ORCID Profile
0000-0001-7759-8344
Current Organisations
Centre for Genomic Regulation
,
University of Melbourne
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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.
Surfacewater Hydrology | Water Resources Engineering | Civil Engineering | Optimisation | Infrastructure Engineering and Asset Management | Environmental Management | Physical Geography and Environmental Geoscience | Environmental Engineering Modelling | Environmental Engineering | Freshwater Ecology
Water Allocation and Quantification | Ecosystem Adaptation to Climate Change | Ecosystem Assessment and Management of Fresh, Ground and Surface Water Environments | Effects of Climate Change and Variability on Australia (excl. Social Impacts) | Climate Variability (excl. Social Impacts) | Expanding Knowledge in Engineering | Urban Water Policy | Rural Water Policy |
Publisher: Copernicus GmbH
Date: 03-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-10
Abstract: & & Climate change is expected to change the pattern of rainfall resulting in changed flood magnitude. However, in large part due to interannual variability, identifying a climate change signal in flood magnitude remains difficult. As an alternative to investigating trends in flood magnitude, it has been suggested that trends in flood timing, that is, the day of annual streamflow maxima, may be a detectable trend due climate change.& & & & Here, using high-quality data from around the world, trends in flood and center timing are investigated. We begin by standardizing the data on a local definition of water year. We find an interesting property, that after standardization, the flood and centre timing of streamflow can be approximated by a normal distribution. Moreover, we find that without the standardization on local water year the calculated trend can reverse. We proceed by analyzing trends in centre and flood timing globally using linear regression.& & & & Results are commensurable with large-scale climatic change. But, unlike changes in extreme rainfall, trends are not spatially consistent. Flood timing is shifting to earlier in the year in the tropics, and later in the year in the extra-tropics, consistent with changes in mean rainfall and flood magnitude. There is evidence of a reversal of trends post-drought, suggesting that the mechanisms controlling flooding at a catchment scale are changing as a result of climate change. It is concluded that trends in flood timing are related to flood generating mechanisms, and largely modulated by changing antecedent moisture conditions.& &
Publisher: Copernicus GmbH
Date: 06-12-2022
DOI: 10.5194/HESS-26-6073-2022
Abstract: Abstract. The Millennium Drought lasted more than a decade and is notable for causing persistent shifts in the relationship between rainfall and runoff in many southeastern Australian catchments. Research to date has successfully characterised where and when shifts occurred and explored relationships with potential drivers, but a convincing physical explanation for observed changes in catchment behaviour is still lacking. Originating from a large multi-disciplinary workshop, this paper presents and evaluates a range of hypothesised process explanations of flow response to the Millennium Drought. The hypotheses consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. The hypotheses are assessed against evidence both temporally (e.g. why was the Millennium Drought different to previous droughts?) and spatially (e.g. why did rainfall–runoff relationships shift in some catchments but not in others?). Thus, the strength of this work is a large-scale assessment of hydrologic changes and potential drivers. Of 24 hypotheses, 3 are considered plausible, 10 are considered inconsistent with evidence, and 11 are in a category in between, whereby they are plausible yet with reservations (e.g. applicable in some catchments but not others). The results point to the unprecedented length of the drought as the primary climatic driver, paired with interrelated groundwater processes, including declines in groundwater storage, altered recharge associated with vadose zone expansion, and reduced connection between subsurface and surface water processes. Other causes include increased evaporative demand and harvesting of runoff by small private dams. Finally, we discuss the need for long-term field monitoring, particularly targeting internal catchment processes and subsurface dynamics. We recommend continued investment in the understanding of hydrological shifts, particularly given their relevance to water planning under climate variability and change.
Publisher: Springer Science and Business Media LLC
Date: 1992
DOI: 10.1007/BF00872205
Publisher: Copernicus GmbH
Date: 19-02-2019
Abstract: Abstract. An accurate representation of spatio-temporal characteristics of precipitation fields is fundamental for many hydro-meteorological analyses but is often limited by the paucity of gauges. Reanalysis models provide systematic methods of representing atmospheric processes to produce datasets of spatio-temporal precipitation estimates. The precipitation from the reanalysis datasets should, however, be evaluated thoroughly before use because it is inferred from physical parameterization. In this paper, we evaluated the precipitation dataset from the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) and compared it against (a) gauged point observations, (b) an interpolated gridded dataset based on gauged point observations (AWAP), and (c) a global reanalysis dataset (ERA-Interim). We utilized a range of evaluation metrics such as continuous metrics (correlation, bias, variability, modified Kling-Gupta efficiency), categorical metrics, and other statistics (wet day frequency, transition probabilities and quantiles) to ascertain the quality of the dataset. BARRA, in comparison with ERA-Interim, shows a better representation of rainfall of larger magnitude at both point and grid scale of 5 km. BARRA also consistently reproduces the distribution of wet days and transition probabilities. The performance of BARRA varies spatially, with better performance in the temperate zone than in the arid and tropical zones. A point-to-grid evaluation based on correlation, bias and modified Kling-Gupta efficiency (KGE') indicates that ERA-Interim performs on par or better than BARRA. However, on a spatial scale, BARRA outperforms AWAP in terms of KGE' score and the components of the KGE' score. Our evaluation illustrates that BARRA, with richer spatial variations in climatology of daily precipitation, provides an improved representation of precipitation compared with the coarser ERA-Interim. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
Publisher: Cambridge University Press
Date: 17-02-2011
Publisher: Wiley
Date: 26-10-2023
DOI: 10.1002/IEAM.4849
Publisher: Copernicus GmbH
Date: 10-10-2023
Publisher: American Geophysical Union (AGU)
Date: 25-02-2020
DOI: 10.1029/2019WR026300
Publisher: Informa UK Limited
Date: 03-07-2021
Publisher: Elsevier BV
Date: 04-2023
Publisher: Springer Science and Business Media LLC
Date: 19-07-2019
Publisher: Elsevier BV
Date: 10-2017
Publisher: Informa UK Limited
Date: 02-2006
DOI: 10.1080/07391102.2006.10507070
Abstract: Analysis, storage, and transfer of molecular dynamic trajectories are becoming the bottleneck of computer simulations. In this paper we discuss different approaches for data mining and data processing of huge trajectory files generated from molecular dynamic simulations of nucleic acids.
