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This paper presents a method to analyze and improve the set of equations constituting a rainfall‐runoff model structure based on a combination of a data assimilation algorithm and polynomial updates to the state equations. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to the GR2M model and 201 catchments in South‐East Australia. Our results show that the updated model generated with DAISI generally performed better for all metrics considered included Kling‐Gupta Efficiency, NSE on log transform flow and flow duration curve bias. In addition, the elasticity of modeled runoff to rainfall is higher in the updated model, which suggests that the structural changes could have a significant impact on climate change simulations. Finally, the DAISI diagnostic identified a reduced number of update configurations in the GR2M structure with distinct regional patterns in three sub‐regions of the modeling domain (Western Victoria, central region, and Northern New South Wales). These configurations correspond to specific polynomials of the state variables that could be used to improve equations in a revised model. Several potential improvements of DAISI are proposed including the use of additional observed variables such as actual evapotranspiration to better constrain internal model fluxes. Plain Language Summary: This paper presents a data‐driven method to improve rainfall‐runoff models used to generate future water resources scenario in climate change studies. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to monthly streamflow simulations over a large data set of catchments in South‐East Australia. Our results show that DAISI improves model performance for a wide range of metrics and increases the sensitivity of the model to climate inputs, which is critical in climate change scenarios. Finally, the improvements identified by DAISI take a simple mathematical form with distinct regional patterns in three sub‐regions of the study domain (Western Victoria, central region, and Northern New South Wales). Several improvements of DAISI are discussed including the inclusion of additional observed variables such as evapotranspiration to better constrain model simulations. Key Points: Data Assimilation Informed model Structure Improvement method diagnoses hydrological model structures by combining data assimilation with a polynomial update of state equationsThe method was applied to the GR2M rainfall‐runoff model with significantly improved streamflow simulations in 201 Australian catchmentsThe method identified updates to state equations with marked regional characteristics that could guide future improvement of GR2M [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has demonstrated how a stochastic disruptive event can dramatically alter community soundscapes. Whilst religious bells have symbolism in many worldwide faiths, the sound emanating from church bells can be considered public domain and therefore, is not exclusive to the church. Pandemic-related interruption of these sounds impacts not only the church involved, but both the surrounding soundscape and any members of the community who ascribe value to these sounds. This paper examines the soundscape of Christian churches in the states of New South Wales and Victoria, to give an Australian perspective one year after the declaration of the COVID-19 pandemic in March 2020. It provides an update of the situation in Australia, building on our previous work from August of that year. In doing so, it explores the activity of church tower bell ringing, and how this "non-essential" activity has been affected, both during and subsequent to the heavy community restrictions applied in Australia. The paper also explores what lengths bellringers have undertaken to be permitted to conduct such activities, such as the use of adaptive measures due to "social distancing", and considers what implications this enforced silence has in similar soundscapes elsewhere in the world. [ABSTRACT FROM AUTHOR]

Introduction: Effective primary healthcare services have been identified by the World Health Organization as the most equitable approach to enhancing universal healthcare. Robust models of mentoring for registered nurses (RNs) transitioning to primary healthcare roles have yet to be described in the Australian context. A robust mentoring model can support RNs to fulfill their potential, bridging the gap between theory and practice. In 2015, the peak body for nurses in primary health care (PHC) began developing a transition to practice program, including embedded mentoring to support newly graduated and more experienced registered and enrolled nurses. This quality improvement study reports the experiences and perspectives of nurses participating as mentors in two separate offerings of the program delivered between 2019 and 2021. Method: A two-phase concurrent mixed methods evaluation utilized data from pre- and post online surveys and post program meetings. Quantitative items underwent descriptive analyses. Thematic analysis of free-text responses and comments was conducted independently by two researchers. Mentors voluntarily provided self-report data and were informed that data is routinely collected to support continuous quality improvement processes for all programs. An Information Sheet informed mentors of data usage, confidentiality, and options to withdraw without penalty from the program at any time. Results: Seventy-nine mentors were recruited to support two groups of nurses (N = 111). Mentor self-rated overall satisfaction with program participation was 86.67% (very or extremely satisfied). Mentors described being "witness to mentee growth," "having facilitated access to learning" and receiving "unexpected benefits" including personal and professional growth and enhanced enthusiasm for their role in PHC. Conclusion: The embedded mentoring reported in this article combined a focus on skills acquisition and professional identity with the provision of a range of resources and support activities. Sustainable mentoring programs will be an important mechanism for supporting the expanding roles required of nurses working in primary health. [ABSTRACT FROM AUTHOR]

