ORCID Profile
0000-0001-5708-1807
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Water Resources Engineering | Civil Engineering | Applied Statistics | Atmospheric Sciences | Statistics | Natural Resource Management | Physical Oceanography | Meteorology | Knowledge Representation and Machine Learning | Climate Change Processes
ANZSRC Socio-Economic Objective (SEO)
Natural Hazards in Fresh, Ground and Surface Water Environments | Effects of Climate Change and Variability on Australia (excl. Social Impacts) | Environmental Management Systems | Atmospheric Processes and Dynamics | Climate Change Models | Expanding Knowledge in the Information and Computing Sciences | Precious (Noble) Metal Ore Exploration | Mining Land and Water Management | Health Protection and/or Disaster Response | Rural Water Evaluation (incl. Water Quality) |
Related Links
Publications
Natural hazards in Australia: floods
Publisher: Springer Science and Business Media LLC
Date: 11-05-2016
Addressing Spatial Dependence Bias in Climate Model Simulations—An Independent Component Analysis Approach
Publisher: American Geophysical Union (AGU)
Date: 02-2018
DOI: 10.1002/2017WR021293
Modelling the influence of short-term climate variability on drinking water quality in tropical developing countries: A case study in Tanzania
Publisher: Elsevier BV
Date: 04-2021
A systematic review of climate change science relevant to Australian design flood estimation
Publisher: Copernicus GmbH
Date: 10-10-2023
A method for combining SRTM DEM and ASTER GDEM2 to improve topography estimation in regions without reference data
Publisher: Elsevier BV
Date: 06-2018
Assessing the Potential Robustness of Conceptual Rainfall‐Runoff Models Under a Changing Climate
Publisher: American Geophysical Union (AGU)
Date: 07-2018
DOI: 10.1029/2018WR022636
A nesting model for bias correction of variability at multiple time scales in general circulation model precipitation simulations
Publisher: American Geophysical Union (AGU)
Date: 2012
DOI: 10.1029/2011WR010464
A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations
Publisher: Elsevier BV
Date: 07-2017
Supplementary material to "Do Southern Hemisphere tree rings record past volcanic events?"
Publisher: Copernicus GmbH
Date: 17-12-2021
A New Framework for Modeling Future Hydrologic Extremes: Nested Bias Correction as a Precursor to Stochastic Rainfall Downscaling
Publisher: American Society of Civil Engineers
Date: 07-02-2013
How reliable are GCM simulations for different atmospheric variables?
Publisher: Springer Science and Business Media LLC
Date: 14-10-2017
How well do general circulation models represent low-frequency rainfall variability?
Publisher: American Geophysical Union (AGU)
Date: 03-2014
DOI: 10.1002/2012WR013085
Identifying Sustained Drought Anomalies in Hydrological Records: A Wavelet Approach
Publisher: American Geophysical Union (AGU)
Date: 27-07-2018
DOI: 10.1029/2018JD028455
Addressing the mischaracterization of extreme rainfall in regional climate model simulations – A synoptic pattern based bias correction approach
Publisher: Elsevier BV
Date: 2018
Examining past and projecting future: an 800-year streamflow reconstruction of the Australian Murray river
Publisher: IOP Publishing
Date: 25-09-2023
Do Southern Hemisphere tree rings record past volcanic events?
Publisher: Copernicus GmbH
Date: 17-12-2021
DOI: 10.5194/CP-2021-171
Abstract: Abstract. Much of our knowledge about the impacts of volcanic events on climate comes from proxy records. However, little is known about the impact of volcanoes on trees from the Southern Hemisphere. We investigated whether volcanic signals could be identified in ring widths from eight New Zealand dendrochronological species, using superposed epoch analysis. We found that most species are good recorders of volcanic dimming and that the magnitude and persistence of the post-event response can be broadly linked to plant life history traits. Across species, site-based factors, particularly altitude and exposure to prevailing conditions, are more important determinants of the strength of the volcanic response than the species. We then investigated whether proxy selection impacts the magnitude of post-volcanic cooling in tree-ring based temperature reconstructions by developing two new multispecies reconstructions of New Zealand summer (December–February) temperature. Both reconstructions showed temperature anomalies remarkably consistent with studies based on instrumental temperature, and with the ensemble mean response of climate models, demonstrating that New Zealand ring widths are reliable indicators of regional volcanic climate response. However, we also found that volcanic response is complex, with positive, negative, and neutral responses identified – sometimes within the same species group. Species-wide composites thus tend to underestimate the volcanic response. The has important implications for the development of future tree ring and multiproxy temperature reconstructions from the Southern Hemisphere.
Investigating strategies to improve hydrologic model performance in a changing climate
Publisher: Elsevier BV
Date: 12-1212
Integrating Remote Sensing and Numerical Modeling to Quantify the Water Balance of Climate‐Induced Intermittent Wetlands
Publisher: American Geophysical Union (AGU)
Date: 10-2021
DOI: 10.1029/2020WR029310
Abstract: Wetlands are an important habitat for many species but over the past few decades ecosystem bio ersity and function have been threatened. Due to their shallow and fluctuating water levels, wetlands are particularly vulnerable to climate variability. This is especially a risk for ephemeral and intermittent wetlands with limited hydrologic connections to deep aquifers, designated herein as Climate‐induced Intermittent Wetlands (CiIWs). However, the response of CiIW systems to long‐term climate variability has received limited research attention, partly because continuous ground surface monitoring data is rarely available over inter‐decadal periods. An alternative to ground surface data is the use of satellite imagery to estimate the temporal water extent variability. An integrated remote sensing and modeling approach is presented here to provide a novel method for investigating historical water storage variations in a CiIW system. The new method estimates water levels in a shallow wetland using Landsat data and was successfully validated against field water level data. The new method performed better than five existing algorithms. A water balance model was calibrated using the combined remotely sensed and local field data to derive daily water level time series since 1900. The validated water balance model results indicated that most of the water level fluctuations in the intermittent wetland can be explained by climatic drivers and subsurface flow interactions. Overall, this study demonstrates the importance of an integrated remote sensing and water balance modeling approach for hydroclimatic analysis of intermittent wetlands.
