@article {bnh-8305, title = {Mapping how outputs from various Bushfire and Natural Hazards CRC projects could be combined to address the issue of how to best manage fuel to reduce bushfire risk into the future}, number = {718}, year = {2022}, month = {01/2022}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

This project reviewed all of the Bushfire and Natural Hazard CRC (CRC) publications hosted on the CRC website to identify outputs that could be of interest in addressing the issue of how to best manage fuel to reduce bushfire risk into the future.

We identified 12 projects part of five research clusters involving a wide range of actors: Prescribed burning and catchment management, Economics and strategic decisions, Bushfire predictive services, Governance and institutional knowledge, Understanding and enhancing resilience which could offer potential synergies with the Mechanical Fuel Load Reduction (MFLR) Utilisation Project. The most relevant outputs were summarised in conceptual diagrams (mind-maps), and possible utilisation for the MFLR milestones was highlighted in each section.

}, issn = {718}, author = {Amelie Jeanneau and Aaron Zecchin and Hedwig van Delden and Tim McNaught and Holger Maier} } @article {bnh-8304, title = {Opportunities for alternative fuel load reduction approaches - summary report}, number = {719}, year = {2022}, month = {01/2022}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Planned burning is one of the most utilised fuel management activities, but the safe and effective application of this method is likely to be hindered by climate change (e.g. shrinking and shifting windows of opportunity) and potential adverse societal outcomes (e.g. smoke impact, risk of fire escape). For this reason, fire managers need access to detailed information to help them make informed decisions and select a fuel management strategy that is compatible with a range of factors.

This project explored the use of experts{\textquoteright} knowledge and the UNHaRMED Decision Support System (DSS) framework (an integrated spatio-temporal model for analysing natural hazard risk within urban and rural environments) to assess the opportunities and risks associated with different approaches to reducing bushfire risk via fuel management.

This project identified:

This report presents the major findings from the Fuel Load Reduction Utilisation Project and proposes future research directions identified by end-users, building on this project{\textquoteright}s results. The proposed projects could help develop policies and strategies for reducing risk in emerging bushfire risk areas at the State and national scale by offering a range of fuel management activities adapted to specific regional conditions, which could change over time.

}, issn = {719}, author = {Amelie Jeanneau and Aaron Zecchin and Hedwig van Delden and Roel Vanhout and Tim McNaught and Mike Wouters and Holger Maier} } @article {bnh-8293, title = {Guidance framework for the selection of different fuel management strategies}, number = {716}, year = {2021}, month = {12/2021}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Planned burning is one of the most utilised fuel management activities, but the safe application of this method is hindered by climate change (e.g. shrinking and shifting windows of opportunity) and adverse societal and environmental outcomes (e.g. smoke impact, risk of fire escape). For this reason, fire managers need access to detailed information to help them make informed decisions and select a fuel management strategy that is compatible with a range of factors.

This report focuses on the development and illustration of a general guidance framework that provides users with the information and knowledge they need to select suitable fuel management strategies for their particular circumstances, and hence assists them with preparing an effective fuel management plan. The framework is developed based on a review of literature and data collected from survey responses from local governments and their fire managers in Western Australia who conduct fuel management activities.

The framework provides information on a set of functions bushfire mitigation officers need to consider when developing fuel management plans for a range of fuel management techniques. The functions are divided into:

The fuel management techniques include:

The utility of the framework is illustrated on two hypothetical scenarios, representing situations where a user would like to ascertain relevant attributes of a set of candidate fuel management techniques and where a user would like to identify the best fuel management technique for a given situation.

}, keywords = {framework, Fuel management, guidance, strategies}, issn = {716}, author = {Amelie Jeanneau and Aaron Zecchin and Hedwig van Delden and Tim McNaught and Holger Maier} } @article {bnh-8292, title = {Identification of fuel management locations and risk reduction potential}, number = {715}, year = {2021}, month = {12/2021}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Planned burning is one of the most utilised fuel management activities, but the safe and effective application of this method is likely to be hindered by climate change (e.g. shrinking and shifting windows of opportunity) and potential adverse societal outcomes (e.g. smoke impact, risk of fire escape). For this reason, fire managers need access to detailed information to help them make informed decisions and select a fuel management strategy that is compatible with a range of factors.

This project explored the use of experts{\textquoteright} knowledge and the UNHaRMED Decision Support System (DSS) framework (an integrated spatio-temporal model for analysing natural hazard risk within urban and rural environments) to identify areas where fuel management activities should be conducted within the study area and identify future bushfire risk reduction potential at identified hotspots.

The discussions with end-users resulted in the selection of five major areas to focus on for this study (i.e. Gingin, Kalamunda, Mundaring and Margaret River). The level of bushfire risk simulated in UNHaRMED for a baseline period indicated a good agreement with the perceived levels of bushfire risk at the rural-urban interface identified by the relevant bushfire management agencies. This observation therefore suggests that UNHaRMED is suitable for identifying areas of emerging risk under different climate change scenarios.

This research also highlighted that areas where fuel management activities are currently conducted in Gingin, Kalamunda, Mundaring and Margaret River overlap with areas of high bushfire risk modelled in UNHaRMED (rural-urban interface). This suggests that UNHaRMED is suitable for assessing the impact of fuel load mitigation activities a the rural-urban interface in WA.

The next step will be to run UNHaRMED simulations involving a range of future climate and population growth scenarios with and without fuel management activities (M2). This will then enable us to identify how bushfire risk changes for each scenario, where management activities are desirable, and where potential risk reduction will be possible (irrespective of management type) (D2).