Publisher: Copernicus GmbH
Date: 20-04-2022
Abstract: Abstract. The Millennium Drought lasted more than a decade, and is notable for causing persistent shifts in the relationship between rainfall and runoff in many south-east Australian catchments. Research to date has successfully characterised where and when shifts occurred and explored relationships with potential drivers, but a convincing physical explanation for observed changes in catchment behaviour is still lacking. Originating from a large multi-disciplinary workshop, this paper presents a range of possible process explanations of flow response, and then evaluates these hypotheses against available evidence. The hypotheses consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. The hypotheses are assessed against evidence both temporally (eg. why was the Millennium Drought different to previous droughts?) and spatially (eg. why did rainfall-runoff relationships shift in some catchments but not in others?). The results point to the unprecedented length of the drought as the primary climatic driver, paired with interrelated groundwater processes, including: declines in groundwater storage, reduced recharge associated with vadose zone expansion, and reduced connection between subsurface and surface water processes. Other causes include increased evaporative demand and interception of runoff by small private dams. Finally, we discuss the need for long-term field monitoring, particularly targeting internal catchment processes and subsurface dynamics. We recommend continued investment in understanding of hydrological shifts, particularly given their relevance to water planning under climate variability and change.
Publisher: Elsevier BV
Date: 05-2002
Publisher: Informa UK Limited
Date: 02-01-2017
Publisher: Elsevier BV
Date: 12-1990
Publisher: American Geophysical Union (AGU)
Date: 09-1990
Publisher: Wiley
Date: 2001
DOI: 10.1002/ENV.486
Publisher: Informa UK Limited
Date: 02-01-2018
Publisher: IOP Publishing
Date: 08-2019
Abstract: Human-induced climate change poses a major threat to the reliable water supply in many highly populated regions. Here we combine hydrological and climate model simulations to evaluate risks to the water supply under projected shifts in the climate at the Paris Agreement warming levels. Modelling the primary surface water sources for Melbourne, Australia, we project that the risk of severe water supply shortage to the climate-dependent portion of the system increases substantially as global warming increases from 1.5 °C to 2.0 °C. Risks are further exacerbated by increases in water demand but substantially ameliorated by supply augmentation from desalination. We demonstrate that reductions in precipitation, rising temperature and growth in water demand combine to substantially lify the risk of severe water supply shortage under near-term global warming in the absence of a climate-independent supply. This risk lification is not as apparent in assessments based on meteorological drought alone. With the diminishing opportunity of meeting the 1.5 °C Paris target, our study highlights the need to accelerate greenhouse gas mitigation efforts to reduce risks to climate dependent water supply systems.
Publisher: American Society of Civil Engineers (ASCE)
Date: 12-2018
Publisher: American Geophysical Union (AGU)
Date: 07-1990
Publisher: American Geophysical Union (AGU)
Date: 07-1991
DOI: 10.1029/91WR01006
Publisher: American Geophysical Union (AGU)
Date: 02-2022
DOI: 10.1029/2021EF002473
Abstract: The relationship between extreme precipitation ( EP ) and precipitable water ( W ) is useful to assess design extremes and speculate on their expected changes with rising global temperatures. This study investigates the relationship between daily and longer‐duration EP and corresponding W at a global scale by analyzing remote‐sensed and reanalysis data sets from 2003 to 2019. An assessment of the consistency in the temporal trend across various W data sets reveals a consistent statistically significant upward trend during the period. This upward trend, while predominant worldwide, is especially significant over tropical land regions. W is found to generally be positively correlated with surface (dew point) temperature, suggesting a rise in temperature will cause a greater W over time. To assess whether EP s occur coincident with extreme W , the Concurrent Extremes Index (CEI) is proposed, which compares the cumulative distribution functions between the two variables and assumes a value of unity if ranks of the EP series are identical to that of the coincident W series, and zero with no correspondence. For EP (defined as the five largest 1‐day events per year on average), a high CEI is pronounced across the tropics, except for rainforests. The W ‐ EP relationship is noticeably weakened in nontropics, except the inland regions of North America and East Asia. An assessment indicates that as the duration of the EP becomes longer, the influence of W on EP decreases. However, the contrast in the W ‐ EP relationship between the tropics and nontropics is found to become more pronounced as longer‐duration EP s are considered.