Spatial Variation in Catchment Response to Climate Change Depends on Lateral Moisture Transport and Nutrient Dynamics
Publisher: American Geophysical Union (AGU)
Date: 10-2022
DOI: 10.1029/2021WR030577
Abstract: Future shifts in rainfall, temperature and carbon dioxide (CO 2 ) will impact hydrologic and ecosystem behavior. These changes are expected to vary in space because water and nutrient availability vary with terrain and soil properties, with feedbacks on vegetation and canopy adjustment. However, within‐basin patterns and spatial dependencies of ecohydrologic dynamics have often been ignored in future scenario modeling. We used a distributed process‐based ecohydrologic model, the Regional Hydro‐Ecological Simulation System, as a virtual catchment to examine spatial and temporal variability in climate change response. We found spatial heterogeneity in Leaf Area Index, transpiration and soil saturation trends, with some scenarios even showing opposite trends in different locations. For ex le, in a drying scenario, decreased vegetation productivity in water‐limited upslope areas enhanced downslope nutrient subsidies so that productivity increased in the nutrient‐limited riparian zone. In scenarios with both warming and rising CO 2 , lifying feedbacks between mineralization, vegetation water use efficiency and litter fall led to large increases in growth that were often strongest in the riparian area (depending on the coincident rainfall change). Modeled transpiration trends were determined by the competing effects of vegetation growth and changing water use efficiency. Overall, the riparian zone experienced substantially different (and even opposing) ecohydrologic trends compared to the rest of the catchment, which is important because productive riparian areas often contribute a disproportionate amount of vegetation growth, transpiration and nutrient consumption to catchment totals. Models that are spatially lumped, lack key ecosystem‐driving dynamics, or ignore lateral transport could misrepresent the complex ecohydrologic changes catchments could experience in the future.
Can examining past variability help us understand catchment response to future climate change?
Publisher: Copernicus GmbH
Date: 27-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-3319
Abstract: & & It is common to test hydrologic models under contrasting historical periods as an indicator of likely performance under climate change. For ex le, a model calibrated under average conditions may be tested under increasingly dry subsets of the observational record. Any decline in performance as the testing conditions deviate further from the calibration conditions is then assumed to represent likely performance degradation under climate change scenarios with comparable rainfall decreases. Many studies have inherently applied the assumption that past rainfall variability can be used as a proxy for future climate change, but the analogy may be flawed for three main reasons:& & & ul& & li& Due to lagged hydrologic response to meteorological shifts, catchment behaviour under long-term wetting or drying may not be fully represented over shorter wet or dry periods.& /li& & li& Subsets of the past record selected based on rainfall are unlikely to reflect future temperature increases.& /li& & li& Past observations do not include expected increases in carbon dioxide levels.& /li& & /ul& & & If any of these factors substantially impacts catchment response, subsets of the historical record with equivalent rainfall will not be accurate proxies for future climate scenarios. We tested the impact of each factor using the ecohydrologic model RHESSys. RHESSys dynamically simulates vegetation growth, subsurface flow and nutrient cycling and is thus able to capture the key processes that could drive nonstationary catchment response in the future. We found that all three future climate factors (rainfall change persistence, temperature, and carbon dioxide) altered catchment response substantially, especially for drier future scenarios. For our study catchment, persistence of dry conditions over many decades led to different subsurface water storage levels than the same rainfall experienced over shorter timeframes, leading to different streamflow. The impacts of increased temperature and carbon dioxide concentrations on vegetation further altered runoff behaviour. This means that long-term climate change effects will not necessarily emerge over short historical periods with equivalent rainfall. In our ex le, ignoring persistence in rainfall changes, rising temperatures, and higher carbon dioxide levels could lead us to underestimate model performance degradation in terms of Nash-Sutcliffe efficiency by as much as 0.41. Therefore, the uncertainty introduced in hydrologic models by future climate change has probably been underestimated in the current literature.& &
Measurement of GCM Skill in Predicting Variables Relevant for Hydroclimatological Assessments
Publisher: American Meteorological Society
Date: 15-08-2009
Abstract: Simulations from general circulation models are now being used for a variety of studies and purposes. With up to 23 different GCMs now available, it is desirable to determine whether a specific variable from a particular model is representative of the ensemble mean, which is often assumed to indicate the likely state of that variable in the future. The answers are important for decision makers and researchers using selective model outputs for follow-on studies such as statistical downscaling, which currently assume all model outputs are simulated with equal reliability. A skill score, termed the variable convergence score (VCS), has been derived that can be used to rank variables based on the coefficient of variation of the ensemble. The key benefit is the development of a simple methodology that allows for a quantitative assessment between different hydroclimatic variables. The VCS methodology has been applied to the outputs of nine GCMs for eight different variables and two emission scenarios to provide a relative ranking of the variables averaged across Australia and over different climatic regions of the country. The methodology, however, would be applicable for any region or any variable of interest from GCMs. It was found that the surface variables with the highest scores are pressure, temperature, and humidity. Regionally in Australia, models again show the best agreement in the surface pressure projections. The tropical and southwestern temperate zones show the overall highest variable convergence when all variables are considered. The desert zone shows relatively low model agreement, particularly in the projections of precipitation and specific humidity.