}, keywords = {Fuel management, locations, potential, risk reduction}, issn = {715}, author = {Amelie Jeanneau and Aaron Zecchin and Hedwig van Delden and Tim McNaught and Holger Maier} } @article {bnh-8294, title = {Identifying opportunities for the use of different fuel management strategies in WA}, number = {717}, year = {2021}, month = {12/2021}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Bushfire risk is likely to increase in the future due to the combined impacts of climate change and urban sprawl. Planned burning is one of the most utilised fuel management activities, but the safe application of this method is being threatened by climate change (e.g. shrinking and shifting windows of opportunity) and potential adverse societal outcomes (e.g. smoke impact, risk of fire escape). In order to address this issue, this report introduces a novel approach to determining the suitability of different fuel management approaches (e.g. forest thinning, scrub rolling, mulching, mowing/slashing, planned burning pile burning, chipping, grazing) in different areas using a combination of local knowledge/experience and spatial data analysis. The approach is applied to four areas of emerging bushfire risk in Western Australia identified in consultation with end-users, producing maps for different fuel management approaches that indicate where the application of particular fuel management approaches is suitable. These maps can be obtained for current and future conditions, therefore providing an assessment of which fuel management options are available to mitigate the impact in areas of emerging bushfire risk. The approach is generic and flexible and can be tailored to different locations based on information of local knowledge and experience.

}, keywords = {Fuel management, opportunities, strartegies}, issn = {717}, author = {Amelie Jeanneau and Aaron Zecchin and Hedwig van Delden and Tim McNaught and Holger Maier} } @article {bnh-8291, title = {Influence of climate change and fuel management on bushfire risk in Western Australia}, number = {714}, year = {2021}, month = {12/2021}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Bushfire risk is likely to increase in the future due to the combined impacts of climate change and urban sprawl. This report presents the results of an analysis combining the outputs from stakeholder consultation with those from the Unified Natural Hazard Risk Mitigation Exploratory Decision Support System (UNHaRMED) to quantify increases in bushfire risk due to different population growth and climate change scenarios in four areas of emerging bushfire risk in Western Australia. Results indicate that increases in bushfire risks from 2018 to 2050 range between 23.9\% and 59.7\% (in terms of average annual loss), depending on the scenario and case study area considered. UNHaRMED is also used to assess the potential of mitigating these increases in risk via fuel load reduction.

Results indicate that fuel management can reduce future bushfire risk and that the decline in risk is positively correlated with an increase in the proportion of the landscape treated. However, our results suggest that in cases where fuel management does significantly reduce the risk of impacts posed by bushfires, this reduction was much less than an increase in risk from climate change.

It should be noted that this project focused on the rural-urban interface in alignment with the existing Bushfire Risk Management Planning approach adopted in Western Australia. As such, landscape-scale mitigation was not considered in this particular project, but would be an important consideration in future research.

}, keywords = {bushfire risk, Climate change, Fuel management, Western Australia}, issn = {714}, author = {Amelie Jeanneau and Aaron Zecchin and Hedwig van Delden and Tim McNaught and Holger Maier} } @article {bnh-7508, title = {Improved decision support for natural hazard risk reduction {\textendash} annual report 2019-2020}, number = {629}, year = {2020}, month = {11/2020}, institution = {Bushfire and Natural Hazards CRC}, address = {MELBOURNE}, abstract = {

There is increasing recognition of the urgency to consider how disaster risk might change into the future, what impacts this is likely to have and, most importantly, what we can do to reduce this risk.\  There is also increased recognition that in order to achieve this, we need to adopt a holistic approach that takes into account community values, vulnerabilities and resilience, future changes in population and demographics, climate change, multiple hazards, cascading events, adaptation and a range of risk reduction strategies, such land use planning, community education, land management, structural measures and changes to building codes.

Over the last 5 years, this project has co-developed conceptual, modelling and decision support frameworks for tackling the above problems in conjunction with more than 40 end-user organisations in four states (South Australia, Western Australia, Tasmania and Victoria).\  The frameworks facilitate (i) the development of the capacity for strategic thinking and for tackling long-term disaster risk in an integrated fashion, (ii) the collaboration between different government departments and different levels of government (federal, state and local), (iii) the development of a shared understanding of risks and values between a range of stakeholders (e.g. different levels of government and the community), (iv) the quantification of how disaster risks and costs might change into the future under a range of integrated socio-economic and climate scenarios and (v) the development of the best adaptive mitigation strategies under these scenarios.

The above frameworks have resulted in the development of the decision support software UNHaRMED (Unified Natural Hazards Risk Mitigation Exploratory Decision support system), applications for which have been co-developed with end users for greater Adelaide, Perth and surrounds, Tasmania and greater and peri-urban Melbourne.\  They are now being deployed in a variety of manners to support understanding and decision making on disaster risk reduction along with continual improvements to the capability.

In the last financial year users have now been trained in all jurisdictions. This report summarises some of the enhanced software capabilities along with describe several utilisation activities designed to highlight the benefits of using an interactive risk assessment tool in participatory settings. This has included facilitating a mitigation exercises for South Australian State and Local Government agencies exploring mitigation activities for a changing coastal risk profile and assessing floodplain management approaches in the Gawler River.

}, keywords = {decision support, improved, natural hazard, risk reduction, UNHaRMED}, issn = {629}, author = {Holger Maier and Graeme Riddell and Hedwig van Delden and Sofanit Araya and Aaron Zecchin and Roel Vanhout and Graeme Dandy and Eike Hamers} } @article {bnh-7026, title = {Improved decision support for natural hazard risk reduction {\textendash} annual project report 2018-2019}, number = {583}, year = {2020}, month = {06/2020}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

There is increasing recognition of the urgency to consider how disaster risk might change into the future, what impacts this is likely to have and, most importantly, what we can do to reduce this risk. There is also increased recognition that in order to achieve this, we need to adopt a holistic approach that takes into account community values, vulnerabilities and resilience, future changes in population and demographics, climate change, multiple hazards, cascading events, adaptation and a range of risk reduction strategies, such as land use planning, community education, land management, structural measures and changes to building codes.

Over the last five years, this project has co-developed conceptual, modelling and decision support frameworks for tackling the above problems in conjunction with more than 40 end-user organisations in four states (South Australia, Western Australia, Tasmania and Victoria). The frameworks facilitate:

The above frameworks have resulted in the development of the decision support software UNHaRMED (Unified Natural Hazards Risk Mitigation Exploratory Decision support system), applications for which have been co-developed with end-users for greater Adelaide, Perth and surrounds, Tasmania and greater and peri-urban Melbourne. In Adelaide, UNHaRMED is being used in collaboration with local governments for strategic flood mitigation planning and the development of a state emergency management exercise focused on recovery and long term mitigation related to sea level rise.