Publisher: American Geophysical Union (AGU)
Date: 12-2022
DOI: 10.1029/2022WR033214
Abstract: Flood inundation emulation models based on deep neural networks have been developed to overcome the computational burden of two‐dimensional (2D) hydrodynamic models. Challenges remain for flat and complex floodplains where many anabranches form during flood events. In this study, we propose a new approach to simulate the temporal and spatial variation of flood inundation for a floodplain with complex flow paths. A U‐Net‐based spatial reduction and reconstruction method (USRR) is used to find representative locations on the floodplain with complex flow paths. The water depths at these locations are simulated using one‐dimensional convolutional neural network (1D‐CNN) models, which are well‐suited to handling multivariate timeseries inputs. The flood surface is then reconstructed using the USRR method and the simulated flood depths at the representative locations. The combined 1D‐CNN and USRR method is compared with a previously developed approach based on the long short‐term memory recurrent neural network (LSTM) models and a 2D linear interpolation‐based SRR method. Compared to the LSTM model, the 1D‐CNN model is not only more accurate, but also takes less time to develop. Although both surface reconstruction methods take s to produce an inundation map for a specific point in time, the USRR method is more accurate than the SRR method, leading to an increase of 5.6% in the proportion of correctly detected inundation area. The combination of 1D‐CNN and USRR can detect over 95% of the inundated area simulated using a 2D hydrodynamic model but is 98 times faster.
Publisher: Copernicus GmbH
Date: 28-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-12742
Abstract: & & Australia's Millennium Drought (1997-2010) was a multi-year event notable for causing persistent shifts in the relationship between rainfall and runoff in many catchments.& Here, we describe a multi-disciplinary eWorkshop held in late 2020 to discuss the hydrology of the Millennium Drought and explore the hydrological processes leading to the hydrological shifts.& Research to date has successfully characterised where and when shifts occurred, explored which catchment attributes are statistically related to the shifts, and noted changes in rainfall partitioning. & However, a physical explanation for the changes in catchment behaviour is still lacking, hence the need for this workshop. & & & & & Integrating perspectives from hydrogeology, ecohydrology, remote sensing, hydroclimatology, experimental hydrology and hydrological modelling, the workshop aimed to share and discuss & #8220 erceptual models& #8221 of flow response that could explain the Millennium Drought streamflow observations, considering both the spatial and temporal patterns of hydrological shifts. We considered a range of perceptual models of flow response, and then evaluated the models against available evidence. The models consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. Perceptual models were assessed both temporally (e.g. why was the Millennium Drought different to previous droughts?) and spatially (e.g. why did rainfall-runoff relationships shift in some catchments but not in others?).& & & & & The results point to the unprecedented length of the drought (10+ years) as the primary climatic driver, paired with interrelated groundwater processes: declines in groundwater storage, reduced recharge associated with vadose zone expansion/drying, and reduced connection between subsurface and surface water processes. & An additional contributor is increased evaporative demand, and minor contributors may include farm dams, salinity recovery, and drainage via regional groundwater systems. & The roles of deep-rooted vegetation, wildfire, rainfall patterns, and land use change, among others, were discounted on various grounds. & & & & & There is a need to confirm these landscape-scale evaluations with local long-term field monitoring, particularly of subsurface dynamics, faced with a lack of such monitoring during the drought itself. & A decline in monitoring meant that many variables went unmeasured that could have aided diagnosis. & Thus, the drought provides an ex le to other countries of the value of continued investment, particularly to build up and retain multi-decadal records in as many sites and variables as possible. & We strongly recommend investment in understanding of hydrological shifts through such monitoring, which is particularly important given the relevance of hydrological shifts to water planning under climate variability and change.& & &
Publisher: American Geophysical Union (AGU)
Date: 11-2022
DOI: 10.1029/2022WR032247
Abstract: The safety of high‐risk water infrastructure, such as dams and nuclear power plants, is often assessed by reference to their ability to accommodate floods derived from the Probable Maximum Precipitation (PMP). However, a key shortcoming of traditional PMP estimates is the assumption of a stationary climate, with evidence indicating that key meteorological conditions related to the magnitudes of extreme storms, such as atmospheric moisture, are changing in a warming climate. Due to the pragmatic nature of PMP methods derived for design purposes, inferring potential changes in PMP estimates based solely on trends or projections of atmospheric variables can ignore PMP method complexities and constraints. Here we explore how different traditional PMP methods will respond to a potential increase in atmospheric moisture. We find that increases in persisting dewpoint will lead to increases in PMP estimates, and the nature of this impact depends on whether the moisture maximization step is based on local or transposed regional information. An historical trend analysis reveals annual maximum persisting dewpoint temperatures have increased continuously over Australia over the past 60 years, with further increases predicted over the coming decades for all Shared Socioeconomic Pathways (SSPs). PMP estimates across Australia are predicated to increase by an average value of 13% by 2100 based on the conservative SSP1‐2.6, compared to 33% for SSP5‐8.5. We conclude PMP methods will require regular updating to account for changing persisting dewpoints and likely progressive increases in PMP, and the ensuing flood estimates.