Social production of ignorance – the role for geoscientists in addressing “undone science”
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-13910
Abstract: In this presentation we discuss the role of geoscientists and engineers in advocating for improved civic science that can minimise the impacts of industrial and mining activities on the environment and downstream communities, with a particular focus on water-related impacts. We argue that, if not carefully designed, data collection, analyses and communication by geoscientists does not always contribute to the wider public good because the issues that communities care about are not addressed & #8211 so called & #8220 undone science& #8221 . A case study, focusing on the environmental impacts of the McArthur River mine (MRM) in a remote part of the Northern Territory, Australia, is used to highlight key issues that should inform civic science and lead to better outcomes for communities and the environment.Despite thousands of pages of & #8220 data& #8221 about the MRM project and its impacts, we argue that this project is an ex le of the social production of ignorance & #8211 because the knowledge of the communities most impacted by the mine& #8217 s activities is not improved by the reporting and impact assessments associated with the project. Based on a temporal synthesis of independent monitoring reports of the McArthur River Mine which covered the period from 2007 to 2018, we identify three main lessons for improving civic science. Firstly, without adequate baseline monitoring prior to development, data collection during a project cannot satisfactorily assess impacts of a development. Baseline data is particularly important when seasonal and interannual variability is high. Baseline and ongoing monitoring programs should be co-designed with the community, so that what matters to the community is monitored (e.g. culturally important sites, contamination in animal species relevant to the community). Secondly, geoscientists and engineers need to partner with social scientists and local community organisations to ensure that communities are effectively informed about the impacts of development, focusing on the impacts that matter to communities, not just the impacts that are conveniently measured. Finally regulatory processes need to be improved to ensure that problems identified by geoscientists and engineers are addressed.
Using second-order approximation to incorporate GCM uncertainty in climate change impact assessments
Publisher: Springer Science and Business Media LLC
Date: 18-03-2017
Using remotely sensed data to understand global lake colour variability
Publisher: Copernicus GmbH
Date: 26-02-2023
DOI: 10.5194/EGUSPHERE-EGU23-13595
Abstract: & & Water colour can reflect waterbody health and environmental conditions of inland waterbodies. As a result, changes in water colour may be associated with environmental dynamics resulting from either climate or catchment changes or both. In the absence of long term, spatially comprehensive global databases of lake water quality, satellite-derived water colour can be used to understand water quality variability. Here we analyse the spatial-temporal variability of water colour for nearly 200,000 inland waterbodies around the world using Landsat 5, 7, and 8 images for 35 years. We investigated the spatial variability in the baseline water colour and temporal patterns of water colour across 41 climate reference regions. We found that the mean dominant wavelengths of small waterbodies were constantly higher (less blue) than larger waterbodies. We also found that most waterbodies became increasingly bluer, with an average change of -14.5 nm & #177 0.15nm over the 35-year study period. The exception were waterbodies in north-eastern Russia which tended to shift towards red wavelengths. The waterbodies were grouped based on their inter-annual water colour change and intra-annual variation (standard deviation) in water colour. Intra-annual variability increased for two thirds of the waterbodies over the study period. Around 20% of the waterbodies have tended to shift to redder wavelengths accompanied by increased intra-annual variation, which may indicate they are more vulnerable to environmental stresses. The findings from this work provide a strong baseline understanding of historical global lake water quality variability with which future projected climate change impacts can be compared.& &
Wavelet-based post-processing of NWP precipitation forecasts
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-14123
Abstract: Reliable flood forecasts are dependent on accurate quantitative precipitation forecasts. Despite improvements in the resolution and schematisation of Numerical Weather Prediction (NWP) models, there are still substantial biases in their precipitation forecasts. Biases are present at a range of time scales and correctly representing the multi-temporal scale properties of precipitation including its persistence and variability is vital. In this presentation a new method for post-processing NWP model precipitation forecasts is developed. The new method is based on continuous wavelet transforms (CWT) which correct the statistical characteristics of the precipitation forecasts across a range of time scales. The precipitation amounts are corrected using a simple quantile mapping of the litude of each time scale of the wavelet decomposition. To account for uncertainty in precipitation timing, we also adjust the phase of the CWT randomly to create an ensemble of post-processed forecasts. Spatial correlations are preserved by maintaining the same phase adjustments at each different precipitation forecast location. & The new method is demonstrated using hourly forecast data from the ACCESS model over the period March 2018 to September 2021 & for a network of 158 gauges around Sydney, in eastern Australia. The new method improves the correlation of the forecasts and reduces the root mean square error. The spatial correlation structure of the post-processed forecasts is also improved. Correctly representing spatial patterns of precipitation is vital to ensure that catchment averaged precipitation and the resulting flood forecasts are correct.
Does storm duration modulate the extreme precipitation-temperature scaling relationship?
Publisher: American Geophysical Union (AGU)
Date: 28-10-2015
DOI: 10.1002/2015GL066274
Merging radar and in situ rainfall measurements: An assessment of different combination algorithms
Publisher: American Geophysical Union (AGU)
Date: 10-2016
DOI: 10.1002/2015WR018441
Climate change and hydrological risk in the Pacific: a Humanitarian Engineering perspective
Publisher: IWA Publishing
Date: 25-01-2021
DOI: 10.2166/WCC.2021.277
Abstract: Pacific Island communities have adapted to floods, droughts and cyclones over many generations. Small and low-lying islands are particularly exposed to natural disasters, and many countries have limited access to water resources. Anthropogenic climate change is expected to further increase these environmental pressures. Any associated engineering response needs to consider the cultural, societal and historical context, and prioritise the agency of local communities to determine their preferred outcomes. It follows that Humanitarian Engineering, a discipline centred around strengths-based and context-appropriate solutions, has an important role to play in climate change adaptation. In this review, the interplay between hydroclimatology, geography and water security in the Pacific Islands is described and projected climate shifts summarised to highlight future adaptation challenges. A key source of uncertainty relates to the dynamics of two convergence zones that largely drive weather patterns. A broad overview of societal factors that present challenges and opportunities for Humanitarian Engineers is given. Finally, actions are recommended to inform climate change adaptation given the scientific uncertainty around hydrologic risks, and outline lessons for best practice Humanitarian Engineering in the Pacific. Enhancing data sharing, building resilience to climate variability and integrating traditional knowledge with convention engineering methods should be key areas of focus.