End-user training for the Perth and Tasmania UNHaRMED applications only occurred in 2019 and relevant agencies in these states are working towards the incorporation of these applications in state planning processes. End-user training for the greater and peri-urban application of UNHaRMED will take place in July 2019.

Other opportunities have also presented themselves in working with agencies and providing outputs and insight from UNHaRMED into other projects and products. These have included working with the SA Government on a mitigation exercise which will take place early in the next financial year focused on how to explore future impacts of coastal flooding and develop mitigation activities to be implemented. Another has been working with the National Resilience Taskforce on modelling capabilities for understanding climate and disaster risks.

}, keywords = {decision support, Natural hazards, risk reduction, UNHaRMED}, issn = {583}, author = {Holger Maier and Graeme Riddell and Hedwig van Delden and Sofanit Araya and Aaron Zecchin and Roel Vanhout and Graeme Dandy and Eike Hamers} } @article {bnh-6567, title = {Simulation optimisation for natural hazard risk management}, number = {533}, year = {2020}, month = {01/2020}, institution = {Bushfire \& Natural Hazards CRC}, address = {Melbourne}, abstract = {

In this report, we outline a decision-support framework for natural hazard management that combines the use of simulation and optimisation for exploring what risk reduction measures best achieve management priorities. This framework addressed several needs that practitioners have with regard to risk and adaptation assessment. First, it uses optimisation approaches to screen through and identify those management options that perform best across a number of decision criteria. This is important, as there are a very diverse range of management options which could be combined in an extremely large number of ways to make portfolios of management options and it is difficult to screen through all potential portfolios to shortlist a small number for further consideration. Second, it simulates the effectiveness of management options over long-term planning horizons. This is important, for management options may have long lead-in-times, and/or may have long lifetimes, are not easily/readily changed, and so need to be effective over a broad range of plausible future conditions, which likely include larger populations, increased economic development and climate change. Third, the framework emphasises holistic assessment, wherein the Integrated assessment modelling (IAM) simulates the effect of management options across a number of criteria, therefore allowing practitioners to explore the trade-offs between risk reduction with other community goals, including environmental, social and economic outcomes.


The value of this framework arises from the greater demands that are being placed on planners to effectively manage natural hazard risk, whether from politicians or from the public who have an increasingly reduced appetite for hazard losses. This creates a need for analytic frameworks for exploring how to best manage risk, and this framework addresses this gap.


Through application to a case study, this report shows how the framework is able to increase the effectiveness and efficiency by which IAM can be applied to natural hazard risk management. The role of the optimisation was seen not to be prescriptive, but to enable better exploration of risk management options. The framework was therefore able to provide rich information on the effectiveness of management portfolios by which better risk management plans could be formed.


The case study to which the framework was applied considered coastal flood risk within Greater Adelaide and explored the combinations of zonal exclusion areas along the coast which prevented further development. If unmitigated, coastal risk could increase by 10\% over the next three decades. However, results of the case study application showed that zonal exclusion policies could effectively reduce this growth of coastal risk, however this required excluding further development from 7000 Ha of land along the coast. Saying that, the growth in risk could be limited to 3\% (i.e. a reduction in growth by 60\%), through excluding coastal development from only 1500 Ha.

}, keywords = {natural hazard, optimisation, risk management, simulation}, issn = {533}, author = {Jeffrey Newman and Graeme Dandy and Aaron Zecchin and Hedwig van Delden and Charles Newland and Holger Maier and Graeme Riddell} } @article {bnh-5694, title = {Exploratory scenario analysis for disaster risk reduction: Considering alternative pathways in disaster risk assessment}, journal = {International Journal of Disaster Risk Reduction}, year = {2019}, month = {07/2019}, abstract = {

Disaster risk is a combination of natural hazards, along with society{\textquoteright}s exposure and vulnerability to them. Therefore, to ensure effective, long-term disaster risk reduction we must consider the dynamics of each of these components and how they change over extended periods due to population, economic and climatic drivers, as well as policy and individual decisions. This paper provides a methodology to capture these factors within exploratory scenarios designed to test the effectiveness of policy responses to reduce disaster losses. The scenarios developed and subsequent analysis of them combine knowledge and insight from stakeholders and experts, and make use of simulation modelling to enable scenarios with qualitative and quantitative elements to be integrated within risk assessment processes and contribute to strategic risk treatments. The methodology was applied to a case-study in Greater Adelaide, Australia, and used to assess how disaster risk for earthquakes, bushfire and coastal inundation changes from 2016 to 2050 under five exploratory scenarios for the future of the region. This analysis can be applied more broadly to consider how future risks impacts on regional viability, and suitability for investment related to the need to gain a better understanding of governmental and organisational exposure to physical risks.

}, keywords = {Disaster risk, Risk assessment, Scenarios, Simulation modelling, Stakeholder engagement}, doi = {https://doi.org/10.1016/j.ijdrr.2019.101230}, url = {https://www.sciencedirect.com/science/article/pii/S2212420919302286}, author = {Graeme Riddell and Hedwig van Delden and Holger Maier and Aaron Zecchin} } @conference {bnh-6513, title = {Future risk framework: understanding tomorrow{\textquoteright}s risk and what we can do to reduce it}, booktitle = {AFAC19 powered by INTERSCHUTZ - Bushfire and Natural Hazards CRC Research Forum}, year = {2019}, month = {12/2019}, publisher = {Australian Institute for Disaster Resilience}, organization = {Australian Institute for Disaster Resilience}, address = {Melbourne}, abstract = {

Unless appropriate mitigation action is taken, disaster risk is likely to increase into the future due to factors such as climate change, population growth, economic development and an ageing population. Consequently, there is a pressing need to think about plausible future risks and how to best mitigate them. This paper presents the future risk framework, which provides a structured, stepwise approach for relevant agencies to explore future risk and what it means for their organisation. The framework consists of four main steps, progressively increasing in levels of insight into future risk, as well as increasing the level of quantification of risk. A key feature of the framework is the incorporation of sense-making and its implementation consists of a combination of participatory approaches and the use of data, information, modelling and analysis. Application of the framework is illustrated for the case study of Greater Adelaide, South Australia, highlighting the approaches used and the level of insight into future risk obtained at each of the four stages. A discussion on the challenges associated with using this insight to mitigate future risk is also provided, suggesting that a collaborative, multidisciplinary, multi-agency approach is needed to effectively mitigate all aspects of future risk, especially those associated with increases in exposure and vulnerability.\ 

Download the full non-peer reviewed research proceedings\ from the Bushfire and Natural Hazards CRC Research Forumhere.

