Francis Chiew

Contrasting ecohydrological links explaining variation in evapotranspiration across global land surface

Publisher: American Geophysical Union (AGU)

Date: 08-07-2017

DOI: 10.1002/2017JD027025

Explaining changes in rainfall–runoff relationships during and after Australia's Millennium Drought: a community perspective

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.

Evaluating Regional and Global Hydrological Models against Streamflow and Evapotranspiration Measurements

Publisher: American Meteorological Society

Date: 03-2016

DOI: 10.1175/JHM-D-15-0107.1

Abstract: Land surface and global hydrological models are often used to characterize global water and energy fluxes and stores and to model their future trajectories. This study evaluates estimates of streamflow and evapotranspiration (ET) obtained with a priori parameterization from a land surface model [CSIRO Atmosphere Biosphere Land Exchange (CABLE)] and a global hydrological model (H08) against a global dataset of streamflow from 644 largely unregulated catchments and ET from 98 flux towers and benchmarks their performance against two lumped conceptual daily rainfall–runoff models [modèle du Génie Rural à 4 paramètres Journalier (GR4J) and a simplified version of the HYDROLOG model (SIMHYD)]. The results show that all four models perform poorly in simulating the monthly and annual runoff values, with the rainfall–runoff models outperforming both CABLE and H08. The model biases in runoff are generally reflected as a complementary opposite bias in ET. All models can generally reproduce the observed seasonal and interannual runoff variability. The correlations between the modeled and observed runoff time series are reasonable, with the rainfall–runoff models performing slightly better than CABLE and H08 at the monthly time scale and all four models performing similarly at the annual time scale. The results suggest that while the land surface and global hydrological models cannot adequately simulate the actual runoff time series and long-term average volumes, they can reasonably simulate the monthly and interannual runoff variability and trends and can therefore be reliably used for broadscale or comparative regional and global water and energy balance assessments and simulations of future trajectories. They can be improved through validating the models or calibrating some of the more sensitive and less physically based parameters.

Different Hydroclimate Modelling Approaches Can Lead to a Large Range of Streamflow Projections under Climate Change: Implications for Water Resources Management

Publisher: MDPI AG

Date: 09-2022

DOI: 10.3390/W14172730

Abstract: The paper compares future streamflow projections for 133 catchments in the Murray–Darling Basin simulated by a hydrological model with future rainfall inputs generated from different methods informed by climate change signals from different global climate models and dynamically downscaled datasets. The results show a large range in future projections of hydrological metrics, mainly because of the uncertainty in rainfall projections within and across the different climate projection datasets. Dynamical downscaling provides simulations at higher spatial resolutions, but projections from different datasets can be very different. The large number of approaches help provide a robust understanding of future hydroclimate conditions, but they can also be confusing. For water resources management, it may be prudent to communicate just a couple of future scenarios for impact assessments with stakeholders and policymakers, particularly when practically all of the projections indicate a drier future in the Basin. The median projection for 2046–2075 relative to 1981–2010 for a high global warming scenario is a 20% decline in streamflow across the Basin. More detailed assessments of the impact and adaptation options could then use all of the available datasets to represent the full modelled range of plausible futures.

Recent increases in terrestrial carbon uptake at little cost to the water cycle

Publisher: Springer Science and Business Media LLC

Date: 24-07-2017

DOI: 10.1038/S41467-017-00114-5

Abstract: Quantifying the responses of the coupled carbon and water cycles to current global warming and rising atmospheric CO 2 concentration is crucial for predicting and adapting to climate changes. Here we show that terrestrial carbon uptake (i.e. gross primary production) increased significantly from 1982 to 2011 using a combination of ground-based and remotely sensed land and atmospheric observations. Importantly, we find that the terrestrial carbon uptake increase is not accompanied by a proportional increase in water use (i.e. evapotranspiration) but is largely (about 90%) driven by increased carbon uptake per unit of water use, i.e. water use efficiency. The increased water use efficiency is positively related to rising CO 2 concentration and increased canopy leaf area index, and negatively influenced by increased vapour pressure deficits. Our findings suggest that rising atmospheric CO 2 concentration has caused a shift in terrestrial water economics of carbon uptake.

Plausible Hydroclimate Futures for the Murray-Darling Basin. A report for the Murray–Darling Basin Authority

Publisher: CSIRO

Date: 2020

DOI: 10.25919/SAMV-EY93

Coal Mining Impacts on Baseflow Detected Using Paired Catchments

Publisher: American Geophysical Union (AGU)

Date: 02-2020

DOI: 10.1029/2019WR025770

Abstract: Large‐scale coal mining not only disturbs natural landscapes but also alters catchment hydrological processes. Although investigating how mining activities such as open cut and/or underground mining change catchment baseflow is critical for understanding mining‐related hydrological mechanisms and for helping water resource management, published data on these changes have not been well documented. This study uses data‐driven approaches to examine how baseflow changes in four sets of paired catchments in the Hunter River Basin in Australia, which is one of the most intensive mining regions across the globe. The difference of cumulative anomaly percentage and double mass curves are used to detect the changes in baseflow and to identify the potential mining impacts. Our results show that underground mining has led to a decline in baseflow, while open cut mining has tended to increase baseflow, and significantly changed the baseflow trend for catchments where underground and open cut mining coexist. The mining impact signal, however, is on the top of regional climate change impacts that dominate baseflow annual variability. The data‐driven investigation cannot separate impacts due to multiple and overlapping disturbances of mining activities but provides insight and guidance for hydrological modeling to simulate mining impacts on hydrological regimes.

Impacts of coal mining and coal seam gas extraction on groundwater and surface water

Publisher: Elsevier BV

Date: 12-2020

DOI: 10.1016/J.JHYDROL.2020.125281

Multi-timescale Performance of Groundwater Drought in Connection with Climate

Publisher: Springer Science and Business Media LLC

Date: 12-04-2023

DOI: 10.1007/S11269-023-03515-Y

Reducing bias in streamflow predictions derived from climate model output.

Publisher: Elsevier BV

Date: 04-2023

DOI: 10.1016/J.JHYDROL.2023.129322

Explaining changes in rainfall-runoff relationships during and after Australia's Millennium Drought: a community perspective

Publisher: Copernicus GmbH

Date: 20-04-2022

DOI: 10.5194/HESS-2022-147

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.

Can Indirect Evaluation Methods and Their Fusion Products Reduce Uncertainty in Actual Evapotranspiration Estimates?

Publisher: American Geophysical Union (AGU)

Date: 06-2022

DOI: 10.1029/2021WR031069

Abstract: Accurately estimating actual evapotranspiration (ET) across global land surface is one of the key challenges in terrestrial hydrological cycles and energy flux balance studies. Gridded ET products have the potential for application in ungauged basins, but their uncertainties are possibly large and it remains unclear which one is best for a given basin. The water balance (WB) method provides a direct estimate of basin scale ET, but it cannot be used in ungauged basins where streamflow data are unavailable. Here, we first assess the performance of ET from 10 global ET products against WB ET estimates in 43 large river basins. The paper then uses three indirect evaluation methods [Three Cornered Hat (TCH), Arithmetic Average (AA), and Bayesian Three Cornered Hat] to identify the optimal ET products without the need of prior information, and to generate fusion products combining the ET from multiple products. Using the evaluation results derived from the WB method as the reference, the results show that the three methods have great success in identifying poorer products, suggesting that they are useful in filtering poor ET products in applications. However, the ability of such methods in identifying better ET products degrades slightly. The AA fusion product, which combines ET outputs from multiple products, is marginally better than the best single ET product in many of the 43 basins. Because of its simplicity, it could be used to reduce the uncertainty in ET estimates from multiple products for ungauged basins and regions.