Merging Alternate Remotely-Sensed Soil Moisture Retrievals Using a Non-Static Model Combination Approach
Publisher: MDPI AG
Date: 21-06-2016
DOI: 10.3390/RS8060518
A comparison of methods to estimate future sub-daily design rainfall
Publisher: Elsevier BV
Date: 12-2017
Forecasting drought revisited – the importance of spectral transformations to dominant atmospheric predictor variables
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-12334
Abstract: & & As we write this abstract, Australia is experiencing widespread forest fires, Sydney has declared significant water restriction measures curtailing demand, and the entire country is experiencing a drought that is amongst the worst on record. Formulating a stable and practical approach for predicting drought into the future is being realised as an important need, as we enter an era of warmer climates that complicate this problem to an even greater extent. This study presents a novel basis for forecasting drought into the future. Use is made of a recently developed wavelets based methodology for transforming predictor variables so as to force greater consistency in spectral attributes with the response being modelled. Using a commonly adopted drought index, we demonstrate how the wavelets transformed predictor variables can be used to model the response with greater accuracy than otherwise. These transformed predictor variables are then used in conjunction with CMIP5 decadal climate forecasts to demonstrate the accuracy attainable at longer lead times than is currently possible. While our application focusses on the Australian mainland, the method is generic and can be adopted anywhere.& &
Remote sensing to detect harmful algal blooms in inland waterbodies
Publisher: Elsevier BV
Date: 12-2022
DOI: 10.1016/J.SCITOTENV.2022.158096
Abstract: Harmful algal blooms (HABs) are an issue of concern for water management worldwide. As such, effective monitoring strategies of HAB spatio-temporal variability in waterbodies are needed. Remote sensing has become an increasingly important tool for HAB detection and monitoring in large lakes. However, accurate HAB detection in small-medium waterbodies via satellite data remains a challenge. Current barriers include the waterbody size, the limited freely available high resolution satellite data, and the lack of field calibration data. To test the applicability of remote sensing for detecting HABs in small-medium waterbodies, three satellites (Planetscope, Sentinel-2 and Landsat-8) were used to understand how spatial resolution, the availability of spectral bands, and the waterbody size itself effect HAB detection skill. Different algorithms and a non-parametric method, Self-Organizing Map (SOM), were tested. Curvature Around Red and NIR minus Red had the best HAB detection skill of the 20 existing algorithms that were tested. Landsat 8 and Sentinel 2 were the best satellites for HAB detection in small to medium waterbodies. The most critical attribute for detecting HABs were the available satellite bands, which determine the detection algorithms that can be used. Importantly, algorithm performance was mostly unrelated to waterbody size. However, there remain some barriers in utilizing satellite data for HAB detection, including algae dynamics, macrophyte cover within the waterbody, weather effects, and the correction models for satellite data. Moreover, it is important to consider the match time between satellite overpass and s ling activities for calibration. Given these challenges, integrating regular s ling activities and remote sensing is recommended for monitoring and managing small-medium waterbodies.
Implications of future climate change for event-based hydrologic models
Publisher: Elsevier BV
Date: 09-2018
A global comparison of alternate AMSR2 soil moisture products: Why do they differ?
Publisher: Elsevier BV
Date: 05-2015
Assessing the extent of non-stationary biases in GCMs
Publisher: Elsevier BV
Date: 06-2017
An Assessment of GCM Skill in Simulating Persistence across Multiple Time Scales
Publisher: American Meteorological Society
Date: 15-07-2011
Abstract: Climate change impact studies for water resource applications, such as the development of projections of reservoir yields or the assessment of likely frequency and litude of drought under a future climate, require that the year-to-year persistence in a range of hydrological variables such as catchment average rainfall be properly represented. This persistence is often attributable to low-frequency variability in the global sea surface temperature (SST) field and other large-scale climate variables through a complex sequence of teleconnections. To evaluate the capacity of general circulation models (GCMs) to accurately represent this low-frequency variability, a set of wavelet-based skill measures has been developed to compare GCM performance in representing interannual variability with the observed global SST data, as well as to assess the extent to which this variability is imparted in precipitation and surface pressure anomaly fields. A validation of the derived skill measures is performed using GCM precipitation as an input in a reservoir storage context, with the accuracy of reservoir storage estimates shown to be improved by using GCM outputs that correctly represent the observed low-frequency variability. Significant differences in the performance of different GCMs is demonstrated, suggesting that judicious selection of models is required if the climate impact assessment is sensitive to low-frequency variability. The two GCMs that were found to exhibit the most appropriate representation of global low-frequency variability for in idual variables assessed were the Istituto Nazionale di Geofisica e Vulcanologia (INGV) ECHAM4 and L’Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL CM4) when considering all three variables, the Max Planck Institute (MPI) ECHAM5 performed well. Importantly, models that represented interannual variability well for SST also performed well for the other two variables, while models that performed poorly for SST also had consistently low skill across the remaining variables.