}, keywords = {Climate change, Disaster risk, mitigation, Planning, risk management, risk reduction}, url = {https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/}, author = {Graeme Riddell and Hedwig van Delden and Holger Maier and Aaron Zecchin and Roel Vanhout and James Daniell and Sofanit Araya and Graeme Dandy and Jeffrey Newman} } @article {bnh-6260, title = {Tomorrow{\textquoteright}s disasters {\textendash} Embedding foresight principles into disaster risk assessment and treatment}, journal = {International Journal of Disaster Risk Reduction}, year = {2019}, month = {12/2019}, abstract = {

Disaster risk is a complex, uncertain and evolving threat to society which changes based on broad drivers of hazard, exposure and vulnerability such as population, economic and climatic change, along with new technologies and social preferences. It also evolves as a function of decisions of public policy and public/private investment which alters future risk profiles. These factors however are often not captured within disaster risk assessments and explicitly excluded from the UN General Assembly definition of a disaster risk assessment which focuses on the current state of risk. This means that 1) we cannot adequately capture changes in risk and risk assessments are out of date as soon as published but also 2) we cannot show the benefit of proactive risk treatments in our risk assessments. This paper therefore outlines a generic, scale-neutral, framework for integrating foresight {\textendash} thinking about the future {\textendash} into risk assessment methodologies. This is demonstrated by its application to a disaster risk assessment of heatwave risk in Tasmania, Australia, and shows how risk changes across three future scenarios and what proactive treatments could be possible mitigating the identified drivers of future risk.

}, keywords = {Disaster risk management, Foresight, Risk assessment, Risk treatment, Scenarios}, doi = {https://doi.org/10.1016/j.ijdrr.2019.101437}, url = {https://www.sciencedirect.com/science/article/pii/S2212420919305588}, author = {Graeme Riddell and Hedwig van Delden and Holger Maier and Aaron Zecchin} } @article {bnh-5686, title = {UNHaRMED framework report: a co-creation approach for the development and use of decision support systems for disaster risk reduction.}, number = {484}, year = {2019}, month = {07/2019}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

This report proposes a generic approach for the development and use of decision support systems (DSSs) for disaster risk reduction (DRR). At the core of the DSS is an integrated model, consisting of a land use model and risk models for four hazards, including flooding, coastal inundation, bushfire and earthquake. The inputs to these models are affected by a number of external drivers that change over time, including demographics, climate change and economics, as well as a number of mitigation options, including spatial planning, land management, structural measures and community-based resilience efforts. The outputs from the integrated model include risk maps for the individual hazards that change over time, as well as cost-benefit, social and environmental indicators used for assessing the impact of risk reduction portfolios.

}, keywords = {DDR, decision support system, Disaster management, framework, UNHaRMED}, issn = {484}, author = {Hedwig van Delden and Graeme Riddell and Roel Vanhout and Holger Maier and Jeffrey Newman and Aaron Zecchin and Graeme Dandy} } @conference {bnh-4771, title = {Applying unharmed for risk reduction planning {\textendash} comparing strategies and long-term effectiveness}, booktitle = {AFAC18}, year = {2018}, month = {09/2018}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Perth}, abstract = {

Natural hazards are an unavoidable component of life in Australia. Analysis shows the average cost of natural hazards in 2015 totalled $9.6billion, and this figure is projected to increase to $33billion by 2050 (Deloitte Access Economics 2015). These figures correspond to a substantial impact and coupled with the social and environmental impacts of disasters, paint a bleak picture. However, as tomorrow{\textquoteright}s risk is a function of today{\textquoteright}s decisions with effective risk reduction planning there is significant scope to minimise tomorrow{\textquoteright}s impacts. The challenge though exists in that ex-ante analysis on the long term effectiveness of risk reduction strategies, the type of analysis required to justify significant investment and policy decisions, is challenging given the dynamic, complex nature of disaster risk, and the length of assessment period required to consider returns. In response to this and to support improved understanding of future risks and ex-ante testing of risk reduction solutions a tool was developed between researchers and Australian government agencies.

}, author = {Graeme Riddell and Hedwig van Delden and Roel Vanhout and Holger Maier and Jeffrey Newman and Aaron Zecchin and Graeme Dandy} } @article {bnh-5133, title = {Empirically derived method and software for semi-automatic calibration of Cellular Automata land-use models}, journal = {Environmental Modelling and Software}, volume = {108}, year = {2018}, month = {10/2018}, pages = {208-239}, chapter = {208}, abstract = {

Land-use change\ models generally include neighbourhood rules to capture the spatial dynamics between different land-uses that drive land-use changes, introducing many parameters that require calibration. We present a process-specific semi-automatic method for calibrating neighbourhood rules that utilises discursive knowledge and\ empirical analysis\ to reduce the complexity of the calibration problem, and efficiently calibrates the remaining interactions with consideration of locational agreement and landscape pattern structure objectives. The approach and software for implementing it are tested on four case studies of major European cities with different physical characteristics and rates of\ urban growth, exploring preferences for different objectives. The approach outperformed benchmark models for both calibration and validation when a balanced objective preference was used. This research demonstrates the utility of process-specific calibration methods, and highlights how process knowledge can be integrated with automatic calibration to make it more efficient.