Publisher: American Geophysical Union (AGU)
Date: 08-2022
DOI: 10.1029/2022WR032248
Abstract: Accurate flood inundation modeling using a complex high‐resolution hydrodynamic (high‐fidelity) model can be very computationally demanding. To address this issue, efficient approximation methods (surrogate models) have been developed. Despite recent developments, there remain significant challenges in using surrogate methods for modeling the dynamical behavior of flood inundation in an efficient manner. Most methods focus on estimating the maximum flood extent due to the high spatial‐temporal dimensionality of the data. This study presents a hybrid surrogate model, consisting of a low‐resolution hydrodynamic (low‐fidelity) and a Sparse Gaussian Process (Sparse GP) model, to capture the dynamic evolution of the flood extent. The low‐fidelity model is computationally efficient but has reduced accuracy compared to a high‐fidelity model. To account for the reduced accuracy, a Sparse GP model is used to correct the low‐fidelity modeling results. To address the challenges posed by the high dimensionality of the data from the low‐ and high‐fidelity models, Empirical Orthogonal Functions analysis is applied to reduce the spatial‐temporal data into a few key features. This enables training of the Sparse GP model to predict high‐fidelity flood data from low‐fidelity flood data, so that the hybrid surrogate model can accurately simulate the dynamic flood extent without using a high‐fidelity model. The hybrid surrogate model is validated on the flat and complex Chowilla floodplain in Australia. The hybrid model was found to improve the results significantly compared to just using the low‐fidelity model and incurred only 39% of the computational cost of a high‐fidelity model.
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 2021
Publisher: American Geophysical Union (AGU)
Date: 10-09-2020
DOI: 10.1029/2020GL089723
Abstract: Extreme precipitation events are intensifying with increasing temperatures. However, observed extreme precipitation‐temperature sensitivities have been found to vary significantly across the globe. Here we show that negative sensitivities found in previous studies are the result of limited consideration of within‐day temperature variations due to precipitation. We find that short‐duration extreme precipitation can be better described by subdaily atmospheric conditions before the start of storm events, resulting in positive sensitivities with increased consistency with the Clausius‐Clapeyron relation across a wide range of climatic regions. Contrary to previous studies that advocate that dew point temperature drives precipitation, dry‐bulb temperature is found to be a sufficient descriptor of precipitation variability. We argue that analysis methods for estimating extreme precipitation‐temperature sensitivities should account for the strong and prolonged cooling effect of intense precipitation, as well as for the intermittent nature of precipitation.
Publisher: Elsevier BV
Date: 10-2023
Publisher: American Geophysical Union (AGU)
Date: 08-2022
DOI: 10.1029/2021WR031210
Abstract: Recent shifts in the hydrological behavior of natural watersheds suggest acute challenges for water planning under climate change. Usually triggered by a multi‐year drought, these shifts involve a tendency for less annual streamflow for a given annual precipitation, and this behavior has now been reported on multiple continents. Future drying under climate change may induce similar unexpected hydrological responses, and this commentary discusses the implications for water planning and management. Commonly used hydrological models poorly represent these shifts in behavior and cannot be relied upon to anticipate future changes. Thus, their use may result in underestimation of hydroclimatic risk and exposure to “surprise” reductions in water supply, relative to projections. The onus is now on hydrologists to determine the underlying causes of shifting behavior and incorporate more dynamic realism into operational models.
Publisher: American Geophysical Union (AGU)
Date: 04-2023
DOI: 10.1029/2021WR031854
Abstract: Accurate estimation of annual exceedance probabilities (AEPs) of extreme rainfalls through rainfall frequency analysis is a critical step in engineering design for flood mitigation and disaster response. Here we show how the estimation of rainfall frequency curves can be improved by fitting a four‐parameter Kappa distribution to a peaks‐over‐threshold (POT) series. To fit the Kappa distribution to POT data we present a two‐step fitting approach based on maximum likelihood estimation which separately models storm intensity and the arrival frequency. First, a Generalized Pareto distribution (GPA) describing storm intensity is fitted, followed by a Binomial distribution for storm arrivals. We compare the performance of this two‐step Kappa approach to an analogous two‐step Generalized Extreme Value (GEV) approach and to Kappa and GEV distributions fitted to annual maxima series (AMS), using both synthetic and real‐world data representative of Australian climatic conditions. The experiments show that leveraging additional information from the POT series in the two‐step Kappa approach dramatically improves quantile estimation and reduces uncertainty compared to fitting either the GEV or the Kappa distributions to AMS, particularly for rare quantiles. When skew–kurtosis properties of extreme rainfalls are well represented by the Kappa but not the GEV, the two‐step Kappa approach yields unbiased quantiles under extrapolation, while the use of GEV can lead to highly biased estimates. From these results, we believe the two‐step Kappa approach is suitable for both at‐site and regional rainfall frequency analyses as it can accommodate distributions ranging from GPA to GEV without encountering over‐fitting problems generally associated with four‐parameter distributions.
Publisher: Elsevier BV
Date: 11-2007
Publisher: Proceedings of the National Academy of Sciences
Date: 16-01-2007
Abstract: The dynamics of proteins in aqueous solution has been investigated through a massive approach based on “state of the art” molecular dynamics simulations performed for all protein metafolds using the four most popular force fields (OPLS, CHARMM, AMBER, and GROMOS). A detailed analysis of the massive database of trajectories ( .5 terabytes of data obtained using ≈50 years of CPU) allowed us to obtain a robust-consensus picture of protein dynamics in aqueous solution.