The Effectiveness of Global Constructed Shallow Waterbody Design Guidelines to Limit Harmful Algal Blooms
Publisher: American Geophysical Union (AGU)
Date: 08-2021
DOI: 10.1029/2020WR028918
Abstract: Constructed shallow waterbodies are often designed and built to limit harmful algal blooms in urban regions. Efforts to reduce algal bloom occurrence in these waterbodies have largely focused on waterbody design, catchment criteria and onsite engineering options. However, many constructed shallow waterbodies that comply with design guidelines still experience harmful algal blooms. Identifying the knowledge gaps in current guidelines and examining their recommended design criteria can improve their effectiveness to reduce algal outbreaks. Here, we reviewed 66 global guidelines and identified common design criteria. The use of a ‘one size fits all' empirical approach and dated literature are common issues associated with the design criteria recommended. Further, only approximately one third of the guidelines that were analyzed directly mentioned harmful algal bloom‐related design criteria. To test the validity of these design values in a real‐world setting, the suitability of design factors in limiting harmful algal blooms was assessed by analyzing 222 shallow waterbodies monitored over a 9 year period in southeastern Australia. The site analysis indicated that macrophyte area to surface area ratio, shoreline development index, and fetch are the three most influential single design factors associated with harmful algal bloom reduction. The analyses highlighted the ineffectiveness of the existing design criteria globally, with blooms occurring even though some waterbodies were designed in accordance with recommended parameters. The analysis suggested that understanding interactions between multiple design factors may be a useful approach, for ex le, when considering the macrophyte area to surface area ratio in combination with the shoreline development index.
A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation
Publisher: American Geophysical Union (AGU)
Date: 18-08-2015
DOI: 10.1002/2015GL064981
Non-stationarity in extreme rainfalls across Australia
Publisher: Elsevier BV
Date: 09-2023
Unprecedented High Northern Australian Streamflow Linked to an Intensification of the Indo‐Australian Monsoon
Publisher: American Geophysical Union (AGU)
Date: 03-2022
DOI: 10.1029/2021WR030881
Abstract: Streamflow in Australia’s northern rivers has been steadily increasing since the 1970s, most likely due to increased intensity in the Indo‐Australian monsoon. However, because of limited data availability, it is hard to assess this recent trend and therefore contextualize potential future climatic changes. In this study, we used a network of 63 precipitation‐sensitive tree‐ring chronologies from the Indo‐Australian and Asian monsoon regions to reconstruct streamflow in the Daly catchment in the Northern Territory of Australia from 1413 to 2005 CE. We used a novel wavelet‐based method to transform the variance structure of the tree‐ring chronologies to better match the hydroclimate prior to reconstruction with a hierarchical Bayesian regression model. Our streamflow reconstruction accounts for 72%–78% of the variance in the instrumental period and closely matches both historical flood events and independent proxy records, increasing confidence in its validity. We find that while streamflow has been increasing since the 1800s, the most recent 40‐year period is unprecedented in the last ∼600 years. Comparison to an independent coral‐based streamflow record shows regional coherency in this trend. Extreme high flows were found to be linked to La Niña events, but we found no significant relationship between streamflow and El Niño events, or streamflow and other regional climatic drivers. More work is therefore needed to understand the drivers of the recent streamflow increase, but, regardless of the cause, water managers should be aware of the paleoclimatic context before making decisions on water allocations.
Comparing three methods to form regions for design rainfall statistics: Two case studies in Australia
Publisher: Elsevier BV
Date: 08-2015
A comparison of methods for estimating climate change impact on design rainfall using a high-resolution RCM
Publisher: Elsevier BV
Date: 04-2017
What are the impacts of bias correction on future drought projections?
Publisher: Elsevier BV
Date: 06-2015
Evaluating the effect of climate change on areal reduction factors using regional climate model projections
Publisher: Elsevier BV
Date: 09-2015
A Comparison of Australian Open Water Body Evaporation Trends for Current and Future Climates Estimated from Class A Evaporation Pans and General Circulation Models
Publisher: American Meteorological Society
Date: 02-2010
Abstract: Trends of decreasing pan evaporation around the world have renewed interest in evaporation and its behavior in a warming world. Observed pan evaporation around Australia has been modeled to attribute changes in its constituent variables. It is found that wind speed decreases have generally led to decreases in pan evaporation. Trends were also calculated from reanalysis and general circulation model (GCM) outputs. The reanalysis reflected the general pattern and magnitude of the observed station trends across Australia. However, unlike the station trends, the reanalysis trends are mainly driven by vapor pressure deficit changes than wind speed changes. Some of the GCMs modeled the trends well, but most showed an average positive trend for Australia. Half the GCMs analyzed show increasing wind speed trends, and most show larger changes in vapor pressure deficit than would be expected based on the station data. Future changes to open water body evaporation have also been assessed using projections for two emission scenarios. Averaged across Australia, the models show a 5% increase in open water body evaporation by 2070 compared to 1990 levels. There is considerable variability in the model projections, particularly for the aerodynamic component of evaporation. Assumptions of increases in evaporation in a warming world need to be considered in light of the variability in the parameters that affect evaporation.