}, doi = {https://doi.org/10.1016/j.envsoft.2018.07.013}, url = {https://www.sciencedirect.com/science/article/pii/S1364815217313105}, author = {Charles Newland and Aaron Zecchin and Holger Maier and Jeffrey Newman and Hedwig van Delden} } @article {bnh-5132, title = {Enhancing the policy relevance of exploratory scenarios: generic approach and application to disaster risk reduction}, journal = {Futures}, volume = {99}, year = {2018}, month = {05/2018}, pages = {1-15}, chapter = {1}, abstract = {

Exploratory scenarios (i.e. scenarios that question what could happen) have been widely applied to a vast array of complex and uncertain socio-environmental system problems. Despite this fact, they have also been criticised by policy makers for not being relevant to policy processes and assessment. This paper proposes a generic approach to enhance policy relevance in the development of exploratory scenarios. This is carried out by participatory exploration and categorisation of available policy responses and framing of scenarios in terms of challenges to these. An exploration of the factors that make these policies more or less effective is used to develop a narrative for temporal developments in scenario instantiation, in comparison to more generic drivers for change. Within this paper, this process is applied to a case-study exploring the future of natural disaster risk; improving understanding of future uncertainties and subsequently the effectiveness of long-term disaster risk reduction. The case-study application consider bushfire, earthquake, flooding and heatwaves and resulted in five scenarios framed on challenges to resilience and challenges to mitigation for policy makers in Adelaide, Australia.

}, doi = {https://doi.org/10.1016/j.futures.2018.03.006}, url = {https://www.sciencedirect.com/science/article/pii/S001632871730410X}, author = {Graeme Riddell and Hedwig van Delden and Graeme Dandy and Aaron Zecchin and Holger Maier} } @article {bnh-5053, title = {Improved decision support for natural hazard risk reduction: annual project report 2017-18}, year = {2018}, month = {11/2018}, institution = {Bushfire and Natural Hazards CRC}, abstract = {

Natural hazards are an unavoidable component of life in Australia. Analysis shows the average cost of natural hazards in 2015 totalled $9.6 billion, and this figure is projected to increase to $33 billion by 2050. These figures correspond to a substantial impact and coupled with the social and environmental impacts of disasters, paint a bleak picture. However, tomorrow{\textquoteright}s risk is a function of today{\textquoteright}s decisions, and with effective adaptation planning there is significant scope to minimise tomorrow{\textquoteright}s impacts. To support improved understanding of future risks and testing of adaptation solutions this project is working on mechanisms to better inform decision making with quantitative tools by working with multiple government agencies.

}, issn = {427}, author = {Holger Maier and Graeme Riddell and Hedwig van Delden and Jeffrey Newman and Aaron Zecchin and Graeme Dandy and Roel Vanhout and Sofanit Araya and Bree Bennett} } @article {bnh-4336, title = {Multi-objective optimisation framework for calibration of Cellular Automata land-use models}, journal = {Environmental Modelling \& Software}, volume = {100}, year = {2018}, month = {02/2018}, pages = {175-200}, chapter = {175}, abstract = {

Modelling of land-use change plays an important role in many areas of environmental planning. However, land-use change models remain challenging to calibrate, as they contain many sensitive parameters, making the calibration process time-consuming. We present a multi-objective optimisation framework for automatic calibration of Cellular Automata land-use models with multiple dynamic land-use classes. The framework considers objectives related to locational agreement and landscape pattern structure, as well as the inherent stochasticity of land-use models. The framework was tested on the Randstad region in the Netherlands, identifying 77 model parameter sets that generated a Pareto front of optimal trade-off solutions between the objectives. A selection of these parameter sets was assessed further based on heuristic knowledge, evaluating the simulated output maps and parameter values to determine a final calibrated model. This research demonstrates that heuristic knowledge complements the evaluation of land-use models calibrated using formal optimisation methods.

}, doi = {10.1016/j.envsoft.2017.11.012}, url = {https://www.sciencedirect.com/science/article/pii/S1364815217306862}, author = {Charles Newland and Holger Maier and Aaron Zecchin and Jeffrey Newman and Hedwig van Delden} } @article {bnh-5072, title = {Multiple objective optimisation framework for automatic parameter tuning of Cellular Automata land-use models with multiple dynamic land-use classes}, journal = {Environmental Modelling and Software}, volume = {100}, year = {2018}, month = {02/2018}, pages = {175-200}, chapter = {175}, abstract = {

Modelling of land-use change plays an important role in many areas of environmental planning. However, land-use change models remain challenging to calibrate, as they contain many sensitive parameters, making the calibration process time-consuming. We present a multi-objective optimisation framework for automatic calibration of Cellular Automata land-use models with multiple dynamic land-use classes. The framework considers objectives related to locational agreement and landscape pattern structure, as well as the inherent stochasticity of land-use models. The framework was tested on the Randstad region in the Netherlands, identifying 77 model parameter sets that generated a Pareto front of optimal tradeoff solutions between the objectives. A selection of these parameter sets was assessed further based on heuristic knowledge, evaluating the simulated output maps and parameter values to determine a final calibrated model. This research demonstrates that heuristic knowledge complements the evaluation of land-use models calibrated using formal optimisation methods.

}, doi = {https://doi.org/10.1016/j.envsoft.2017.11.012}, url = {https://www.sciencedirect.com/science/article/pii/S1364815217306862?via\%3Dihub}, author = {Charles Newland and Hedwig van Delden and Jeffrey Newman and Aaron Zecchin and Holger Maier} } @article {bnh-3355, title = {Futures Greater Adelaide 2050: An exploration of disaster risk and the future}, number = {243}, year = {2017}, month = {01/2017}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Natural disaster risk is a combination of the natural hazard, exposure\ and vulnerability. As a result when considering future disaster risk and planning to minimise it, the uncertainty and complexity of each factor must be considered. Influencing factors on the three components of risk include political decisions, economic development, technological advancement, demographic changes and changing climate, many of which are mutually influential as well. The uncertainty and complexity that arise from these factors are critical to understand when considering long term disaster risk reduction planning, especially when planning decisions can have long lasting influence and large expense.