Publisher: Elsevier BV
Date: 11-2021
Publisher: Copernicus GmbH
Date: 22-09-2022
DOI: 10.5194/IAHS2022-72
Abstract: & & Small shifts in the climate can have large consequences on flood timing and magnitude. For ex le, changes of only 1-2 degrees Celsius and 10& #8211 % in annual precipitation can cause order of magnitude changes in flooding. Changes in flood magnitude and timing can affect flood risk, farming productivity, the health of ecological systems, and impact water supply reliability.& & & & Here we examine changes in both flood magnitude and timing across the world with a focus on Mediterranean and semi-arid climates, such as those in south-west Australia, which are dominated by dry summers and wet winters. Relative to other climates across the world, we find semi-arid regions are particularly susceptible to drying antecedent moisture conditions, with the largest decrease in antecedent soil moisture of any climate zone across the world.& & & & & Drying antecedent soil moisture conditions in semi-arid regions are causing a shift to a later onset of flooding in the wet season. Despite increases in extreme rainfall magnitudes, frequent floods, such as those expected to occur on average once per year, are decreasing in magnitude due to the impact of drying antecedent moisture conditions more than offsetting the impact of increasing extreme rainfall. Only rarer events, such as those expected to occur once every 10 years, are increasing in response to increases in extreme rainfalls, where the increase in extreme rainfall outweighs the decrease in soil moisture. These results point to smaller floods, such as responsible for filling our water supplies, decreasing, while the larger flood events that pose a risk to life and infrastructure are increasing, with semi-arid regions particularly susceptible to these changes.& &
Publisher: American Meteorological Society
Date: 15-09-2023
Abstract: It is well known that as a consequence of climate change, higher temperatures are causing extreme precipitation events to intensify, leading to greater flooding. However, the relationship between temperature and the temporal distribution of precipitation within storms is not well understood, with limited research focus on precipitation event loading or where the bulk of the precipitation occurs within the storm duration. Here, we investigate the relationship between temperature and the temporal pattern of precipitation, with a focus on event loading. Historical trend analyses based on station observations reveal that precipitation events have become increasingly front loaded (i.e., a greater percentage of precipitation falling earlier in the storm) across Australia over the past six decades. This increased frontal loading of precipitation events coincides with increasing trends in representative storm temperatures, with higher temperatures associated with a greater proportion of short-duration convective events. Linking these precipitation events with the representative storm temperatures shows that precipitation events become more front loaded with increasing temperature across nearly all event durations and intensities, with the emphasis on shorter duration ( h) events in the tropics. There is a clear systematic shift toward more front-loaded temporal patterns of precipitation with increasing temperature, coupled with intensification of embedded bursts. These results have implications for potentially increased flooding, with hydrological applications needing to account for nonstationarity in the temporal pattern of precipitation. To date, there is very little understanding of how temporal patterns of precipitation events change with increasing temperatures. Here, we investigate the relationship between temperature and the temporal pattern of precipitation events with a focus on the timing of when the bulk of precipitation occurs (termed event loading ). Our results indicate a clear systematic shift toward more front-loaded temporal patterns of precipitation with increasing temperature, coupled with intensification of embedded bursts. Greater shifts in temporal patterns of precipitation are observed for shorter-duration precipitation events, particularly in the tropics. The impact of changing temporal patterns of precipitation on flood estimation will require careful examination due to the risk of increased flood peaks.
Publisher: Elsevier BV
Date: 02-2017
Publisher: Copernicus GmbH
Date: 04-06-2020
DOI: 10.5194/HESS-24-2951-2020
Abstract: Abstract. The high spatio-temporal variability of precipitation is often difficult to characterise due to limited measurements. The available low-resolution global reanalysis datasets inadequately represent the spatio-temporal variability of precipitation relevant to catchment hydrology. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) provides a high-resolution atmospheric reanalysis dataset across the Australasian region. For hydrometeorological applications, however, it is essential to properly evaluate the sub-daily precipitation from this reanalysis. In this regard, this paper evaluates the sub-daily precipitation from BARRA for a period of 6 years (2010–2015) over Australia against point observations and blended radar products. We utilise a range of existing and bespoke metrics for evaluation at point and spatial scales. We examine bias in quantile estimates and spatial displacement of sub-daily rainfall at a point scale. At a spatial scale, we use the fractions skill score as a spatial evaluation metric. The results show that the performance of BARRA precipitation depends on spatial location, with poorer performance in tropical relative to temperate regions. A possible spatial displacement during large rainfall is also found at point locations. This displacement, evaluated by comparing the distribution of rainfall within a day, could be quantified by considering the neighbourhood grids. On spatial evaluation, hourly precipitation from BARRA is found to be skilful at a spatial scale of less than 100 km (150 km) for a threshold of 75th percentile (90th percentile) at most of the locations. The performance across all the metrics improves significantly at time resolutions higher than 3 h. Our evaluations illustrate that the BARRA precipitation, despite discernible spatial displacements, serves as a useful dataset for Australia, especially at sub-daily resolutions. Users of BARRA are recommended to properly account for possible spatio-temporal displacement errors, especially for applications where the spatial and temporal characteristics of rainfall are deemed very important.
