan in 2024-26. Drawing on these six papers, the authors synthesise knowledge of the risks to shared water resources and identify policy and management options and information gaps. We find that few risk factors have decreased in significance. Most risks remain and new risks are identified. Water managers must plan for a significant decrease in water availability and governments need to actively manage these risks under conditions of increasing uncertainty.

The world's most iconic forests are under threat from climate change. Climate-fire-vegetation feedback mechanisms are altering the usual successional trajectories of forests. Many obligate seeder forests across the globe are experiencing regeneration failures and subsequent alterations to their recovery trajectories. For example, the persistence of Eucalyptus regnans F. Muell. forests in southeast Australia is highly vulnerable to the effects of climate-driven increases in wildfire frequency. Shortening of the wildfire return interval from >100 years to < 20 years would inhibit or entirely stop regeneration of E. regnans, leading to replacement with understorey species such as Acacia dealbata Link. In this study, it is hypothesised that following such replacement, forest overstorey structure and transpiration will diverge. An experiment was designed to test this hypothesis by measuring and comparing overstorey transpiration and structural properties, including sapwood area and leaf area, between E. regnans and A. dealbata over a chronosequence (10-, 20-, 35- and 75-/80-year-old forests). We found that overstorey structure significantly diverged between the two forest types throughout the life cycle of A. dealbata after age 20. The study revealed strikingly different temporal patterns of water use, indicating a highly significant eco-hydrologic change as a result of this species replacement. Overall, the results provide a strong indication that after age 20, overstorey transpiration in Acacia-dominated forests is substantially lower than in the E. regnans forests they replace. This difference may lead to divergence in water yield from forested catchments where this species replacement is widespread.

As wildfires become more frequent and severe, there are concerns regarding their impacts on water yield from forested catchments. While there are many studies in Australia about the effects of individual wildfires on streamflow at fine scales (< 1 km(2)) in specific geographic settings, the effects of wildfire regimes on streamflow at broad spatial scales across temperate forests in Australia are not well understood. In this paper, we combined climate, wildfire, streamflow records (1975 to 2018), topographic, and landcover data from 92 catchments (74 - 4740 km(2)) in the Australian temperate zone to quantify the contribution of wildfire regimes over time to streamflow variability in different hydroclimatic settings (humid, dry sub-humid, and semi-arid) and geographic regions (Southeast Australia (SEA), Southwest Western Australia (SWWA), and Tasmania (TAS)). Wildfire regimes were represented by two metrics: the burnt area to drainage area (BDA) ratio for wildfire events in each year and a spatially averaged metric of Time Since Fire (TSF), which is a spatial average of time since the last wildfire in the catchment. By comparing prefire and postfire runoff ratios our study found that on average there was a short-term increase in runoff ratio (-3% in year 1 and-6% in year 2 post-fire) after wildfires with BDA > 25%. No influence of fire was found in the long-term (15-20 years after the wildfire) runoff ratio. We found that wildfire regime, measured by TSF, explained-8.8% of the variation in annual streamflow across the Australian temperate zone, and that with decreasing TSF (i.e., increased wildfire impact), the average streamflow increased. Streamflow variation explained by wildfire regimes varied with hydroclimate. The explained variance of streamflow by wildfire regimes in semi-arid catchments (23%) and dry sub-humid catchments (13%) were higher than humid catchments (5%). Our results provide a broad-scale understanding of how wildfire regimes influence streamflow variability at broad temporal and spatial scales, and provided important context and baseline information for determining the implications of changes in climate and fire regimes for regional water availability.

Monitoring forest structural properties is critical for a range of applications because structure is key to understanding and quantifying forest biophysical functioning, including stand dynamics, evapotranspiration, habitat, and recovery from disturbances. Monitoring of forest structural properties at desirable frequencies and cost globally is enabled by space-borne LiDAR missions such as the global ecosystem dynamics investigation (GEDI) mission. This study assessed the accuracy of GEDI estimates for canopy height, total plant area index (PAI), and vertical profile of plant area volume density (PAVD) and elevation over a gradient of canopy height and terrain slope, compared to estimates derived from airborne laser scanning (ALS) across two forest age-classes in the Central Highlands region of south-eastern Australia. ALS was used as a reference dataset for validation of GEDI (Version 2) dataset. Canopy height and total PAI analyses were carried out at the landscape level to understand the influence of beam-type, height of the canopy, and terrain slope. An assessment of GEDI’s terrain elevation accuracy was also carried out at the landscape level. The PAVD profile evaluation was carried out using footprints grouped into two forest age-classes, based on the areas of mountain ash (Eucalyptus regnans) forest burnt in the Central Highlands during the 1939 and 2009 wildfires. The results indicate that although GEDI is found to significantly under-estimate the total PAI and slightly over-estimate the canopy height, the GEDI estimates of canopy height and the vertical PAVD profile (above 25 m) show a good level of accuracy. Both beam-types had comparable accuracies, with increasing slope having a slightly detrimental effect on accuracy. The elevation accuracy of GEDI found the RMSE to be 10.58 m and bias to be 1.28 m, with an R2 of 1.00. The results showed GEDI is suitable for canopy densities and height in complex forests of south-eastern Australia.