Different precipitation elasticity of runoff for precipitation increase and decrease at watershed scale

Publisher: American Geophysical Union (AGU)

Date: 26-11-2019

DOI: 10.1029/2018JD030129

Stochastic Generation of Plausible Hydroclimate Futures Using Climate Teleconnections for Southeastern Australia

Publisher: American Meteorological Society

Date: 10-2023

DOI: 10.1175/JHM-D-22-0206.1

Abstract: Generating plausible future climate timeseries is needed for bottom-up climate impact modelling, as well as downscaling climate model output for hydrological applications. A novel method for generating multisite daily stochastic climate series is developed based on: 1) linear regression between climate teleconnection timeseries (e.g. IPO/SOI) and annual rainfall, 2) clustered method of fragments for subannual disaggregation, and 3) a regression-based approach to daily potential evapotranspiration (PET) for hydrological modelling. We demonstrate that bias (i.e. overs ling) occurs with the standard method of fragments disaggregation in the multisite context and show that selection of an analogue year from clustered rainfall amounts provides better s ling properties than the standard method of fragments. Using hydrological data for south-eastern Australia, we model runoff from observed and simulated rainfall and PET using the GR4J model. Simulated annual and daily rainfall and runoff characteristics from the new method are similar to existing methods, with improvements demonstrated in wet-wet transition probabilities and spatial (between-site) correlations.

Impact of Coal Resource Development on Streamflow Characteristics: Influence of Climate Variability and Climate Change

Publisher: MDPI AG

Date: 30-08-2018

DOI: 10.3390/W10091161

Abstract: The potential cumulative impact of coal mining and coal seam gas extraction on water resources and water-dependent assets from proposed developments in eastern Australia have been recently assessed through a Bioregional Assessment Programme. This study investigates the sensitivity of the Bioregional Assessment results to climate change and hydroclimate variability, using the Gloucester sub-region as an ex le. The results indicate that the impact of climate change on streamflow under medium and high future projections can be greater than the impact from coal mining development, particularly where the proposed development is small. The differences in the modelled impact of coal resource development relative to the baseline under different plausible climate futures are relatively small for the Gloucester sub-region but can be significant in regions with large proposed development. The sequencing of hydroclimate time series, particularly when the mine footprint is large, significantly influences the modelled maximum coal resource development impact. The maximum impact on volumetric and high flow variables will be higher if rainfall is high in the period when the mine footprint is largest, and vice-versa for low flow variables. The results suggest that detailed analysis of coal resource development impact should take into account climate change and hydroclimate variability.

Estimation of Climate Change Impact on Mean Annual Runoff across Continental Australia Using Budyko and Fu Equations and Hydrological Models

Publisher: American Meteorological Society

Date: 06-2012

DOI: 10.1175/JHM-D-11-097.1

Abstract: This paper presents the climate change impact on mean annual runoff across continental Australia estimated using the Budyko and Fu equations informed by projections from 15 global climate models and compares the estimates with those from extensive hydrological modeling. The results show runoff decline in southeast and far southwest Australia, but elsewhere across the continent there is no clear agreement between the global climate models in the direction of future precipitation and runoff change. Averaged across large regions, the estimates from the Budyko and Fu equations are reasonably similar to those from the hydrological models. The simplicity of the Budyko equation, the similarity in the results, and the large uncertainty in global climate model projections of future precipitation suggest that the Budyko equation is suitable for estimating climate change impact on mean annual runoff across large regions. The Budyko equation is particularly useful for data-limited regions, for studies where only estimates of climate change impact on long-term water availability are needed, and for investigative assessments prior to a detailed hydrological modeling study. The Budyko and Fu equations are, however, limited to estimating the change in mean annual runoff for a given change in mean annual precipitation and potential evaporation. The hydrological models, on the other hand, can also take into account potential changes in the subannual and other climate characteristics as well as provide a continuous simulation of daily and monthly runoff, which is important for many water availability studies.

Generation of multi-site stochastic daily rainfall with four weather generators: a case study of Gloucester catchment in Australia

Publisher: Springer Science and Business Media LLC

Date: 20-11-2017

DOI: 10.1007/S00704-017-2306-3

Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections

Publisher: Copernicus GmbH

Date: 08-06-2020

DOI: 10.5194/HESS-24-2963-2020

Abstract: Abstract. Dynamical downscaling of future projections of global climate model outputs can provide useful information about plausible and possible changes to water resource availability, for which there is increasing demand in regional water resource planning processes. By explicitly modelling climate processes within and across global climate model grid cells for a region, dynamical downscaling can provide higher-resolution hydroclimate projections and independent (from historical time series), physically plausible future rainfall time series for hydrological modelling applications. However, since rainfall is not typically constrained to observations by these methods, there is often a need for bias correction before use in hydrological modelling. Many bias-correction methods (such as scaling, empirical and distributional mapping) have been proposed in the literature, but methods that treat daily amounts only (and not sequencing) can result in residual biases in certain rainfall characteristics, which flow through to biases and problems with subsequently modelled runoff. We apply quantile–quantile mapping to rainfall dynamically downscaled by the NSW and ACT Regional Climate Modelling (NARCliM) Project in the state of Victoria, Australia, and examine the effect of this on (i) biases both before and after bias correction in different rainfall metrics, (ii) change signals in metrics in comparison to the bias and (iii) the effect of bias correction on wet–wet and dry–dry transition probabilities. After bias correction, persistence of wet states is under-correlated (i.e. more random than observations), and this results in a significant bias (underestimation) of runoff using hydrological models calibrated on historical data. A novel representation of quantile–quantile mapping is developed based on lag-one transition probabilities of dry and wet states, and we use this to explain residual biases in transition probabilities. Representing quantile–quantile mapping in this way demonstrates that any quantile mapping bias-correction method is unable to correct the underestimation of autocorrelation of rainfall sequencing, which suggests that new methods are needed to properly bias-correct dynamical downscaling rainfall outputs.