Publisher: Elsevier BV
Date: 12-2016
Publisher: IOP Publishing
Date: 07-09-2020
Publisher: American Geophysical Union (AGU)
Date: 02-2022
DOI: 10.1029/2021WR030192
Abstract: Climate change is projected to impact multiple components of the flow regime. However, changes in some ecologically important aspects of flow seasonality and variability are not well‐represented by global climate models. We used a stress testing method and global sensitivity analysis to investigate whether interactions between five different, but plausible, change “dimensions” (hydroclimatic variables or relationships) led to worse ecological outcomes than in idual changes. The five dimensions include changes in long‐term average rainfall and temperature, low‐frequency variability of rainfall, seasonality of rainfall, and the rainfall‐runoff relationship. Our case study involved regulated and unregulated sections of the Goulburn River, Australia. We found that four different modeled ecological outcomes (condition of small bodied fish, large bodied fish, in‐channel vegetation, and floodplain vegetation) are most sensitive to changes in long‐term average rainfall. Sensitivity to changes in rainfall seasonality depends on river characteristics and appears to be heavily d ened by regulation and actively managed environmental water. Changes to the rainfall‐runoff relationship (which may be triggered by long‐term drying) were found to greatly influence ecological outcomes, but remain poorly understood. However, when considering the worst outcomes that are likely to present severe threats to ecological survival, all five dimensions were significant. These worst outcomes only manifest under certain combinations of changes with interactive effects. These joint interactions have implications for climate risk assessments that do not consider multiple dimensions of change, particularly those aimed at evaluating and mitigating severe threats or extinction probability.
Publisher: Elsevier BV
Date: 07-2021
Publisher: American Geophysical Union (AGU)
Date: 04-2001
DOI: 10.1029/2000WR900269
Publisher: American Geophysical Union (AGU)
Date: 31-07-2020
DOI: 10.1029/2020WR027233
Abstract: Analysis of flood and streamflow timing has recently gained prominence as a tool for attribution of climatic changes to flooding. Such studies generally apply circular statistics to the day of maximum flow in a calendar year and use nonparametric linear trend tests to investigate changes in flooding on a local or regional scale. Here we investigate both the center timing of streamflow and the day of maximum flow using a local water year. For each station, the start of the water year is defined as the month of lowest average monthly streamflow. This definition of water year prevents ambiguity in the direction of computed trends and enables flood and streamflow timing to be described by a normal distribution. Using the assumption of normality, we calculate the historical trend in both flood and streamflow timing using linear regression. While shifts in flood and streamflow timing are consistent with climate change and are shifting in a similar direction, shifts in the timing of the annual maxima flood are approximately three times that of streamflow timing. The results here have implications for water resources and environmental management where streamflow and flood timing are critical to planning. The applicability of the normal approximation to flood and streamflow timing will enable future analyses to use parametric statistics.
Publisher: Wiley
Date: 08-05-2021
DOI: 10.1002/WAT2.1527
Abstract: There is an extensive literature dealing with the interaction between groundwater and surface water, and this includes major reviews on baseflow, transmission losses, baseflow recession analysis, and broader aspects of low flows. Although these are mature topics in hydrology, they continue to attract strong interest, with hundreds of papers published in leading journals over the past 20 years. Our comprehensive review of the relevant literature focusses in detail on the use of linear and nonlinear models of recession discharge, and on transmission loss. From this review we identify three approaches to understanding recession, namely (a) theoretical approaches based on the Boussinesq equation, (b) applications of recession slope analysis, and (c) estimates of transmission loss by input–output water balance. We review the application of these techniques to ephemeral and humid areas and note the wide adoption of linear models despite most researchers accepting that the processes are nonlinear. Few papers address the characteristics of groundwater flow to ephemeral streams from unconfined aquifers. Although initially considered an ephemeral arid/semi‐arid stream feature, transmission loss occurs in streams in humid areas. Interestingly, we identify a significant omission in the literature, in that while it is common to observe nonlinear behavior in streamflow recessions, little explicit account has been given to the role of transmission loss which can be an important factor in identifying the structure of nonlinear recession models. This article is categorized under: Science of Water Hydrological Processes
Publisher: Elsevier BV
Date: 02-2021
Publisher: CSIRO Publishing
Date: 2001
DOI: 10.1071/MF00018
Abstract: This paper summarizes the results from a study of historical stream salinity trends and catchment salt balances within the Murray–Darling Basin, Australia. A broad analysis of stream salinization was necessary to assist prediction of the increase in the effect and extent of dryland salinity across the basin. The sparseness of the water-quality data necessitated the development of an innovative statistical trend technique that also allowed for the high autocorrelation of the stream salinity data which was often present.Results showed the spatial distribution of stream salinization and identified regions of concern. The salinization characteristics of four distinct geographical regions were identified by providing a spatial analysis of catchment salt balances and stream salinity trends. The salinization behaviour of each region was also related to distinct physical processes. The most significant rising trends and catchment salt output/input ratios were in the zone with 500–800 mm year–1 rainfall in the southern and eastern dryland region.
