1,354 research outputs found
Adapting to climate risks and extreme weather: guide for mining - minerals industry professionals
AbstractExtreme weather events in Australia over recent years have highlighted the costs for Australian mining and mineral processing operations of being under-prepared for adapting to climate risk. For example, the 2010/2011 Queensland floods closed or restricted production of about forty out of Queensland’s fifty coal mines costing more than $2 billion in lost production.Whilst mining and mineral professionals have experience with risk management and managing workplace health and safety, changes to patterns of extreme weather events and future climate impacts are unpredictable. Responding to these challenges requires planning and preparation for events that many people have never experienced before. With increasing investor and public concern for the impact of such events, this guide is aimed at assisting a wide range of mining and mineral industry professionals to incorporate planning and management of extreme weather events and impacts from climate change into pre-development, development and construction, mining and processing operations and post-mining phases. The guide should be read in conjunction with the research final report which describes the research process for developing the guide and reflects on challenges and lessons for adaptation research from the project.The Institute for Sustainable Futures, University of Technology Sydney (UTS) led the development of the guide with input from the Centre for Mined Land Rehabilitation, University of Queensland and a Steering Committee from the Australasian Institute of Mining and Metallurgy’s Sustainability Committee and individual AusIMM members, who volunteered their time and experience. As the situation of every mining and mineral production operation is going to be different, this guide has been designed to provide general information about the nature of extreme weather events, and some specific examples of how unexpectedly severe flooding, storm, drought, high temperature and bushfire events have affected mining and mineral processing operations. A number of case studies used throughout the guide also illustrate the ways forward thinking operations have tackled dramatically changing climatic conditions.Each section of the guide outlines a range of direct and indirect impacts from a different type of extreme weather, and provides a starting point for identifying potential risks and adaptation options that can be applied in different situations. The impacts and adaptation sections provide guidance on putting the key steps into practice by detailing specific case examples of leading practice and how a risk management approach can be linked to adaptive planning. More information about specific aspects of extreme weather, planning and preparation for the risks presented by these events, and tools for undertaking climate related adaptation is provided in the ‘Additional Resources’ section
Evaluating the risks of pasture and land degradation in native pastures in Queensland
The objective of the project was to develop an approach to quantify the risks of land nd pasture degradation. This objective was achieved by developing an operational model of the condition of native pastures in Queensland.
The results of the project showed that:
1) historical and current pasture data can be used with models to simulate grazing lands in near real-time;
2) spatial models of production can be developed and validated with existing spatial data and monitoring systems;
3) data from graziers indicate that safe utilisation rates are 15-25% of average pasture growth;
4) relative risks of land and pasture can be quantified from simulations using actual numbers compared to safe stocking rates; and
5) case studies using the pasture growth model and models of grazing feedback on pasture and land degradation to evaluate the economic consequences of stocking rate strategies have been used in other projects (e.g. DroughtPlan: McKeon et al. 1996, Stafford Smith et al. 1996)
Final Report : learning system for life prediction of infrastructure
The project has further developed two programs for the industry partners related to service life prediction and salt deposition. The program for Queensland Department of Main Roads which predicts salt deposition on different bridge structures at any point in Queensland has been further refined by looking at more variables. It was found that the height of the bridge significantly affects the salt deposition levels only when very close to the coast. However the effect of natural cleaning of salt by rainfall was incorporated into the program. The user interface allows selection of a location in Queensland, followed by a bridge component. The program then predicts the annual salt deposition rate and rates the likely severity of the environment. The service life prediction program for the Queensland Department of Public Works has been expanded to include 10 common building components, in a variety of environments. Data mining procedures have been used to develop the program and increase the usefulness of the application. A Query Based Learning System (QBLS) has been developed which is based on a data-centric model with extensions to provide support for user interaction. The program is based on number of sources of information about the service life of building components. These include the Delphi survey, the CSIRO Holistic model and a school survey. During the project, the Holistic model was modified for each building component and databases generated for the locations of all Queensland schools. Experiments were carried out to verify and provide parameters for the modelling. These included instrumentation of a downpipe, measurements on pH and chloride levels in leaf litter, EIS measurements and chromate leaching from Colorbond materials and dose tests to measure corrosion rates of new materials. A further database was also generated for inclusion in the program through a large school survey. Over 30 schools in a range of environments from tropical coastal to temperate inland were visited and the condition of the building components rated on a scale of 0-5. The data was analysed and used to calculate an average service life for each component/material combination in the environments, where sufficient examples were available