Schizophrenia liability shares common molecular genetic risk factors with sleep duration and nightmares in childhood

Publisher: F1000 Research Ltd

Date: 20-08-2019

DOI: 10.12688/WELLCOMEOPENRES.15060.2

Abstract: Background: Sleep abnormalities are common in schizophrenia, often appearing before psychosis onset however, the mechanisms behind this are uncertain. We investigated whether genetic risk for schizophrenia is associated with sleep phenotypes. Methods: We used data from 6,058 children and 2,302 mothers from the Avon Longitudinal Study of Parents and Children (ALSPAC). We examined associations between a polygenic risk score for schizophrenia and sleep duration in both children and mothers, and nightmares in children, along with genetic covariances between these traits. Results: Polygenic risk for schizophrenia was associated with increased risk of nightmares (OR=1.07, 95% CI: 1.01, 1.14, p=0.02) in children, and also with less sleep (β=-44.52, 95% CI: −88.98, −0.07 p=0.05). We observed a similar relationship with sleep duration in mothers, although evidence was much weaker (p=0.38). Finally, we found evidence of genetic covariance between schizophrenia risk and reduced sleep duration in children and mothers, and between schizophrenia risk and nightmares in children. Conclusions: These molecular genetic results support recent findings from twin analysis that show genetic overlap between sleep disturbances and psychotic-like experiences. They also show, to our knowledge for the first time, a genetic correlation between schizophrenia liability and risk of nightmares in childhood.

Schizophrenia liability shares common molecular genetic risk factors with sleep duration and nightmares in childhood

Publisher: F1000 Research Ltd

Date: 25-01-2019

DOI: 10.12688/WELLCOMEOPENRES.15060.1

Abstract: Background: Sleep abnormalities are common in schizophrenia, often appearing before psychosis onset however, the mechanisms behind this are uncertain. We investigated whether genetic risk for schizophrenia is associated with sleep phenotypes. Methods: We used data from 6,058 children and 2,302 mothers from the Avon Longitudinal Study of Parents and Children (ALSPAC). We examined associations between a polygenic risk score for schizophrenia and sleep duration in both children and mothers, and nightmares in children, along with genetic covariances between these traits. Results: Polygenic risk for schizophrenia was associated with increased risk of nightmares (OR=1.07, 95% CI: 1.01, 1.14, p=0.02) in children, and also with less sleep (β=-44.52, 95% CI: −88.98, −0.07 p=0.05). We observed a similar relationship with sleep duration in mothers, although evidence was much weaker (p=0.38). Finally, we found evidence of genetic covariance between schizophrenia risk and reduced sleep duration in children and mothers, and between schizophrenia risk and nightmares in children. Conclusions: These molecular genetic results support recent findings from twin analysis that show genetic overlap between sleep disturbances and psychotic-like experiences. They also show, to our knowledge for the first time, a genetic correlation between schizophrenia liability and risk of nightmares in childhood.

Uncertainties of Statistical Downscaling from Predictor Selection: “Equifinality”

Publisher: Elsevier BV

Date: 05-2018

DOI: 10.1016/J.ATMOSRES.2017.12.008

Change-signal impacts in downscaled data and its influence on hydroclimate projections

Publisher: Elsevier BV

Date: 09-2018

DOI: 10.1016/J.JHYDROL.2018.06.018

Projections of water futures for Australia: an update

Publisher: Modelling and Simulation Society of Australia and New Zealand

Date: 12-2019

DOI: 10.36334/MODSIM.2019.K7.ZHENGH

Statistical analysis of attributions of climatic characteristics to nonstationary rainfall‐streamflow relationship

Publisher: Elsevier BV

Date: 12-2021

DOI: 10.1016/J.JHYDROL.2021.127017

Robust modelling to address UPH19 to predict future hydrological responses for water resources adaptation under climate change

Publisher: Copernicus GmbH

Date: 04-03-2021

DOI: 10.5194/EGUSPHERE-EGU21-9014

Abstract: & & This paper addresses the implications of UPH19 in extrapolating hydrological models to predict the future and assessing water resources adaptation to climate change. Many studies have now shown that traditional application of hydrological models calibrated against past observations will underestimate the range in the projected future hydrological impact, that is, it will underestimate the decline in runoff where a runoff decrease is projected, and underestimate the increase in runoff where a runoff increase is projected. This study opportunistically uses data from south-eastern Australia which recently experienced a long and severe drought lasting more than ten years and subsequent partial hydrological recovery from the drought. The paper shows that a more robust calibration of rainfall-runoff models to produce good calibration metrics in both the dry periods and wet periods, at the expense of the best calibration over the entire data period, can produce a more accurate estimate of the uncertainty in the projected future runoff, but cannot entirely eliminate the modelling limitation of underestimating the projected range in future runoff. This is because of the need to consider trade-offs between the calibration objectives, particularly in simulating the dry periods, versus enhanced bias that results from the consideration. Hydrological models must therefore also need to be adapted to reflect the non-stationary nature of catchment and vegetation responses in a changing climate under warmer conditions, higher CO& sub& & /sub& and changed precipitation patterns. This is an active area of research in UPH19, and some ideas relevant to this region will be presented.& &

Estimating ecosystem maximum light use efficiency based on the water use efficiency principle

Publisher: IOP Publishing

Date: 10-2021

DOI: 10.1088/1748-9326/AC263B

Coupled estimation of 500 m and 8-day resolution global evapotranspiration and gross primary production in 2002–2017

Publisher: Elsevier BV

Date: 03-2019

DOI: 10.1016/J.RSE.2018.12.031

Modelling runoff with statistically downscaled daily site, gridded and catchment rainfall series

Publisher: Elsevier BV

Date: 06-2013

DOI: 10.1016/J.JHYDROL.2013.03.041

How does bias correction of RCM precipitation affect modelled runoff?

Publisher: Copernicus GmbH

Date: 23-09-2014

DOI: 10.5194/HESSD-11-10683-2014

Abstract: Abstract. Many studies bias correct daily precipitation from climate models to match the observed precipitation statistics, and the bias corrected data are then used for various modelling applications. This paper presents a review of recent methods used to bias correct precipitation from regional climate models (RCMs). The paper then assesses four bias correction methods applied to the weather research and forecasting (WRF) model simulated precipitation, and the follow-on impact on modelled runoff for eight catchments in southeast Australia. Overall, the best results are produced by either quantile mapping or a newly proposed two-state gamma distribution mapping method. However, the difference between the tested methods is small in the modelling experiments here (and as reported in the literature), mainly because of the substantial corrections required and inconsistent errors over time (non-stationarity). The errors remaining in bias corrected precipitation are typically lified in modelled runoff. The tested methods cannot overcome limitation of RCM in simulating precipitation sequence, which affects runoff generation. Results further show that whereas bias correction does not seem to alter change signals in precipitation means, it can introduce additional uncertainty to change signals in high precipitation amounts and, consequently, in runoff. Future climate change impact studies need to take this into account when deciding whether to use raw or bias corrected RCM results. Nevertheless, RCMs will continue to improve and will become increasingly useful for hydrological applications as the bias in RCM simulations reduces.