Publisher: Copernicus GmbH
Date: 03-09-2019
Abstract: Abstract. The high spatio-temporal variability of precipitation is often difficult to characterise due to limited measurements. The available low-resolution global reanalysis datasets inadequately represent the spatio-temporal variability of precipitation relevant to catchment hydrology. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) provides a high-resolution atmospheric reanalysis dataset across the Australasian region. For hydrometeorological applications, however, it is essential to properly evaluate the sub-daily precipitation from this reanalysis. In this regard, this paper evaluates the sub-daily precipitation from BARRA for a period of 6 years (2010–2015) over Australia against point observations and blended radar products. We utilise a range of existing and bespoke metrics for evaluation at point and spatial scales. We examine bias in quantile estimates and spatial displacement of sub-daily rainfall at a point scale. At a spatial scale, we use the Fractions Skill Score as a spatial evaluation metric. The results show that the performance of BARRA precipitation depends on spatial location with poorer performance in tropical relative to temperate regions. A possible spatial displacement during large rainfall is also found at point locations. This displacement, evaluated by comparing the distribution of rainfall within a day, could be quantified by considering the neighbourhood grids. On spatial evaluation, hourly precipitation from BARRA are found to be skilful at a spatial scale of less than 100 km (150 km) for a threshold of 75 % quantile (90 % quantile) at most of the locations. The performance across all the metrics improves significantly at time resolutions higher than 3 h. Our evaluations illustrate that the BARRA precipitation, despite discernible spatial displacements, serves as a useful dataset for Australia, especially at sub-daily resolutions. Users of BARRA are recommended to properly account for possible spatio-temporal displacement errors, especially for applications where the spatial and temporal characteristics of rainfall are deemed very important.
Publisher: Elsevier BV
Date: 08-2019
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-1224
Abstract: Increases in extreme rainfall intensities as a result of climate change pose a great risk due to the possible increases in pluvial flooding. But evidence is emerging that the observed increases in extreme rainfall are not resulting in universal increases in flooding. Here, we begin by presenting historical evidence for changes in extreme rainfalls and floods discussing the underlying mechanisms for the changes, before examining the implications of climate change projections on engineering design.Extreme rainfall is intensifying universally across the globe with more extreme events experiencing larger degrees of intensification. Simultaneously, and somewhat paradoxically, the magnitude of frequent floods (those expected to occur on average once per year) are in general decreasing, particularly in the tropical and arid regions of the world. We suggest this is likely due to the dominance of drying antecedent soil moisture conditions and shorter storm durations at higher temperatures offsetting any increases in rainfall intensity. However, for rare magnitude floods (those expected, on average, to occur less than once every twenty years) the increase in rainfall appears to outweigh any decrease in soil moisture or change in the temporal pattern of the storm.Climate model projections, downscaled through a continental scale water balance model and locally calibrated rainfall-runoff models, show that future projections of flood responses follow historical trends & #8211 with the rarer the flood, the more likely it is to be increasing. To deepen our understanding, we focus our analysis on event runoff coefficients as an indicator of future runoff changes. Across Australia we find runoff coefficients are projected to decrease, that is, reduced runoff resulting from the same amount of rainfall. These results indicate drier conditions and a compounding of the reduced average rainfall and drier conditions already being experiences in many arid parts of the world.With these historical changes and projections in mind we conclude with some insights and implications on how best to incorporate the additional uncertainty due to climate change when estimating floods for planning and design purposes. As floods constitute a large portion of the inflows into reservoirs, we suggest that future water resources planning will need to account for reduced runoff yields. To assess the potential impacts of future climate change for planning and design purposes we need to consider how changes to rainfall intensity vary with both storm duration and storm rarity, as well as how antecedent conditions influence the proportion of rainfall that appears as runoff. There remains significant work in adapting our current flood guidance to reflect these historical and projected changes.
Publisher: Copernicus GmbH
Date: 10-10-2023
Publisher: Elsevier BV
Date: 10-1996
Publisher: Wiley
Date: 17-07-2022
Publisher: Wiley
Date: 11-04-2022
Publisher: American Geophysical Union (AGU)
Date: 06-2023
DOI: 10.1029/2022WR033836
Abstract: High computational cost is often the most limiting factor when running high‐resolution hydrodynamic models to simulate spatial‐temporal flood inundation behavior. To address this issue, a recent study introduced the hybrid Low‐fidelity, Spatial analysis, and Gaussian Process learning (LSG) model. The LSG model simulates the dynamic behavior of flood inundation extent by upskilling simulations from a low‐resolution hydrodynamic model through Empirical Orthogonal Function (EOF) analysis and Sparse Gaussian Process learning. However, information on flood extent alone is often not sufficient to provide accurate flood risk assessments. In addition, the LSG model has only been tested on hydrodynamic models with structured grids, while modern hydrodynamic models tend to use unstructured grids. This study therefore further develops the LSG model to simulate water depth as well as flood extent and demonstrates its efficacy as a surrogate for a high‐resolution hydrodynamic model with an unstructured grid. The further developed LSG model is evaluated on the flat and complex Chowilla floodplain of the Murray River in Australia and accurately predicts both depth and extent of the flood inundation, while being 12 times more computationally efficient than a high‐resolution hydrodynamic model. In addition, it has been found that weighting before the EOF analysis can compensate for the varying grid cell sizes in an unstructured grid and the inundation extent should be predicted from an extent‐based LSG model rather than deriving it from water depth predictions.