In an attempt to characterise, understand and subsequently make better decisions under these conditions the BNHCRC funded project {\textquotedblleft}Decision Support System (DSS) for Assessment of Policy \& Planning Investment Options for Optimal Natural Hazard Mitigation{\textquotedblright}, was initiated. For Greater Adelaide the project looks to develop an integrated spatial DSS to model long term changes in risk and subsequently assist decision makers plan and implement disaster risk reduction policies and investments.\  Incorporated with the development of the prototype software package is a facilitated stakeholder engagement process informing the development and then subsequent use of the system.

In September 2014 the first stage of this process was completed with results documented in Van Delden et al. (2015). The second phase, of which this report documents, incorporated the development of exploratory scenarios\ to better understand relevant uncertainties, develop strategic capacity in decision makers to consider uncertainties impacting on policies and provide a better understanding of the value and use of the developed DSS.

The process looked to discover critical elements relevant to disaster risk reduction\ and consider how they change into the future. As a method for exploring the future, scenarios were developed considering the changes from 2013 to 2050. Five alternate futures for Greater Adelaide were developed by members of SA{\textquoteright}s State Mitigation Advisory Group (SMAG), assisted by the scenarios team at the University of Adelaide and Research Institute for Knowledge Systems. These were subsequently modelled and results of the qualitative and quantitative scenarios will be presented in this report.

}, issn = {243}, author = {Graeme Riddell and Hedwig van Delden and Graeme Dandy and Holger Maier and Aaron Zecchin and Jeffrey Newman and Charles Newland} } @article {bnh-4207, title = {Improved decision support for natural hazard risk reduction: annual project report 2016-17}, number = {321}, year = {2017}, month = {09/2017}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Decision support systems that contain integrated models for the assessment of natural hazard mitigation options are an important component for robust, transparent, and long-term mitigation planning. Integrated modelling of underlying social, environmental, and economic systems is required to take into account system dynamics, and to explore the implications of future changes, such as changes in demographics, land use, economics and climate.\ Consequently, a generic decision support system for the long-term planning for natural disaster risk reduction is being developed as part of the Bushfire and Natural Hazards Cooperative Research Centre.\ 

The project consists of implementing an iterative development and use cycle across three different case studies. This development aspect of this cycle focuses on creating a generic framework for the integration of models to answer policy relevant questions, in this case for improved understanding and reduction of disaster risk. The use process tailors this framework to each of the case study regions, Greater Adelaide, Greater \& Peri-Urban Melbourne and Tasmania.\ 

The focus of 2016-2017 has been on the completion of the first development cycle for Greater Adelaide, with the prototype software to be delivered to end user organisations shortly. Training was also provided to users within the South Australian government and on-going support will be provided to this user group to enable uptake and use within respective departments.\ 

Work has also continued on the Greater \& Peri-urban Melbourne case study with significant process in the data collection and application of the DSS system to the region. Coupled with this has also been the use process of scenario development, with four scenarios for the region currently in draft form prior to follow up sessions in 17-18 to finalise the drafts, quantitatively model the scenarios and look to integrate the exploration of plausible futures to strategy development into organisations.

Similar progress in Tasmania has also been made with the land use model application completed and data collection for the hazard, and exposure modelling ongoing for completion of the first iteration of DSS development by the end of 2017. The participatory use process also saw multiple workshops take place in Tasmania throughout 16/17. These were centred on exploring uncertainties for change in the state, along with collecting data for multiple criteria analysis of risk reduction options, and defining optimisation questions for future analysis.

Other efforts have gone into the publication of journal papers, analysing the current state of literature in the field of decision support for risk reduction planning, and the calibration of land use modelling. Significant effort has also been placed into utilisation activities and exploring future application regions, resulting in a successful NDRP project proposal to apply the DSS in Western Australia.\ 

}, issn = {321}, author = {Holger Maier and Hedwig van Delden and Graeme Riddell and Jeffrey Newman and Aaron Zecchin and Graeme Dandy and Charles Newland} } @conference {bnh-3906, title = {Multi-hazard mitigation planning, combining modelling, scenarios and optimisation: results from South Australia}, booktitle = {AFAC17}, year = {2017}, month = {09/2017}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Sydney}, abstract = {

Natural hazards are an unavoidable component of life in Australia, but with effective planning and mitigation spending, their impacts can be minimised significantly. Analysis shows an average cost of natural hazards in Australia for 2015 totalled $9.6 billion, and this figure is projected to increase to $33 billion by 2050 (Deloitte Access Economics, 2016). These figures correspond to a substantial impact and coupled with the social and environmental impacts of disasters, paint a bleak picture. However, tomorrow{\textquoteright}s risk is a function of decisions made today, including the developments permitted and laws passed, and as such there is significant scope to minimise tomorrow{\textquoteright}s impacts.

To assist in the understanding of tomorrow{\textquoteright}s risk, driven by changing hazards, exposure and vulnerability, a decision support system (DSS) and integrated use process have been developed. This DSS models risk into the future and how it is driven by climatic, economic and demographic factors. Figure 1 shows the integration of risk across exposure, vulnerability and hazard along with some of the factors that are encompassed, as well as the drivers and uncertainties surrounding these factors that make the future so hard to predict.

}, author = {Graeme Riddell and Hedwig van Delden and Roel Vanhout and Holger Maier and Jeffrey Newman and Aaron Zecchin and Graeme Dandy} } @article {bnh-3916, title = {Review of literature on decision support systems for natural hazard risk reduction: current status and future research directions}, journal = {Environmental Modelling \& Software}, volume = {96}, year = {2017}, month = {10/2017}, pages = {378-409}, chapter = {378}, abstract = {

Natural hazard risk is largely projected to increase in the future, placing growing responsibility on decision makers to proactively reduce risk. Consequently, decision support systems (DSSs) for natural hazard risk reduction (NHRR) are becoming increasingly important. In order to provide directions for future research in this growing area, a comprehensive classification system for the review of NHRR-DSSs is introduced, including scoping, problem formulation, the analysis framework, user and organisational interaction with the system, user engagement, monitoring and evaluation. A review of 101 papers based on this classification system indicates that most effort has been placed on identifying areas of risk and assessing economic consequences resulting from direct losses. However, less effort has been placed on testing risk-reduction options and considering future changes to risk. Furthermore, there was limited evidence within the reviewed papers on the success of DSSs in practice and whether stakeholders participated in DSS development and use.