The within-day behaviour of 6 minute rainfall intensity in Australia

Publisher: Copernicus GmbH

Date: 18-08-2011

DOI: 10.5194/HESS-15-2561-2011

Abstract: Abstract. The statistical behaviour and distribution of high-resolution (6 min) rainfall intensity within the wet part of rainy days (total rainfall depth mm) is investigated for 42 stations across Australia. This paper compares nine theoretical distribution functions (TDFs) in representing these data. Two goodness-of-fit statistics are reported: the Root Mean Square Error (RMSE) between the fitted and observed within-day distribution and the coefficient of efficiency for the fit to the highest rainfall intensities (average intensity of the 5 highest intensity intervals) across all days at a site. The three-parameter Generalised Pareto distribution was clearly the best performer. Good results were also obtained from Exponential, Gamma, and two-parameter Generalized Pareto distributions, each of which are two parameter functions, which may be advantageous when predicting parameter values. Results of different fitting methods are compared for different estimation techniques. The behaviour of the statistical properties of the within-day intensity distributions was also investigated and trends with latitude, Köppen climate zone (strongly related to latitude) and daily rainfall amount were identified. The latitudinal trends are likely related to a changing mix of rainfall generation mechanisms across the Australian continent.

Australian National Outlook 2015: Economic activity, resource use, environmental performance and living standards, 1970-2050.

Publisher: CSIRO

Date: 2015

DOI: 10.4225/08/58542C22D98AD

A benefit cost analysis of strategic and operational management options for water management in hyper-arid southern Peru

Publisher: Elsevier BV

Date: 05-2022

DOI: 10.1016/J.AGWAT.2022.107518

Predicting Runoff Signatures Using Regression and Hydrological Modeling Approaches

Publisher: American Geophysical Union (AGU)

Date: 10-2018

DOI: 10.1029/2018WR023325

Abstract: Accurate prediction of runoff signatures is important for numerous hydrological and water resources applications. However, there are lack of comprehensive evaluations of various approaches for predicting hydrological signatures. This study, for the first time, introduces regression tree ensemble approach and compares it with other three widely used approaches (multiple linear regression, multiple log‐transformed linear regression, and hydrological modeling) for assessing prediction accuracy of 13 runoff characteristics or signatures, using a large data set from 605 catchments across Australia. The climate, in particular, mean annual precipitation and aridity index, has the most significant influence on the runoff signatures. Physical catchment attributes including forest ratio, slope, and soil water holding capacity also have significant influence ( p 0.05) on the runoff signatures. All four approaches can predict the long‐term average and high flow signatures accurately. The regression approaches can also well predict majority of the other runoff signatures, with the Nash‐Sutcliffe Efficiency larger than 0.60. The regression tree ensemble outperforms the two linear regressions in predicting signatures of flow dynamics. The hydrological models, calibrated to one specific objective criterion, cannot predict many of the runoff signatures, particularly those reflecting low flows and flow dynamics. This is because in most hydrological model applications, the simulations allow satisfactory predictions of long‐term average and high flow signatures. In applications where a specific runoff signature is needed, regression relationships that directly relate that runoff signature to catchment attributes give the best predictions. Here the regression tree ensemble is overall best and offers significant potential, being able to predict most of the runoff signatures very well.

Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems

Publisher: Wiley

Date: 06-04-2018

DOI: 10.1002/ECO.1974

ClimKaddo tool

Publisher: CSIRO

Date: 2017

DOI: 10.4225/08/5934DEF7CDE78

Hydroclimate projections for Victoria at 2040 and 2065

Publisher: CSIRO

Date: 2016

DOI: 10.4225/08/5892224490E71

Quantifying the impacts of vegetation changes on catchment storage‐discharge dynamics using paired‐catchment data

Publisher: American Geophysical Union (AGU)

Date: 07-2017

DOI: 10.1002/2017WR020600

A robust methodology for conducting large-scale assessments of current and future water availability and use: A case study in Tasmania, Australia

Publisher: Elsevier BV

Date: 2012

DOI: 10.1016/J.JHYDROL.2011.02.011

Identifying terraces in the hilly and gully regions of the Loess Plateau in China

Publisher: Wiley

Date: 07-08-2019

DOI: 10.1002/LDR.3405

Implication of calibration period on modelling climate change impact on future runoff

Publisher: Copernicus GmbH

Date: 12-06-2015

DOI: 10.5194/PIAHS-371-3-2015

Abstract: Abstract. This paper explores the consideration and implication of calibration period on the modelled climate change impact on future runoff. The results show that modelled runoff and hydrologic responses can be influenced by the choice of historical data period used to calibrate and develop the hydrological model. Modelling approaches that do not take this into account may therefore underestimate the range and uncertainty in future runoff projections. Nevertheless, the uncertainty associated with the choice of hydrological models and consideration of calibration dataset for modelling climate change impact on runoff is likely to be small compared to the uncertainty in the future rainfall projections.

Adapting Water Management to Climate Change in the Murray–Darling Basin, Australia

Publisher: MDPI AG

Date: 12-09-2021

DOI: 10.3390/W13182504

Abstract: Climate change is threatening water security in water-scarce regions across the world, challenging water management policy in terms of how best to adapt. Transformative new approaches have been proposed, but management policies remain largely the same in many instances, and there are claims that good current management practice is well adapted. This paper takes the case of the Murray–Darling Basin, Australia, where management policies are highly sophisticated and have been through a recent transformation in order to critically review how well adapted the basin’s management is to climate change. This paper synthesizes published data, recent literature, and water plans in order to evaluate the outcomes of water management policy. It identifies several limitations and inequities that could emerge in the context of climate change and, through synthesis of the broader climate adaptation literature, proposes solutions that can be implemented when basin management is formally reviewed in 2026.

Monthly and seasonal streamflow forecasts using rainfall‐runoff modeling and historical weather data

Publisher: American Geophysical Union (AGU)

Date: 05-2011

DOI: 10.1029/2010WR009922

How sensitive are catchment runoff estimates to on-farm storages under current and future climates?

Publisher: Elsevier BV

Date: 11-2023

DOI: 10.1016/J.JHYDROL.2023.130185

Climate analyses for South-West Western Australia: A report to the Australian Government from the CSIRO South-West Western Australia Sustainable Yields Project

Publisher: CSIRO

Date: 2010

DOI: 10.4225/08/584D9590D046B

Lags in hydrologic recovery following an extreme drought: Assessing the roles of climate and catchment characteristics

Publisher: American Geophysical Union (AGU)

Date: 06-2017

DOI: 10.1002/2017WR020683

Estimating the Relative Uncertainties Sourced from GCMs and Hydrological Models in Modeling Climate Change Impact on Runoff

Publisher: American Meteorological Society

Date: 02-2012

DOI: 10.1175/JHM-D-11-058.1

Abstract: This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is lified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–runoff models informed by 1 GCM (a less than 7% difference between the minimum and maximum results). The difference between the rainfall–runoff modeling results is larger in the drier regions for scenarios of big declines in future rainfall and in the low-flow characteristics. The rainfall–runoff modeling here considers only the runoff sensitivity to changes in the input climate data (primarily daily rainfall), and the difference between the hydrological modeling results is likely to be greater if potential changes in the climate–runoff relationship in a warmer and higher CO2 environment are modeled.