Understanding the Impacts of Short‐Term Climate Variability on Drinking Water Source Quality: Observations From Three Distinct Climatic Regions in Tanzania
Publisher: American Geophysical Union (AGU)
Date: 04-2019
DOI: 10.1029/2018GH000180
Do Southern Hemisphere tree rings record past volcanic events? A case study from New Zealand
Publisher: Copernicus GmbH
Date: 24-05-2022
Abstract: Abstract. Much of our knowledge about the impacts of volcanic eruptions on climate comes from proxy records. However, little is known about their impact on the low to mid-latitudes of the Southern Hemisphere. Using superposed epoch analysis, we investigated whether volcanic signals could be identified in annual tree-ring series from eight New Zealand dendrochronological species. We found that most species are reliable recorders of volcanic cooling and that the magnitude and persistence of the post-event response can be broadly linked to plant life history traits. Across species, site-based factors, particularly altitude and exposure to prevailing conditions, are more important determinants of the strength of the volcanic response than species. We then investigated whether chronology selection impacts the magnitude of post-volcanic cooling in tree-ring-based temperature reconstructions by developing two new multispecies reconstructions of New Zealand summer (December–February) temperature with one reconstruction from the pool of all available chronologies, and the other from a selected subset shown to be sensitive to volcanic eruptions. Both reconstructions record temperature anomalies that are remarkably consistent with studies based on instrumental temperature and the ensemble mean response of climate models, demonstrating that New Zealand ring widths are reliable indicators of regional volcanic climate response. However, we also found that volcanic response can be complex, with positive, negative, and neutral responses identified – sometimes within the same species group. Species-wide composites thus tend to underestimate the volcanic response. This has important implications for the development of future tree-ring and multiproxy temperature reconstructions from the Southern Hemisphere.
Building a Flood-Warning Framework for Ungauged Locations Using Low Resolution, Open-Access Remotely Sensed Surface Soil Moisture, Precipitation, Soil, and Topographic Information
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2018
Accounting for interannual variability: A comparison of options for water resources climate change impact assessments
Publisher: American Geophysical Union (AGU)
Date: 04-2011
DOI: 10.1029/2010WR009272
Do Derived Drought Indices Better Characterize Future Drought Change?
Publisher: American Geophysical Union (AGU)
Date: 27-06-2023
DOI: 10.1029/2022EF003350
Abstract: Current methods for climate change assessment ignore the significant differences in uncertainty in model projections of the two key constituents of drought, precipitation, and evapotranspiration. We present here a new basis for assessing future drought using climate model simulations that addresses this limitation. The new method estimates the Standardized Precipitation Evapotranspiration Index (SPEI) in a two‐stage process. The first stage of our proposed approach is to derive the Standardized Precipitation Index (SPI) using reliable atmospheric variables, which are filtered with a wavelet‐based spectral transformation. This derived SPI is then converted to an equivalent SPEI by combining it with climate model evapotranspiration simulations. We assess the performance of our proposed approach across Australia. The consistency of general circulation model (GCM) drought projections, in terms of both frequency and severity, is improved using the derived SPI. Incorporating evapotranspiration further improves the consistency of the multiple GCMs and drought time scales. The proposed framework can also be generalized to other water resources applications, where the differences in GCM uncertainty for precipitation and evapotranspiration affect climate change impact assessments.
Refining Predictor Spectral Representation Using Wavelet Theory for Improved Natural System Modeling
Publisher: American Geophysical Union (AGU)
Date: 03-2020
DOI: 10.1029/2019WR026962
Landscape changes and their hydrologic effects: Interactions and feedbacks across scales
Publisher: Elsevier BV
Date: 2021
Water resources climate change projections using supervised nonlinear and multivariate soft computing techniques
Publisher: Elsevier BV
Date: 05-2016
Spatial Disaggregation of Coarse Soil Moisture Data by Using High-Resolution Remotely Sensed Vegetation Products
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2017
Future changes to the intensity and frequency of short-duration extreme rainfall
Publisher: American Geophysical Union (AGU)
Date: 27-08-2014
DOI: 10.1002/2014RG000464
Influence of resampling techniques on Bayesian network performance in predicting increased algal activity
Publisher: Elsevier BV
Date: 08-2023
Which Rainfall Errors Can Hydrologic Models Handle? Implications for Using Satellite‐Derived Products in Sparsely Gauged Catchments
Publisher: American Geophysical Union (AGU)
Date: 08-2022
DOI: 10.1029/2020WR029331
Abstract: There is interest in applying satellite‐derived rainfall products for water management in data‐sparse areas. However, questions remain around how uncertainties in different products interact with hydrologic models to determine simulation skill. Most related work uses performance statistics that inherently combine rainfall magnitude, timing and persistence, making it unclear which product improvements should be prioritized. We applied six satellite‐derived rainfall products in a conceptual hydrologic model (GR4J) across four Australian catchments with dense gauge data for comparison. We found that GR4J's inherent flexibility allowed it to filter errors in rainfall magnitude and variance through parameterization. Therefore, when rainfall observations for bias correction are unavailable, calibration of a flexible model could prove a useful alternative. However, the model was less able to compensate for errors in rainfall occurrence. In fact, the Probability of Detection score explained 59% of the variance in calibration performance (26% for validation), while overall bias explained just 14% (8% for validation). All products underestimated rainfall state persistence, but this had less influence on model skill. We then removed gauges from the observed data set to mimic data sparsity, finding that even a few gauges could reproduce rainfall occurrence and outperform satellite‐derived products. Two data‐sparse catchments in Vietnam were modeled to check whether the same learnings applied. The gauge data also performed best in Vietnam, and performance of most satellite‐derived products was comparable to the Australian case. Efforts to increase the spatial and temporal resolution of satellite observations, which could improve rainfall detection, will enhance satellite‐derived precipitation for hydrologic modeling.