}, doi = {10.1016/j.envsoft.2017.06.042}, url = {http://www.sciencedirect.com/science/article/pii/S1364815216311239}, author = {Jeffrey Newman and Holger Maier and Graeme Riddell and Aaron Zecchin and James Daniell and Andreas Schafer and Hedwig van Delden and Bijan Khazai and Michael O{\textquoteright}Flaherty and Charles Newland} } @article {bnh-2925, title = {Natural hazard mitigation decision support system: Annual project report 2015-2016}, number = {178}, year = {2016}, month = {08/2016}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Decision support systems (DSS) that contain integrate models for the assessment of natural hazard mitigation options are an important component of robust, transparent, and long-term mitigation planning. Integrated modelling of underlying social, environmental, and economic systems is required to take into account system dynamics, and to explore the implications of future changes, such as changes in demographics, land use, economics and climate. Consequently, a generic decision support system for the long-term planning for natural disaster risk reduction is being developed through the Bushfire and Natural Hazards Cooperative Research Centre.\ The project consists of implementing an iterative development and use cycle across three different case studies. The development aspect of this cycle focuses on creating a generic framework for the integration of models to answer policy relevant questions, in this case for improved understanding and reduction of disaster risk. The use process tailors this framework to each of three case study regions, Greater Adelaide, Greater \& Peri-Urban Melbourne and Tasmania.

The focus of 2015-2016 has been on the use cycle for Greater Adelaide, with a first prototype of the software application presented to end-users and five exploratory scenarios qualitatively and quantitatively developed that capture policy-relevant uncertainties in the development of Greater Adelaide. The DSS application in its first iteration provides annual expected losses from coastal inundation, riverine flooding, bushfire and earthquake. The entire use process has been driven by several stages of stakeholder engagement involving SA{\textquoteright}s State Mitigation Advisory Group.\ Work has also begun on the Greater \& Peri-urban Melbourne case study with the first stage of stakeholder engagement occurring on the 21st {\textendash} 23rd October 2015. This involved questionnaires, semi-structured interviews and a workshop to collect information on spatial region, hazards, drivers for change, risk reduction options and indicators of interest. Model development followed focussing initially on the central land use model, and data have also been collected for hazard modelling. Further stakeholder work will occur in the second half of this year including presentation of a first iteration of the software, and its integrated use process of exploratory scenario development.\ The first stage of stakeholder engagement for the Tasmania case study occurred on 4th {\textendash} 6th November 2015. Similar information was collected regarding inputs to the system{\textquoteright}s development. The spatial region considered initially excluded the World Heritage and National Park sites on the South West of the island, but this has changed due to fire events over summer 2015/16. Due to this change in scope the DSS development has been delayed, with a first iteration of the software now planned to be completed in 2017.
Other work has also involved the development of specific hazard models by project team members to be integrated within the systems for each of the case studies. These include a riverine flood and coastal inundation model, and a bushfire risk assessment model co-developed with SA{\textquoteright}s Department of Environment, Water \& Natural Resources (DEWNR).

}, issn = {178}, author = {Holger Maier and Hedwig van Delden and Graeme Riddell and Jeffrey Newman and Aaron Zecchin and Graeme Dandy and Charles Newland} } @conference {bnh-2949, title = {A spatial decision support system for natural hazard risk reduction policy assessment and planning}, booktitle = {AFAC16}, year = {2016}, month = {08/2016}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Brisbane}, abstract = {

The challenges facing environmental policymakers grow increasingly complex and uncertain as more factors that impact on their ability to manage the environment and its risks need to be considered. Due to a large number of influencing environmental and anthropogenic factors, natural hazard risk is difficult to estimate accurately, and exaggerated by large uncertainty in future socioeconomic consequences. Furthermore, resources are scarce, and the benefits of risk reduction strategies are often intangible. Consequently, a decision support system assisting managers to understand disaster risk has great advantage for strategic policy assessment and development, and is the focus of this extended abstract.
The spatial decision support system (SDSS) presented is being developed in collaboration with several South Australian government departments and funded by the Bushfire and Natural Hazards CRC. It integrates multiple hazard models with a land use model which includes information on population and building stock to consider long term spatial and temporal dynamics of natural hazard risk. The integrated SDSS operates at a 100m resolution with a time-step of one year and can be used to model 20{\textendash}50 years into the future. Hazards included in the SDSS include riverine flood, coastal inundation, bushfire, heatwave and earthquake. Each is modelled dependent on the relevant physical properties of the hazard and include the impacts of climate change on hydro-meteorological, bushfire and heatwave hazard. The land use model is driven by land use demand (population and jobs), and allocates land accordingly.