Decadal Trends in Evaporation from Global Energy and Water Balances

Publisher: American Meteorological Society

Date: 02-2012

DOI: 10.1175/JHM-D-11-012.1

Abstract: Satellite and gridded meteorological data can be used to estimate evaporation (E) from land surfaces using simple diagnostic models. Two satellite datasets indicate a positive trend (first time derivative) in global available energy from 1983 to 2006, suggesting that positive trends in evaporation may occur in “wet” regions where energy supply limits evaporation. However, decadal trends in evaporation estimated from water balances of 110 wet catchments do not match trends in evaporation estimated using three alternative methods: 1) , a model-tree ensemble approach that uses statistical relationships between E measured across the global network of flux stations, meteorological drivers, and remotely sensed fraction of absorbed photosynthetically active radiation 2) , a Budyko-style hydrometeorological model and 3) , the Penman–Monteith energy-balance equation coupled with a simple biophysical model for surface conductance. Key model inputs for the estimation of and are remotely sensed radiation and gridded meteorological fields and it is concluded that these data are, as yet, not sufficiently accurate to explain trends in E for wet regions. This provides a significant challenge for satellite-based energy-balance methods. Trends in for 87 “dry” catchments are strongly correlated to trends in precipitation (R2 = 0.85). These trends were best captured by , which explicitly includes precipitation and available energy as model inputs.

Using Remote Sensing Data-based Hydrological Model Calibrations for Predicting Runoff in Ungauged or Poorly Gauged Catchments

Publisher: Wiley

Date: 28-06-2020

DOI: 10.1002/ESSOAR.10503449.1

A framework estimating cumulative impact of damming on downstream water availability

Publisher: Elsevier BV

Date: 08-2019

DOI: 10.1016/J.JHYDROL.2019.05.061

Multi-decadal trends in global terrestrial evapotranspiration and its components

Publisher: Springer Science and Business Media LLC

Date: 11-01-2016

DOI: 10.1038/SREP19124

Abstract: Evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981–2012 and its three components: transpiration from vegetation (E t ), direct evaporation from the soil (E s ) and vaporization of intercepted rainfall from vegetation (E i ). During this period, ET over land has increased significantly ( p 0.01), caused by increases in E t and E i , which are partially counteracted by E s decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in E t over land is about twofold of the decrease in E s . These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle.

Use of data assimilation to improve rainfall-runoff model structure for climate change projections

Publisher: Copernicus GmbH

Date: 23-09-2022

DOI: 10.5194/IAHS2022-365

Abstract: & & Data assimilation is a powerful tool that has been used to correct states and parameters of rainfall-runoff models based on recent streamflow, remotely sensed soil moisture or groundwater data. Data assimilation is now routinely applied by forecasting centres around the world to improve simulations and increase forecast skill. In this work, we are less concerned with the direct benefits of data assimilation on model outputs, but more on the nature of the corrections introduced and how they can be analysed to diagnose structural deficiencies in rainfall-runoff models.& & & & Rainfall-runoff models have been shown to lack extrapolation capacity in simulating dry and wet periods that are more extreme than calibration conditions. This is particularly concerning in the context of climate change studies where more climate extremes are generally predicted for expected. This is the case in South-Eastern Australia where annual rainfall is expected to decrease significantly under most climate scenarios. Consequently, the improvement of rainfall-runoff model structures to better simulate dry flow regimes is critical to obtain robust estimates of water resources availability.& & & & In this work, we assimilated streamflow data in the GR2M monthly rainfall-runoff models for 100 catchments in South-East Australia. The assimilation was conducted during a wet period between 1970 to 1995 and used to identify model structure deficiencies, particularly in the function computing water exchanges with nearby catchments. An attempt of correcting these deficiencies was undertaken using a simple regression approach. Finally, the correction was applied during a dry period (1995-2010) and performance was compared with the original (uncorrected) model. The results suggest that the corrected simulations better capture streamflow extremes, especially low flows. Further work is also discussed related to the use of additional data such as LAI and groundwater data to better constrain the correction regression.& &

Research to support water resources planning in the Murray-Darling Basin

Publisher: Copernicus GmbH

Date: 22-09-2022

DOI: 10.5194/IAHS2022-120

Abstract: & & Many hydrological models (GR4J, Sacramento and SIMHYD for ex le) currently exist to reproduce hydrological response at a catchment scale. Some models (IQQM, Source for ex le) also exist to assess the impacts of human interventions designed to in some way optimise the use of water in regulated river systems. There are however a much smaller number of models designed to assess the impacts of water resources management on socio-economics, the community and the environment more broadly.& & & & A current program of work known as MD-WERP & #8211 the Murray-Darling Water and Environment Research Program, seeks to improve the understanding and representation of key processes in hydrological models used to underpin basin analysis and planning. We are working with policy makers and water managers in State and Federal government to apply these models to assess the impacts of water resource management options on hydrological, ecological and socio-economic outcomes in the Murray-Darling Basin. This will allow planners to consider a wide range of management options in the review and revision of the Murray-Darling Basin Plan that is scheduled for the next few years.& & & & The vast majority of global and regional climate models, as well as understanding of changes in global and regional circulation patterns suggest a drier future for the Murray-Darling Basin with consequently more frequent and severe droughts. The management options to be assessed therefore are primarily those that minimise the impacts of drier conditions on the environment, irrigators and the Basin community, along with models that allow assessments of trade-offs between these disparate water users to be made.& & & & The models that are required to assess these adaptation options need to be erse, covering not only things such as changes in rainfall and hydrological response, but also climate adaptation options in river system operations, conjunctive use of groundwater and surface water, water trading and allocation, and consequent impacts on the environment, irrigators, basin communities and First Nations groups.& & & & This presentation will provide an overview of MD-WERP with a focus on the climate adaptation and hydrology themes, assessing how modelling tools can be used to better inform Basin-wide water resources policy and planning.& &

Using remote sensing data-based hydrological model calibrations for predicting runoff in ungauged or poorly gauged catchments

Publisher: American Geophysical Union (AGU)

Date: 08-2020

DOI: 10.1029/2020WR028205

Abstract: Because remote sensing (RS) data are spatially and temporally explicit and available across the globe, they have the potential to be used for predicting runoff in ungauged catchments and poorly gauged regions, a challenging area of research in hydrology. There is potential to use remotely sensed data for calibrating hydrological models in regions with limited streamflow gauges. This study conducts a comprehensive investigation on how to incorporate gridded remotely sensed evapotranspiration (AET) and water storage data for constraining hydrological model calibration in order to predict daily and monthly runoff in 30 catchments in the Yalong River basin in China. To this end, seven RS data calibration schemes are explored and compared to direct calibration against observed runoff and traditional regionalization using spatial proximity to predict runoff in ungauged catchments. The results show that using bias‐corrected remotely sensed AET (bias‐corrected PML‐AET data) for constraining model calibration performs much better than using the raw remotely sensed AET data (nonbias‐corrected AET obtained from PML model estimate). Using the bias‐corrected PML‐AET data in a gridded way is much better than using lumped data and outperforms the traditional regionalization approach especially in headwater and large catchments. Combining the bias‐corrected PML‐AET and GRACE water storage data performs similarly to using the bias‐corrected PML‐AET data only. This study demonstrates that there is great potential in using bias‐corrected RS‐AET data to calibrating hydrological models (without the need for gauged streamflow data) to estimate daily and monthly runoff time series in ungauged catchments and sparsely gauged regions.