The incidence of pyro-cumulonimbus (pyroCb) caused by extreme wildfires has increased markedly in Australia over the last several decades. This increase can be associated with a dangerous escalation of wildfire risk and severe stratospheric pollution events. Atmospheric and fuel conditions are important influences on pyroCb occurrence, but the exact causal relationships are still not well understood. We used the Continuous Haines Index (C-Haines) to represent atmospheric instability and the Fuel Moisture Index (FMI) to represent fuel moisture to provide better insight into the effects of atmospheric and fuel conditions on pyroCb occurrence over southeast Australia. C-Haines and FMI were related to the probability of pyroCb occurrence by employing a logistic regression on data gathered between 1980 and 2020. Emphasis is placed on investigating the independent effects and combined effects of FMI and C-Haines, as well as assessing their potential to predict whether a pyroCb develops over a fire. The main findings of this study are: (1) high C-Haines and low FMI values are representative of favorable conditions for pyroCb occurrence, but C-Haines can offset the effect of FMI—the addition of C-Haines to the logistic model muted the significance of FMI; (2) among the components of C-Haines, air temperature lapse rate (CA) is a better predictor of pyroCb occurrence than the dryness component (CB); (3) there are important regional differences in the effect of C-Haines and FMI on pyroCb occurrence, as they have better predictive potential in New South Wales than in Victoria. [ABSTRACT FROM AUTHOR]

The emission of black carbon (BC) particles, which cause atmospheric warming by affecting radiation budget in the atmosphere, is the result of an incomplete combustion process of organic materials. The recent wildfire event during the summer 2019–2020 in south-eastern Australia was unprecedented in scale. The wildfires lasted for nearly 3 months over large areas of the two most populated states of New South Wales and Victoria. This study on the emission and dispersion of BC emitted from the biomass burnings of the wildfires using the Weather Research Forecast–Chemistry (WRF–Chem) model aims to determine the extent of BC spatial dispersion and ground concentration distribution and the effect of BC on air quality and radiative transfer at the top of the atmosphere, the atmosphere and on the ground. The predicted aerosol concentration and AOD are compared with the observed data using the New South Wales Department of Planning and Environment (DPE) aethalometer and air quality network and remote sensing data. The BC concentration as predicted from the WRF–Chem model, is in general, less than the observed data as measured using the aethalometer monitoring network, but the spatial pattern corresponds well, and the correlation is relatively high. The total BC emission into the atmosphere during the event and the effect on radiation budget were also estimated. This study shows that the summer 2019–2020 wildfires affect not only the air quality and health impact on the east coast of Australia but also short-term weather in the region via aerosol interactions with radiation and clouds. [ABSTRACT FROM AUTHOR]