Analysis of bridge failure due to Cyclone Marcia in Central Queensland using fault tree method
Over the past few years Queensland has suffered from a number of severe tropical cyclones, the most recent one being Marcia, that took place on 20th of February 2015. Damage bill of Marcia exceeded $50 million which included cost of repairing a number of damaged bridges. Failure of road infrastructure isolates communities from accessing essential services and commodities. This necessitated an urgent need to develop a systematic method of assessing the failure of the bridge component to improve the resilience of future bridges and provide base knowledge for developing emergency maintenance response. There are several methods available to investigate the bridge failure. Fault tree analysis (FTA) was selected considering its positive attributes over other methods. FTA was used to estimate the probabilities of failure of main components (Super Structure and Sub Structure) and elements of timber and concrete bridges. Secondary data (Level 1 and level 2 bridge inspection reports from the department of transport and main roads) before and after the cyclone Marcia were used in conjunction with expert consultations to construct fault trees for both timber and concrete bridges. Results indicated potential failure mechanisms and the degree of susceptibility of main components of timber and concrete bridges to cyclonic events. However, the extent of the data was not adequate to draw firm conclusions and further studies (i.e. probabilistic models) are recommended to strengthen the understanding of the complete dynamics of the bridge failure under cyclonic event
Supporting evidence-based adaptation decision-making in the Australian Capital Territory: a synthesis of climate change adaptation research
This research synthesis provides policy-makers and practitioners with an understanding of the building blocks for effective adaptation decision-making, as evidenced through the NCCARF research program. It synthesised a portfolio of adaptation research for each Australian state and territory and addressing the complex relationships between research and policy development. Each state and territory synthesis report directs users to research relevant identified priorities.
Authored by Jennifer Cane, Laura Cacho, Nicolas Dircks and Peter Steele
A prototype framework for models of socio-hydrology: identification of key feedback loops and parameterisation approach
It is increasingly acknowledged that, in order to sustainably manage global
freshwater resources, it is critical that we better understand the nature of
human–hydrology interactions at the broader catchment system scale. Yet to
date, a generic conceptual framework for building models of catchment
systems that include adequate representation of socioeconomic systems – and
the dynamic feedbacks between human and natural systems – has remained
elusive. In an attempt to work towards such a model, this paper outlines a
generic framework for models of socio-hydrology applicable to agricultural
catchments, made up of six key components that combine to form the coupled
system dynamics: namely, catchment hydrology, population, economics,
environment, socioeconomic sensitivity and collective response. The
conceptual framework posits two novel constructs: (i) a composite
socioeconomic driving variable, termed the Community Sensitivity state
variable, which seeks to capture the perceived level of threat to a
community's quality of life, and acts as a key link tying together one of
the fundamental feedback loops of the coupled system, and (ii) a Behavioural
Response variable as the observable feedback mechanism, which reflects land
and water management decisions relevant to the hydrological context. The
framework makes a further contribution through the introduction of three
macro-scale parameters that enable it to normalise for differences in
climate, socioeconomic and political gradients across study sites. In this
way, the framework provides for both macro-scale contextual parameters,
which allow for comparative studies to be undertaken, and catchment-specific
conditions, by way of tailored "closure relationships", in order to ensure
that site-specific and application-specific contexts of socio-hydrologic
problems can be accommodated. To demonstrate how such a framework would be
applied, two socio-hydrological case studies, taken from the Australian
experience, are presented and the parameterisation approach that would be
taken in each case is discussed. Preliminary findings in the case studies
lend support to the conceptual theories outlined in the framework. It is
envisioned that the application of this framework across study sites and
gradients will aid in developing our understanding of the fundamental
interactions and feedbacks in such complex human–hydrology systems, and
allow hydrologists to improve social–ecological systems modelling through
better representation of human feedbacks on hydrological processes
Regional climate projections for the South West of Western Australia to simulate changes in mean and extreme rainfall and temperature
The southwest of Western Australia (SWWA) is an area of significant agricultural production and an internationally recognised biodiversity hotspot. The region has experienced marked rainfall reductions over the last four decades and there is uncertainty as to the extent of future changes to the hydrological regime. Hence, there is a need for regional climate information in SWWA to better inform climate adaptation strategies for several key sectors, including agriculture and forestry. The overarching aim of this project is to provide such information, with a focus on changes in rainfall and temperature extremes.