A comparison of multi-site daily rainfall downscaling techniques under Australian conditions

Publisher: Elsevier BV

Date: 09-2011

DOI: 10.1016/J.JHYDROL.2011.06.021

Assessing irrigated agriculture's surface water and groundwater consumption by combining satellite remote sensing and hydrologic modelling

Publisher: Elsevier BV

Date: 2016

DOI: 10.1016/J.SCITOTENV.2015.10.086

Abstract: Globally, irrigation accounts for more than two thirds of freshwater demand. Recent regional and global assessments indicate that groundwater extraction (GWE) for irrigation has increased more rapidly than surface water extraction (SWE), potentially resulting in groundwater depletion. Irrigated agriculture in semi-arid and arid regions is usually from a combination of stored surface water and groundwater. This paper assesses the usefulness of remotely-sensed (RS) derived information on both irrigation dynamics and rates of actual evapotranspiration which are both input to a river-reach water balance model in order to quantify irrigation water use and water provenance (either surface water or groundwater). The assessment is implemented for the water-years 2004/05-2010/11 in five reaches of the Murray-Darling Basin (Australia) a heavily regulated basin with large irrigated areas and periodic droughts and floods. Irrigated area and water use are identified each water-year (from July to June) through a Random Forest model which uses RS vegetation phenology and actual evapotranspiration as predicting variables. Both irrigated areas and actual evapotranspiration from irrigated areas were compared against published estimates of irrigated areas and total water extraction (SWE+GWE).The river-reach model determines the irrigated area that can be serviced with stored surface water (SWE), and the remainder area (as determined by the Random Forest Model) is assumed to be supplemented by groundwater (GWE). Model results were evaluated against observed SWE and GWE. The modelled SWE generally captures the observed interannual patterns and to some extent the magnitudes, with Pearson's correlation coefficients >0.8 and normalised root-mean-square-error<30%. In terms of magnitude, the results were as accurate as or better than those of more traditional (i.e., using areas that fluctuate based on water resource availability and prescribed crop factors) irrigation modelling. The RS irrigated areas and actual evapotranspiration can be used to: (i) understand irrigation dynamics, (ii) constrain irrigation models in data scarce regions, as well as (iii) pinpointing areas that require better ground-based monitoring.

Groundwater Impacts and Management under a Drying Climate in Southern Australia

Publisher: MDPI AG

Date: 14-12-2021

DOI: 10.3390/W13243588

Abstract: The trend to a hotter and drier climate, with more extended droughts, has been observed in recent decades in southern Australia and is projected to continue under climate change. This paper reviews studies on the projected impacts of climate change on groundwater and associated environmental assets in southern Australia, and describes groundwater planning frameworks and management responses. High-risk areas are spatially patchy due to highly saline groundwater or low-transmissivity aquifers. The proportional reduction in rainfall is lified in the groundwater recharge and some groundwater discharge fluxes. This leads to issues of deteriorating groundwater-dependent ecosystems, streamflow depletion, reduced submarine discharge, groundwater inundation and intrusion in coastal regions and reduced groundwater supply for extraction. Recent water reforms in Australia support the mitigation of these impacts, but groundwater adaptation is still at its infancy. Risk management is being incorporated in regional water and groundwater management plans to support a shift to a more sustainable level of use and more climate-resilient water resources in affected areas. The emerging strategies of groundwater trade and managed aquifer recharge are described, as is the need for a national water-focused climate change planning process.

Observed hydrologic non-stationarity in far south-eastern Australia: implications for modelling and prediction

Publisher: Springer Science and Business Media LLC

Date: 04-06-2014

DOI: 10.1007/S00477-013-0755-5

Assessment of catchment runoff and high flows in the Murray-Darling Basin under climate change

Publisher: CSIRO

Date: 2021

DOI: 10.25919/YVKF-4S63

Australian National Outlook 2015 Technical Report: Economic activity, resource use, environmental performance and living standards, 1970-2050

Publisher: CSIRO

Date: 2015

DOI: 10.4225/08/58542EB3ED885

Australia is ‘free to choose’ economic growth and falling environmental pressures

Publisher: Springer Science and Business Media LLC

Date: 11-2015

DOI: 10.1038/NATURE16065

Abstract: Over two centuries of economic growth have put undeniable pressure on the ecological systems that underpin human well-being. While it is agreed that these pressures are increasing, views ide on how they may be alleviated. Some suggest technological advances will automatically keep us from transgressing key environmental thresholds others that policy reform can reconcile economic and ecological goals while a third school argues that only a fundamental shift in societal values can keep human demands within the Earth's ecological limits. Here we use novel integrated analysis of the energy-water-food nexus, rural land use (including bio ersity), material flows and climate change to explore whether mounting ecological pressures in Australia can be reversed, while the population grows and living standards improve. We show that, in the right circumstances, economic and environmental outcomes can be decoupled. Although economic growth is strong across all scenarios, environmental performance varies widely: pressures are projected to more than double, stabilize or fall markedly by 2050. However, we find no evidence that decoupling will occur automatically. Nor do we find that a shift in societal values is required. Rather, extensions of current policies that mobilize technology and incentivize reduced pressure account for the majority of differences in environmental performance. Our results show that Australia can make great progress towards sustainable prosperity, if it chooses to do so.

Genetic architecture of subcortical brain structures in 38,851 individuals

Publisher: Springer Science and Business Media LLC

Date: 21-10-2019

DOI: 10.1038/S41588-019-0511-Y

Enhanced low flow prediction for water and environmental management

Publisher: Elsevier BV

Date: 05-2020

DOI: 10.1016/J.JHYDROL.2020.124658

Interim report on the hydroclimate of the Pilbara: past, present and future. A technical report to the Government of Western Australia and industry partners from the CSIRO Pilbara Water Resource Assessment

Publisher: CSIRO

Date: 2013

DOI: 10.4225/08/584AF3F138FDC

Using Remote Sensing Data-based Hydrological Model Calibrations for Predicting Runoff in Ungauged or Poorly Gauged Catchments

Publisher: Wiley

Date: 22-04-2020

DOI: 10.1002/ESSOAR.10502731.1

Assessment of an analogue downscaling method for modelling climate change impacts on runoff

Publisher: Elsevier BV

Date: 11-2012

DOI: 10.1016/J.JHYDROL.2012.09.024

Predicting hydrological signatures in ungauged catchments using spatial interpolation, index model, and rainfall–runoff modelling

Publisher: Elsevier BV

Date: 09-2014

DOI: 10.1016/J.JHYDROL.2014.06.032

How does bias correction of regional climate model precipitation affect modelled runoff?