High-resolution palaeoclimate proxies are fundamental to our understanding of the diverse climatic history of the Australian mainland, particularly given the deficiency in instrumental datasets spanning more than a century. Annually resolved, tree-ring-based proxies play a unique role in addressing limitations in our knowledge of interannual to multi-decadal temperature and hydroclimatic variability prior to the instrumental period. Here we present cross-dated ring-width (RW) and minimum blue-intensity (BI) chronologies spanning 70 years (1929–1998) for Podocarpus lawrencei Hook.f., the Australian mainland's only alpine conifer, based on nine full-disc cross-sections from Mount Loch in the Victorian Alps. Correlations with climate variables from observation stations and gridded data across the 1929–1998 period reveal a significant positive relationship between RW and mean monthly maximum temperatures in winter throughout central Victoria (r=0.62 , p<0.001) and a significant negative correlation to winter precipitation (r=-0.51 , p<0.001). We also found significant negative correlations between RW and monthly snow depth at Spencer Creek in New South Wales (r=-0.60 , p<0.001). Of the assessed BI parameters, delta blue intensity (Δ BI; the difference between early- and late-wood BI) displayed the greatest sensitivity to climate, with robust spatial correlations with mean October to December maximum and minimum monthly temperatures (r=-0.43 , p<0.001 ; r=-0.51 , p<0.001) and July precipitation (r=0.44 , p<0.001), across large areas of northern Victoria. These promising findings highlight the utility of this species for future work. With the very limited availability of suitable long-lived and cross-datable species on the Australian mainland, these results have significant implications for advancing high-resolution palaeoclimate science in southeastern Australia and for improving our understanding of past climate in the region. [ABSTRACT FROM AUTHOR]

Regional flood frequency analysis (RFFA) is widely used to estimate design floods in ungauged catchments. Both linear and non-linear methods are adopted in RFFA. The development of the non-linear RFFA method Adaptive Neuro-fuzzy Inference System (ANFIS) using data from 181 gauged catchments in south-eastern Australia is presented in this study. Three different types of ANFIS models, Fuzzy C-mean (FCM), Subtractive Clustering (SC), and Grid Partitioning (GP) were adopted, and the results were compared with the Quantile Regression Technique (QRT). It was found that FCM performs better (with relative error (RE) values in the range of 38–60%) than the SC (RE of 44–69%) and GP (RE of 42–78%) models. The FCM performs better for smaller to medium ARIs (2 to 20 years) (ARI of five years having the best performance), and in New South Wales, over Victoria. In many aspects, the QRT and FCM models perform very similarly. These developed RFFA models can be used in south-eastern Australia to derive more accurate flood quantiles. The developed method can easily be adapted to other parts of Australia and other countries. The results of this study will assist in updating the Australian Rainfall Runoff (national guide)-recommended RFFA technique. [ABSTRACT FROM AUTHOR]

The diversity of lagoviruses (Caliciviridae) in Australia has increased considerably in recent years. By the end of 2017, five variants from three viral genotypes were present in populations of Australian rabbits, while prior to 2014 only two variants were known. To understand the evolutionary interactions among these lagovirus variants, we monitored their geographical distribution and relative incidence over time in a continental-scale competition study. Within 3 years of the incursion of rabbit haemorrhagic disease virus 2 (RHDV2, denoted genotype GI.1bP-GI.2 [polymerase genotype]P-[capsid genotype]) into Australia, two novel recombinant lagovirus variants emerged: RHDV2-4e (genotype GI.4eP-GI.2) in New South Wales and RHDV2-4c (genotype GI.4cP-GI.2) in Victoria. Although both novel recombinants contain non-structural genes related to those from benign, rabbit-specific, enterotropic viruses, these variants were recovered from the livers of both rabbits and hares that had died acutely. This suggests that the determinants of host and tissue tropism for lagoviruses are associated with the structural genes, and that tropism is intricately connected with pathogenicity. Phylogenetic analyses demonstrated that the RHDV2-4c recombinant emerged independently on multiple occasions, with five distinct lineages observed. Both the new RHDV2-4e and -4c recombinant variants replaced the previous dominant parental RHDV2 (genotype GI.1bP-GI.2) in their respective geographical areas, despite sharing an identical or near-identical (i.e. single amino acid change) VP60 major capsid protein with the parental virus. This suggests that the observed replacement by these recombinants was not driven by antigenic variation in VP60, implicating the non-structural genes as key drivers of epidemiological fitness. Molecular clock estimates place the RHDV2-4e recombination event in early to mid-2015, while the five RHDV2-4c recombination events occurred from late 2015 through to early 2017. The emergence of at least six viable recombinant variants within a 2-year period highlights the high frequency of these events, detectable only through intensive surveillance, and demonstrates the importance of recombination in lagovirus evolution. [ABSTRACT FROM AUTHOR]