}, author = {Graeme Riddell and Holger Maier and Hedwig van Delden and Jeffrey Newman and Aaron Zecchin and Roel Vanhout and James Daniell and Andreas Schafer and Graeme Dandy and Charles Newland} } @conference {bnh-2089, title = {A decision support framework for multi-hazard mitigation planning - non peer reviewed extended abstract}, booktitle = {Adelaide Conference 2015}, year = {2015}, address = {Adelaide, Australia}, abstract = {

Research proceedings from the Bushfire and Natural Hazards CRC \& AFAC Conference in Adelaide, 1-3 September 2015.\ 

}, author = {Jeffrey Newman and Hedwig van Delden and Graeme Riddell and Charles Newland and Aaron Zecchin and Holger Maier and Roel Vanhout and Ed Pikusa and Graeme Dandy} } @conference {bnh-1560, title = {Integrated Disaster Decision Support System Conference Paper 2014}, booktitle = {Bushfire and Natural Hazards CRC and AFAC Wellington Conference 2014}, year = {2015}, abstract = {

Investing in mitigation activities before a natural disaster occurs can be very effective in reducing disaster losses. However, there can be a number of obstacles to developing and implementing long term mitigation schemes, including a tendency to invest in works with clearer short-term benefits, and the difficulty in accurately attributing risk and benefits to natural disasters and mitigation options, respectively. Decision support systems (DSSs) can be advantageous in helping overcome these obstacles, because of their analytical capabilities to combine various sources of information and support trade-off analysis. However, DSSs for natural disaster mitigation have so far tended to focus on disaster preparedness and the immediate and post-crisis response to emergencies. Consequently, an integrated natural hazard mitigation DSS is being developed. This DSS will optimise the choice of mitigation options in a multicriteria sense, through assessing the performance of various policy options in the long term. Models will be used to evaluate the performance of mitigation options across a number of natural hazards in an integrated way, whilst taking account of land use and climate change. The system will be developed through participatory processes, involving stakeholders from various organisations responsible for hazard mitigation, to ensure the system addresses the most pertinent issues, as well as the decision making process for hazard mitigation. To test the approach in different contexts, it will be applied to three case studies, the first being Greater Adelaide. This paper introduces the proposed DSS.

}, author = {Jeffrey Newman and Holger Maier and Hedwig van Delden and Aaron Zecchin and Graeme Dandy and Ed Pikusa} } @article {bnh-2342, title = {Natural hazard mitigation decision support system: Annual project report 2014-2015}, number = {135}, year = {2015}, month = {02/11/2015}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Decision support systems (DSS) that contain integrated models for the assessment of natural hazard mitigation options are an important component for robust, transparent, and long-term mitigation planning.\  Integrated modelling of underlying social, environmental, and economic systems is required to take into account system dynamics, and to explore the implications of future changes, such as changes in demographics, land use and climate.\  Consequently, a generic decision support system for the long-term planning of natural disaster impact mitigation options is being developed as part of the Bushfire and Natural Hazards Cooperative Research Centre.

Throughout 2014-2015, the project team has focussed on the production of a framework for the {\textquoteleft}development{\textquoteright} and {\textquoteleft}use{\textquoteright} of the DSS. The {\textquoteleft}development{\textquoteright} aspects propose a generic framework for the integration of models to bridge the science-policy gap through a collaboration between scientists, end users and IT specialists. The {\textquoteleft}use{\textquoteright} process focusses on the application of the generic DSS to a region of interest; in this project three case study locations are considered including Greater Adelaide, Greater Melbourne and Tasmania. This involves collaboration between modellers, stakeholders and facilitators to customise, calibrate and validate the case-study specific integrated models. Subsequently, the integrated model is used to support a Storyline and Simulation (SAS)[1] approach that attempts to develop scenarios through a participatory process, wherein the DSS helps build and assess these scenarios through an iterative process.

Additional to the production of this overarching framework has been specific model development to ensure appropriate models are available to consider hazard risk within the integrated DSS. Risk models for flooding, coastal inundation and bushfire have been conceptually developed and will be applied to each case study as appropriate. Each model focuses on changing risk spatially and temporally.

The Greater Adelaide DSS is the first case study application of the generic framework, which began with an extensive intial stakeholder engagement phase in September 2014. This involved identification of key stakeholders, questionnaries, interviews and a whole-day workshop at the University of Adelaide on the 18th of September. From there, critical external drivers and uncertainties were identified, along with aspects of risk and indicators of hazard impact and mitigation performance. These factors have subsequently been incorporated within the DSS for Greater Adelaide and a proto-type DSS will be completed in time for further stakeholder engagement around scenario development and DSS use in October/November 2015.

Greater Melbourne and Tasmania have also begun to progress as case studies. Key contacts have been developed in each location, and with the assistance of these contacts, data and model availability have been discussed for each location, along with identification of stakeholders relevant for each location. The first stage of stakeholder engagement for these case studies, as described for Greater Adelaide, will occur in October/November 2015.\ 

}, issn = {135}, author = {Holger Maier and Hedwig van Delden and Jeffrey Newman and Aaron Zecchin and Graeme Dandy and Graeme Riddell and Charles Newland and Michael O{\textquoteright}Flaherty} } @article {bnh-1536, title = {Natural Hazard Mitigation Decision Support System Annual Report 2014}, year = {2015}, abstract = {

This is an annual report for the year 2013/14 for the Natural Hazard Mitigation Decision Support System project. This project will develop an integrated natural hazard mitigation DSS framework, which will be used to develop prototype DDSs for three case studies.

}, author = {Jeffrey Newman and Holger Maier and Hedwig van Delden and Aaron Zecchin and Graeme Dandy} } @article {bnh-1520, title = {Literature Review on Decision Support Systems for Optimising Long-term Natural Hazard Mitigation Policy and Project Portfolios}, year = {2014}, abstract = {

In this report, literature pertinent to the development of natural hazard mitigation decision support systems is reviewed across four areas:

1. Evidence for the increased frequency of natural hazards and the benefits of mitigation are reviewed.\ \ 

2. Mitigation planning is reviewed, with the presentation of mitigation planning frameworks and classifications of mitigation options.

3. The decision support system (DSS) literature is surveyed to understand current research thrusts in this field.\ \ 

4. The development of emergency management DSSs since the early 1980s is surveyed, with a particular focus on DSSs for mitigation.\ 

Consequently, this report concludes that the development of decision support systems that (i) use state of the art methodologies, (ii) incorporate the use of optimisation within a multihazard approach, (iii) consider changes in climate, demographics, land use and economics, and (iv) assess land-use related mitigation measures in addition to structural and management measures, is both important and novel.

}, author = {Jeffrey Newman and Holger Maier and Hedwig van Delden and Aaron Zecchin and Graeme Dandy and Graeme Riddell and Charles Newland} }