Publisher: Copernicus GmbH

Date: 04-02-2015

DOI: 10.5194/HESS-19-711-2015

Abstract: Abstract. Many studies bias correct daily precipitation from climate models to match the observed precipitation statistics, and the bias corrected data are then used for various modelling applications. This paper presents a review of recent methods used to bias correct precipitation from regional climate models (RCMs). The paper then assesses four bias correction methods applied to the weather research and forecasting (WRF) model simulated precipitation, and the follow-on impact on modelled runoff for eight catchments in southeast Australia. Overall, the best results are produced by either quantile mapping or a newly proposed two-state gamma distribution mapping method. However, the differences between the methods are small in the modelling experiments here (and as reported in the literature), mainly due to the substantial corrections required and inconsistent errors over time (non-stationarity). The errors in bias corrected precipitation are typically lified in modelled runoff. The tested methods cannot overcome limitations of the RCM in simulating precipitation sequence, which affects runoff generation. Results further show that whereas bias correction does not seem to alter change signals in precipitation means, it can introduce additional uncertainty to change signals in high precipitation amounts and, consequently, in runoff. Future climate change impact studies need to take this into account when deciding whether to use raw or bias corrected RCM results. Nevertheless, RCMs will continue to improve and will become increasingly useful for hydrological applications as the bias in RCM simulations reduces.

Trends and variability of rainfall characteristics influencing annual streamflow: A case study of southeast Australia

Publisher: Wiley

Date: 07-12-2022

DOI: 10.1002/JOC.7923

Abstract: The trend and variability in rainfall characteristics that influence annual streamflow of southeast Australia is assessed using two methods, non‐parametric Kendall test and linear slope, and two gridded daily rainfall datasets (SILO and AWAP) and 1,196 station rainfall data for 1971–2021 period. The rainfall anomaly before, during and after the Millennium Drought (1997–2009) is compared to quantify the variability. The results show: (a) a declining rainfall trend is detected as the recent dry decades were preceded by wet decades. The declining trend largely occurs from autumn through to spring with the largest trend in August to October followed by April and May (b) the trend is more significant for number of rainfall days and for multi‐day rainfall totals (and more so for longer accumulations) than for annual rainfall (c) the very high extreme rainfall shows a small increasing trend in summer and mixed signal in the other seasons (d) the streamflow in the post drought period is lower than the long‐term mean, despite the mean annual rainfall being slightly higher. This can be partly explained by the rainfall‐runoff relationship of catchments not having fully recovered from the prolonged drought and partly by changes in rainfall characteristics, like the wet spell length and multi‐day rainfall, influencing annual streamflow (e) The general conclusions for analyses with different sources of daily rainfall data are the same. However, some differences do exist, with SILO gridded rainfall and station data having larger areas with statistically significant trend than the AWAP gridded rainfall, as well as larger declining trends in the high elevation areas. The general conclusions of this study are drawn from an Australia case study but could have implications for other regions to investigate the attributions of rainfall characteristics other than annual rainfall to the non‐stationary rainfall‐streamflow relationship.

Climate data and their characterisation for hydrological scenario modelling across northern Australia

Publisher: CSIRO

Date: 2009

DOI: 10.4225/08/584AF30470D0A

Database of CMIP5 climate change projections across south Asia

Publisher: CSIRO

Date: 2015

DOI: 10.4225/08/58518BA9EB9E0

An assessment of modelling capacity to identify the impacts of climate variability on catchment hydrology

Publisher: Elsevier BV

Date: 03-2011

DOI: 10.1016/J.MATCOM.2010.05.007

Rainfall-Runoff Modelling Considerations to Predict Streamflow Characteristics in Ungauged Catchments and under Climate Change

Publisher: MDPI AG

Date: 24-09-2018

DOI: 10.3390/W10101319

Abstract: This paper investigates the prediction of different streamflow characteristics in ungauged catchments and under climate change, with three rainfall-runoff models calibrated against three different objective criteria, using a large data set from 780 catchments across Australia. The results indicate that medium and high flows are relatively easier to predict, suggesting that using a single unique set of parameter values from model calibration against an objective criterion like the Nash–Sutcliffe efficiency is generally adequate and desirable to provide a consistent simulation and interpretation of daily streamflow series and the different medium and high flow characteristics. However, the low flow characteristics are considerably more difficult to predict and will require careful modelling consideration to specifically target the low flow characteristic of interest. The modelling results also show that different rainfall-runoff models and different calibration approaches can give significantly different predictions of climate change impact on streamflow characteristics, particularly for characteristics beyond the long-term averages. Predicting the hydrological impact from climate change, therefore, requires careful modelling consideration and calibration against appropriate objective criteria that specifically target the streamflow characteristic that is being assessed.

Rainfall–runoff modelling in northern Australia: A guide to modelling strategies in the tropics

Publisher: Elsevier BV

Date: 09-2012

DOI: 10.1016/J.JHYDROL.2011.12.046

Examination of climate risk using a modified uncertainty matrix framework—Applications in the water sector

Publisher: Elsevier BV

Date: 02-2013

DOI: 10.1016/J.GLOENVCHA.2012.11.003

Decrease in southeastern Australian water availability linked to ongoing Hadley cell expansion

Publisher: American Geophysical Union (AGU)

Date: 04-2014

DOI: 10.1002/2013EF000194

Can Remotely Sensed Actual Evapotranspiration Facilitate Hydrological Prediction in Ungauged Regions Without Runoff Calibration?

Publisher: American Geophysical Union (AGU)

Date: 2020

DOI: 10.1029/2019WR026236

Abstract: Runoff prediction in ungauged catchments is a significant hydrological challenge. The common approach is to calibrate hydrological models against streamflow data from gauged catchments, and then regionalize or transfer parameter values from the gauged calibration to predict runoff in the ungauged catchments. This paper explores the potential for using parameter values from hydrological models calibrated solely against readily available remotely sensed evapotranspiration data to estimate runoff time series. The advantage of this approach is that it does not require observed streamflow data for model calibration and is therefore particularly useful for runoff prediction in poorly gauged or ungauged regions. The modeling experiments are carried out using data from 222 catchments across Australia. The results from the remotely sensed evapotranspiration runoff‐free calibration are encouraging, particularly in simulating monthly runoff and mean annual runoff in the wetter catchments. However, results for daily runoff and in the drier regions are relatively poor, and further developments are needed to realize the benefit of direct model calibration against remotely sensed data to predict runoff in ungauged catchments.

An investigation into changes in climate characteristics causing the recent very low runoff in the southern Murray-Darling Basin using rainfall-runoff models

Publisher: American Geophysical Union (AGU)

Date: 18-10-2011

DOI: 10.1029/2010WR010333

Future climate and runoff projections across South Asia from CMIP5 global climate models and hydrological modelling

Publisher: Elsevier BV

Date: 08-2018

DOI: 10.1016/J.EJRH.2018.06.004

Dynamic identification of summer cropping irrigated areas in a large basin experiencing extreme climatic variability

Publisher: Elsevier BV

Date: 11-2014

DOI: 10.1016/J.RSE.2014.08.016

Climate change and water in south Asia - Overview and literature review

Publisher: CSIRO

Date: 2016

DOI: 10.4225/08/58518B8BD697C

Landscape patches influencing hillslope erosion processes and flow hydrodynamics

Publisher: Elsevier BV

Date: 11-2019

DOI: 10.1016/J.GEODERMA.2019.07.003

Conceptual Rainfall–Runoff Model Performance with Different Spatial Rainfall Inputs

Publisher: American Meteorological Society

Date: 10-2011

DOI: 10.1175/2011JHM1340.1

Abstract: Different methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inputs for each grid cell. The results show only marginal improvement in the “distributed” application compared to the single rainfall series, and only in two of the four models for the larger catchments. Where a single lumped catchment-average daily rainfall series is used, care should be taken to obtain a rainfall series that best represents the spatial rainfall distribution across the catchment. However, there is little advantage in driving a conceptual rainfall–runoff model with different rainfall inputs from different parts of the catchment compared to using a single lumped rainfall series, where only estimates of runoff at the catchment outlet is required.