The Weather Research and Forecasting (WRF) model was used as a regional climate model for SWWA. Given the known sensitivity of WRF to physics options and driving data, the most appropriate physical parameterisations were tested on a yearly time-scale. Based on these findings, a 30-year climatology was produced for SWWA (1981-2010) at a 5 km resolution by downscaling ERA-Interim reanalysis. Comparisons against observations showed that the model was able to simulate the daily, seasonal and annual variation of temperature and precipitation well, including extreme events. The model was then used to downscale an ensemble of 4 general circulation models (GCMs) for the historical period (1970- 1999) and compared against both observations and the GCMs. WRF was shown to add value to the GCM data for 3 out of the 4 GCMs evaluated, particularly in the spatio-temporal distribution of winter rainfall.
Finally, the ensemble was run from 2030-2059 to examine projected climate change in SWWA. Results project that maximum temperature extremes will increase, consistent with mean changes however the variance of maximum temperatures is not projected to change significantly. While mean minimum temperatures are not projected to increase as much as maximum temperatures, there is strong evidence that the variability of minimum temperatures will increase. This has the potential to raise the likelihood of night time temperature extremes. Simulations project a reduction in rainfall, particularly during winter. This decline is related to fewer frontal systems traversing the SWWA and hence fewer rain days. The study found no evidence to suggest that the intensity of rain bearing winter storms is likely to change
The Effect of El Niño Southern Oscillation (ENSO) on World Cereal Production
El Niño Southern Oscillation (ENSO) anomalies are responsible for medium-frequency climate fluctuations across many regions of the world. Not only ENSO induces temperature and precipitation variability in the affected regions, but it is also responsible for larger magnitude weather anomalies, such as droughts, hurricanes, and tsunamis. All these directly impact agricultural production. The overall objective of this research is to determine the relationship between ENSO and world major cereal production. While several studies have addressed the issue, this research contributes to the literature in a number of directions. Firstly, it measures the ENSO effect net of temperature and precipitation. Secondly, it allows for the threshold-like effect of ENSO; that is, El Niño effects are not mirror images of La Niña effects. Thirdly, it incorporates expected price in the regression setting, thus controlling for an important economic variable affecting crop supply. Finally, this study applies the largest possible panel of countries, to analyse the region-specific peculiarities of the ENSO–production relationship, and to best approximate the global production effect of ENSO anomalies. This study uses a combination of extensive climatic and economic datasets spanning the years 1962-2009 to empirically measure the impact of ENSO on wheat, maize and rice production, via a threshold regression framework. The results reveal statistically significant and economically meaningful ENSO impact on cereal production in many regions, with particularly strong effects in Southeast Asian and American countries. Although the expected global effect may camouflage the country-specific effects, the research findings suggest that El Niño shocks are likely to cause on average a reduction in global production of rice and maize. La Niña episodes, on the other hand, are associated with increased global rice and decreased global wheat and maize production. Although consequences of ENSO shocks on a global scale are sporadic, understanding the overall impact of ENSO on major grain production is an important tool for managing global food security. Results of this study provide implications for food policy makers, and help them develop precautionary economic policies that will take advantage of ENSO signals to cope with production shocks and ensure food availability, which is particularly relevant in the developing world
Developing health-related climate indicators: a case study of South Australia
Australia has experienced, and is projected to experience, a range of direct and indirect climate change-related health impacts. Extreme weather events have been associated with substantial increases in morbidity and mortality, as exemplified by the Victorian bushfires in 2009 and the Queensland floods in 2011. Moreover, significant epidemiological evidence of increases in morbidity and mortality during heatwaves has emerged in Australia.
Although the primary public health problem is extreme weather-related morbidity and mortality, a secondary public health problem is that there are limited tools to track the health impacts of climate change and to develop public health interventions in a timely manner. In particular, climate-sensitive health indicators are needed by public health planners and policymakers in order to mitigate the effects for vulnerable subpopulations. This issue has recently been raised at a global level by the Lancet Countdown, an international collaboration aiming to develop and report on a series of health indicators of climate change.
Gap analysis
A scoping review of the literature in the area of climate-sensitive health indicators, together with preliminary consultations with stakeholders in public health agencies, identified three major gaps. Firstly, although climate-related impacts put significant pressure on the health sector, climate-related health indicators are generally not used as part of routine Australian health evaluation. In contrast, some such indicators have been developed in other countries and are currently used by the European Environmental Agency. Secondly, due to differences in climate characteristics and demographics, there is a need to identify a set of evidence-based climate-sensitive health indicators specifically for use in Australia. Finally, the feasibility and usability of such indicators in an Australian context should be investigated.Thesis (Ph.D.) -- University of Adelaide, School of Public Health, 201
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