Publisher: Elsevier BV
Date: 09-2009
Publisher: Springer Science and Business Media LLC
Date: 11-09-2023
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-10210
Abstract: Can total annual streamflow in any given year be largely characterised by a relatively small number of high flow events? A comprehensive assessment of this is of high value as there is evidence to suggest that as flood events increase in rarity a more consistent response between streamflow extremes and temperature increases can be established & #8212 providing greater reliability in projections of rare events. We propose here a novel methodology to characterise streamflow regimes in the context of total annual streamflow for water supply. Using the Australian Bureau of Meteorology& #8217 s Hydrologic Reference Station database, we developed annual event flow distributions that standardise the relationship between total annual streamflow and event flows. It was found that the annual event flow distributions are primarily a function of local climate and catchment size and were largely insensitive to interannual variability represented by the El Nino Southern Oscillation Index, mean annual temperature, or total annual rainfall volume. Statistically significant trends were found in the timeseries of annual event flow distribution values, signalling a move to a less even distribution in the southern latitudes and a more even distribution in the northern latitudes. Our results show that total annual streamflows can be characterised by a small number of high flow events. This suggests that for Australia& #8217 s most critical surface drinking water supply catchments the streamflow yields can be represented by changes in a few, high flow events, independent of interannual variability. As these relationships are non-stationary, they may provide a basis for understanding changes in water supply into the future.
Publisher: Copernicus GmbH
Date: 19-08-2019
DOI: 10.5194/HESS-23-3387-2019
Abstract: Abstract. An accurate representation of spatio-temporal characteristics of precipitation fields is fundamental for many hydro-meteorological analyses but is often limited by the paucity of gauges. Reanalysis models provide systematic methods of representing atmospheric processes to produce datasets of spatio-temporal precipitation estimates. The precipitation from the reanalysis datasets should, however, be evaluated thoroughly before use because it is inferred from physical parameterization. In this paper, we evaluated the precipitation dataset from the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) and compared it against (a) gauged point observations, (b) an interpolated gridded dataset based on gauged point observations (AWAP – Australian Water Availability Project), and (c) a global reanalysis dataset (ERA-Interim). We utilized a range of evaluation metrics such as continuous metrics (correlation, bias, variability, and modified Kling–Gupta efficiency), categorical metrics, and other statistics (wet-day frequency, transition probabilities, and quantiles) to ascertain the quality of the dataset. BARRA, in comparison with ERA-Interim, shows a better representation of rainfall of larger magnitude at both the point and grid scale of 5 km. BARRA also more closely reproduces the distribution of wet days and transition probabilities. The performance of BARRA varies spatially, with better performance in the temperate zone than in the arid and tropical zones. A point-to-grid evaluation based on correlation, bias, and modified Kling–Gupta efficiency (KGE′) indicates that ERA-Interim performs on par or better than BARRA. However, on a spatial scale, BARRA outperforms ERA-Interim in terms of the KGE′ score and the components of the KGE′ score. Our evaluation illustrates that BARRA, with richer spatial variations in climatology of daily precipitation, provides an improved representation of precipitation compared with the coarser ERA-Interim. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
Publisher: Copernicus GmbH
Date: 25-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-128
Abstract: & & Changes in flooding have substantial economic consequences. Increases in flooding increase economic losses while decreases in flooding increase water scarcity. Greater extreme rainfalls due to climate change are expected to cause greater flood magnitudes. This is particularly true for urban and developed catchments where there is a lack of impervious surfaces and surface water storage. However, in rural and undeveloped catchments historical trends are mixed, with many catchments experiencing decreases in flood magnitude.& & & & Here we argue the observed increase in flood variability is due to (1) changes in the extreme rainfall patterns and antecedent soil moisture conditions that drive flood response, and (2) the influence of event rarity on the interaction of these flood drivers. To investigate this hypothesis, we use 2776 stations from the Global Runoff Data Centre paired with rainfall and soil moisture from the Global Land Data Assimilation System. Flood events are chosen to isolate the flood driving rainfall volume, rainfall peak, and antecedent soil moisture, and trends are analysed in each of these variables alongside the subsequent flood peak. The analysis is limited to stations with 30 years or more of active record with the majority of stations in North America, Europe, Brazil, Oceania, and southern Africa.& & & & We find that, while peak rainfall magnitudes are increasing globally, storm volumes are not increasing as greatly, resulting in a decrease in storm durations. Antecedent soil moisture on the other hand is consistently drier across the world. The result is a mixed flood response that depends on the local climate and the event rarity. In temperate and cold regions of the world floods are generally increasing in magnitude & #8211 these increases are less for more frequent events (those expected to occur on average once per year) and greater for more rare events (those expected to occur once every 10 years). The increases in flood magnitude are consistently less than the increases in the peak rainfall and rainfall volume because of drying soils.& & & & In tropical and arid regions, there is a decline in flood magnitude for frequent flood events, with increases in flood magnitude only for the rarest events. This is because, in these regions, the antecedent moisture decreases outweigh the increase in rainfall. These results point to a worst of both world& #8217 s scenario where small floods, responsible for filling our water supplies, are decreasing, while the large flood events which pose a risk to life and infrastructure, are increasing.& &
Publisher: Informa UK Limited
Date: 03-07-2016
Publisher: American Geophysical Union (AGU)
Date: 06-2007
DOI: 10.1029/2006WR004913
Start Date: 09-2018
End Date: 12-2022
Amount: $404,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2020
End Date: 12-2024
Amount: $345,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 06-2014
End Date: 06-2018
Amount: $710,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 06-2016
End Date: 10-2020
Amount: $387,041.00
Funder: Australian Research Council
View Funded Activity