Residual Mass Severity Index (RMSI) – a duration free method to characterise droughts
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-6317
Abstract: & & The complexity of representing droughts has led to many drought indices being developed. A common aspect for many of these indices, however, is the need to adopt a predefined time period, over which a drought is characterized. Therefore, to declare a catchment as drought-impacted, 6, 12 or 24-month SPI are required. Actual water allocations, however, are required at all times and are thus duration free a concept well described by the well-known residual mass curve. Here we propose a new framework to characterize drought, termed as the Residual Mass Severity Index (RMSI). As the name suggests, the RMSI defines drought based on the magnitude of the residual mass in any location which is calculated by performing a water balance using a prescribed demand. Demand here is adopted as the median monthly precipitation for the region. Water shortages only become significant when there is a sustained deficit compared to this demand. The above described residual mass is standardized to formulate the RMSI across Australia. The new RMSI has been validated against established drought indices (such as the SPI) to highlight the advantages of a duration-free drought index.& & & & RMSI provides a simple method of assessing sustained and severe drought anomalies which is important with expected increases in water scarcity due to anthropogenic climate change. We demonstrate that RMSI can be used as a tool to evaluate the performance of General Circulation Models (GMCs) in representing the sustainability of water resource systems as a product of resilience, reliability, and vulnerability (RRV) of the system. Future projections of drought from GCMs which perform well in representing RMSI in the RRV context in the historical climate are then compared to drought projections from the full CMIP5 ensemble.& & & & Keywords: Drought, Residual Mass Curve, SPI, RRV, Climate Change, CMIP5 GCMs& &
A new framework for monitoring flood inundation using readily available satellite data
Publisher: American Geophysical Union (AGU)
Date: 16-03-2016
DOI: 10.1002/2016GL068192
Improving radar rainfall estimation by merging point rainfall measurements within a model combination framework
Publisher: Elsevier BV
Date: 11-2016
Continental-scale bias-corrected climate and hydrological projections for Australia
Publisher: Copernicus GmbH
Date: 03-2023
DOI: 10.5194/GMD-2023-7
Abstract: Abstract. The Australian Bureau of Meteorology has developed a national hydrological projections (NHP) service for Australia. With the focus on hydrological change assessment, the NHP service aims at being complementary to climate projections work carried out by many federal and state governments, universities, and other organisations across Australia. The projections comprise an ensemble of application-ready bias-corrected climate model data and derived hydrological projections at daily temporal and 0.05° × 0.05° spatial resolution for the period 1960–2099 and two emission scenarios (RCP 4.5 and RCP 8.5). The spatial resolution of the projections matches that of gridded historical reference data used to perform the bias correction and the Bureau's operational gridded hydrological model. Three bias correction techniques were applied to four CMIP5 global climate models (GCMs) and one to output from a regional climate model forced by the same four GCMs, resulting in a 16-member ensemble of bias-corrected GCM data for each emission scenario. The bias correction was applied to fields of precipitation, minimum and maximum temperature, downwelling shortwave radiation and surface winds. These variables are required inputs to the Bureau's landscape water balance hydrological model (AWRA-L) which was forced using the bias-corrected GCM and RCM data to produce a 16-member ensemble of hydrological output. The hydrological output variables include root-zone soil moisture (moisture in the top 1 m soil layer), potential evapotranspiration and runoff. Here we present an overview of the production of the hydrological projections, including GCM selection, bias correction methods and their evaluation, technical aspects of their implementation and ex les of analysis performed to construct the NHP service. The data are publicly available on the National Computing Infrastructure (0.25914/6130680dc5a51) and a user interface is accessible at awo.bom.gov.au roducts rojection/.
Comparing and Combining Remotely Sensed Land Surface Temperature Products for Improved Hydrological Applications
Publisher: MDPI AG
Date: 20-02-2016
DOI: 10.3390/RS8020162
Is Past Variability a Suitable Proxy for Future Change? A Virtual Catchment Experiment
Publisher: American Geophysical Union (AGU)
Date: 02-2020
DOI: 10.1029/2019WR026275
Abstract: To estimate the robustness of hydrologic models under projected future climate change, researchers test transferability between climatically contrasting observed periods. This approach can only assess the performance changes induced by altered precipitation and related environmental dynamics (e.g., greening under wet conditions), since the instrumental record does not contain temperatures or carbon dioxide levels that are similar to future climate change projections. Additionally, there is an inherent assumption that long‐term persistence of changes in precipitation will not further impact catchment response. In this study, we undertake a series of virtual catchment experiments using an ecohydrologic model that simulates dynamic vegetation growth, nutrient cycling, and subsurface hydrology. These experiments explore a number of climate change scenarios. We compare simulations based on persistent altered climate states against simulations designed to represent historical periods with the same precipitation but limited time for ecohydrologic adaptation. We find that persistence of precipitation changes as well as increased temperature and elevated carbon dioxide levels can all substantially impact streamflow under drier future conditions. For wetter future scenarios, simulated differences in the flow regime were smaller, but there was still notable ergence in modeled low flows and other hydrologic variables. The results suggest that historical periods with equivalent precipitation statistics cannot necessarily be used as proxies for future climate change when examining catchment runoff response and/or model performance. The current literature likely underestimates the potential for nonstationarity in hydrologic assessments, especially for drier future scenarios.
Quantifying the sources of uncertainty in upper air climate variables
Publisher: American Geophysical Union (AGU)
Date: 22-04-2016
DOI: 10.1002/2015JD024341
A wavelet-based tool to modulate variance in predictors: An application to predicting drought anomalies
Publisher: Elsevier BV
Date: 2021
Supplementary material to A systematic review of climate change science relevant to Australian design flood estimation
Publisher: Copernicus GmbH
Date: 10-10-2023
Deriving daily water levels from satellite altimetry and land surface temperature for sparsely gauged catchments: A case study for the Mekong River
Publisher: Elsevier BV
Date: 06-2018
Daily time series of river water levels derived from a seasonal linear model using multisource satellite products under uncertainty
Publisher: Elsevier BV
Date: 11-2021
Can Regional Climate Modeling Capture the Observed Changes in Spatial Organization of Extreme Storms at Higher Temperatures?