Hydrologic nonstationarity and extrapolating models to predict the future: overview of session and proceeding

Publisher: Copernicus GmbH

Date: 12-06-2015

DOI: 10.5194/PIAHS-371-17-2015

Abstract: Abstract. This paper provides an overview of this IAHS symposium and PIAHS proceeding on "hydrologic nonstationarity and extrapolating models to predict the future". The paper provides a brief review of research on this topic, presents approaches used to account for nonstationarity when extrapolating models to predict the future, and summarises the papers in this session and proceeding.

Drought projections for Australia: updated results and analysis of model simulations

Publisher: Elsevier BV

Date: 12-2020

DOI: 10.1016/J.WACE.2020.100280

Representation of the Australian sub‐tropical ridge in the CMIP3 models

Publisher: Wiley

Date: 14-12-2011

DOI: 10.1002/JOC.3406

Estimating the Impact of Projected Climate Change on Runoff across the Tropical Savannas and Semiarid Rangelands of Northern Australia

Publisher: American Meteorological Society

Date: 04-2012

DOI: 10.1175/JHM-D-11-062.1

Abstract: The majority of the world’s population growth to 2050 is projected to occur in the tropics. Hence, there is a serious need for robust methods for undertaking water resource assessments to underpin the sustainable management of water in tropical regions. This paper describes the largest and most comprehensive assessment of the future impacts of runoff undertaken in a tropical region using conceptual rainfall–runoff models (RRMs). Five conceptual RRMs were calibrated using data from 115 streamflow gauging stations, and model parameters were regionalized using a combination of spatial proximity and catchment similarity. Future rainfall and evapotranspiration projections (denoted here as GCMES) were transformed to catchment-scale variables by empirically scaling (ES) the historical climate series, informed by 15 global climate models (GCMs), to reflect a 1°C increase in global average surface air temperature. Using the best-performing RRM ensemble, approximately half the GCMES used resulted in a spatially averaged increase in mean annual runoff (by up to 29%) and half resulted in a decrease (by up to 26%). However, ~70% of the GCMES resulted in a difference of within ±5% of the historical rainfall (1930–2007). The range in modeled impact on runoff, as estimated by five RRMs (for in idual GCMES), was compared to the range in modeled runoff using 15 GCMES (for in idual RRMs). For mid- to high runoff metrics, better predictions will come from improved GCMES projections. A new finding of this study is that in the wet–dry tropics, for extremely large runoff events and low flows, improvements are needed in both GCMES and rainfall–runoff modeling.

Future global streamflow declines are probably more severe than previously estimated

Publisher: Springer Science and Business Media LLC

Date: 02-02-2023

DOI: 10.1038/S44221-023-00030-7

Contrasting runoff trends between dry and wet parts of eastern Tibetan Plateau

Publisher: Springer Science and Business Media LLC

Date: 13-11-2017

DOI: 10.1038/S41598-017-15678-X

Abstract: As the “Asian Water Tower”, the Tibetan Plateau (TP) provides water resources for more than 1.4 billion people, but suffers from climatic and environmental changes, followed by the changes in water balance components. We used state-of-the-art satellite-based products to estimate spatial and temporal variations and trends in annual precipitation, evapotranspiration and total water storage change across eastern TP, which were then used to reconstruct an annual runoff variability series for 2003–2014. The basin-scale reconstructed streamflow variability matched well with gauge observations for five large rivers. Annual runoff increased strongly in dry part because of increases in precipitation, but decreased in wet part because of decreases in precipitation, aggravated by noticeable increases in evapotranspiration in the north of wet part. Although precipitation primarily governed temporal-spatial pattern of runoff, total water storage change contributed greatly to runoff variation in regions with wide-spread permanent snow/ice or permafrost. Our study indicates that the contrasting runoff trends between the dry and wet parts of eastern TP requires a change in water security strategy, and attention should be paid to the negative water resources impacts detected for southwestern part which has undergone vast glacier retreat and decreasing precipitation.

Impact of downscaled rainfall biases on projected runoff changes

Publisher: Copernicus GmbH

Date: 08-06-2019

DOI: 10.5194/HESS-24-2981-2020

Abstract: Abstract. Realistic projections of changes to daily rainfall frequency and magnitude, at catchment scales, are required to assess the potential impacts of climate change on regional water supply. We show that quantile–quantile mapping (QQM) bias-corrected daily rainfall from dynamically downscaled WRF simulations of current climate produce biased hydrological simulations, in a case study for the state of Victoria, Australia (237 629 km2). While the QQM bias correction can remove bias in daily rainfall distributions at each 10 km × 10 km grid point across Victoria, the GR4J rainfall–runoff model underestimates runoff when driven with QQM bias-corrected daily rainfall. We compare simulated runoff differences using bias-corrected and empirically scaled rainfall for several key water supply catchments across Victoria and discuss the implications for confidence in the magnitude of projected changes for mid-century. Our results highlight the imperative for methods that can correct for temporal and spatial biases in dynamically downscaled daily rainfall if they are to be suitable for hydrological projection.

The effect of spatial rainfall variability on water balance modelling for south-eastern Australian catchments

Publisher: Elsevier BV

Date: 06-2013

DOI: 10.1016/J.JHYDROL.2013.04.028

Supplementary material to "How does bias correction of RCM precipitation affect modelled runoff?"

Publisher: Copernicus GmbH

Date: 23-09-2014

DOI: 10.5194/HESSD-11-10683-2014-SUPPLEMENT

The Murrumbidgee soil moisture monitoring network data set

Publisher: American Geophysical Union (AGU)

Date: 07-2012

DOI: 10.1029/2012WR011976

Commonwealth Scientific And Industrial Research Organisation

Location: Australia

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University Of Melbourne

Location: Australia

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CSIRO Land And Water

Location: Australia

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CSIRO

Location: Australia

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Research Networks - Grant ID: RN0460181

Start Date: 12-2004

End Date: 12-2010

Amount: $1,950,000.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP130100072

Start Date: 03-2014

End Date: 12-2016

Amount: $375,000.00

Funder: Australian Research Council

Special Research Initiatives - Grant ID: SR0354677

Start Date: 12-2003

End Date: 12-2004

Amount: $10,000.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP0455338

Start Date: 07-2004

End Date: 12-2007

Amount: $252,200.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP180100796

Start Date: 05-2020

End Date: 12-2023

Amount: $410,334.00

Funder: Australian Research Council