Publisher: American Geophysical Union (AGU)
Date: 12-05-2018
DOI: 10.1029/2018GL077716
A software toolkit for correcting systematic biases in climate model simulations
Publisher: Elsevier BV
Date: 06-2018
A New Method for Postprocessing Numerical Weather Predictions Using Quantile Mapping in the Frequency Domain
Publisher: American Meteorological Society
Date: 08-2023
Abstract: Improving lead time for forecasting floods is important to minimize property damage and ensure the safety of the public and emergency services during flood events. Numerical weather prediction (NWP) models are important components of flood forecasting systems and have been vital in extending forecasting lead time under complex weather and terrain conditions. However, NWP forecasts still have significant uncertainty associated with the precipitation fields that are the main inputs of the hydrologic models and thus the resulting flood forecasts. An issue often overlooked is the importance of correctly representing variability over a range of different temporal scales. To address this gap, here a new wavelet-based method for postprocessing NWP precipitation forecasts is proposed. First, precipitation forecasts are decomposed into the frequency domain using a wavelet transform, providing estimates of the litudes and phases of the time series at different frequencies. Quantile mapping is then used to correct bias in the litudes of each frequency. Randomized phases are used to generate an ensemble of realizations of the precipitation forecasts. The postprocessed precipitation forecasts are reconstructed by taking the inverse of adjusted time-frequency decompositions with the corrected litudes and randomized phases. The proposed method was used to postprocess NWP precipitation forecasts in the Sydney region of Australia. There is a significant improvement in postprocessed precipitation forecasts across multiple time scales in terms of bias and temporal and spatial correlation structures. The postprocessed precipitation fields can be used for the modeling of fully distributed hydrologic systems, improving runoff stimulation, flood depth estimation, and flood early warning. A new method accounting for the timing and spatial errors of NWP precipitation forecasts is proposed, and it can improve the skill of forecasts across multiple time scales, especially at short lead times. The proposed method provides a practical and effective way to correct these errors by incorporating spatiotemporal neighborhood information through the frequency domain using sophisticated wavelet transforms. With systematic timing and spatial errors removed, precipitation forecasts will be more skillful, and hydrological modeling using the postprocessed forecasts can provide higher accuracy of streamflow estimation.
Natural hazards in Australia: droughts
Publisher: Springer Science and Business Media LLC
Date: 19-09-2016
500-year reconstruction of Dez River discharge in southwestern Iran from tree rings
Publisher: Elsevier BV
Date: 09-2023
Revisiting Pan Evaporation Trends in Australia a Decade on
Publisher: American Geophysical Union (AGU)
Date: 27-10-2018
DOI: 10.1029/2018GL079332
Abstract: Decreases in pan evaporation ( E pan ) have been reported around the world despite increasing air temperatures this was attributed to reductions in wind speed and solar radiation. Using 42 years (1975–2016) of Australian E pan data, we reexamined E pan trends, adding over a decade of observations to previous analyses. Flexible local linear regression models showed that many previously reported decreasing E pan trends have plateaued or reversed. Attribution analysis confirmed that 1975–1994 E pan decreases in southern/western Australia were chiefly driven by decreasing wind speeds. Increasing vapor pressure deficit subsequently became dominant, resulting in 1994–2016 E pan increases. Climate trend analyses should consider applying flexible statistical models to qualitatively understand temporal dynamics, complementing linear models that are able to provide quantitative assessments, especially when multiple drivers are involved.
Exploring Pacific Island hydroclimatic extremes using the South Pacific Drought Atlas
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-10570
Abstract: Droughts are a natural occurrence in many small Pacific Islands and can have severe impacts on local populations and environments. The El Ni& #241 o-Southern Oscillation (ENSO) is a well-known driver of drought in the South Pacific, but our understanding of extreme ENSO events and their influence on island hydroclimate is limited by the short instrumental record and the infrequency of ENSO extremes. To address this gap, we present the South Pacific Drought Atlas (SPaDA), a multi-proxy, spatially resolved reconstruction of the November-April Standardised Precipitation Evapotranspiration Index for the southwest Pacific islands. The reconstruction integrates coral proxies, which provide local information on the South Pacific hydroclimate but are limited in number and length, with a network of continental tree-ring chronologies targeting Pacific climate variability through remote teleconnections. The reconstruction demonstrates the benefits of multi-proxy reconstructions incorporating tree rings, which allow for the alignment of other proxy records without chronological error.The SPaDA provides a 350-year, continuous dataset of climate information, which can be used to explore the occurrence of extreme events in the pre-instrumental period. The SPaDA closes the gap between existing paleo-reconstructions of point ENSO indices, and a spatially resolved drought atlas, allowing both the hydroclimate of in idual islands and regional patterns of drought to be assessed. The benefit of a spatially resolved dataset to assess climate extremes in small Pacific islands is highlighted in the case of extreme El Ni& #241 o events, which can have substantially different hydroclimatic impacts than more moderate events.We used an Isolation Forest, an unsupervised machine learning algorithm, to identify anomalous hydroclimatic states in the SPaDA that may indicate the occurrence of an extreme event. Extreme El Ni& #241 o events characterised by very strong southwest Pacific drought anomalies and a zonal South Pacific Convergence Zone orientation are shown to have occurred semi-regularly throughout the reconstruction interval, providing a valuable baseline to compare to climate model projections. By identifying the spatial patterns of drought resulting from extreme events, we can better understand the impacts these events may have on in idual Pacific Islands in the future.
Correcting bias in radar Z – R relationships due to uncertainty in point rain gauge networks
Publisher: Elsevier BV
Date: 11-2014
Related Organisations
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Related Funding Activities
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