Darling River Research Articles

Climate Change Reduces Darling River Water Levels by Decreasing Eastern Australian Rainfall

Climate Change Reduces Darling River Water Levels by Decreasing Eastern Australian Rainfall

Provenance of the Copi North heavy mineral sands deposit, Murray Basin, Australia, based on the geochronology and geochemistry of detrital zircon, rutile and monazite

The Murray Basin hosts one of the world’s largest strandplain systems and has enormous potential for heavy mineral sand resources of titanium, zircon and rare earth elements. Further discovery of heavy mineral sand deposits can be aided via improved understanding of the source and transport of detrital heavy minerals of the basin. In this study, the provenance of two heavy mineral sand units of the Copi North deposit (western NSW) was determined using U–Pb geochronology and geochemistry of detrital zircon, rutile and monazite. Results from the two units are similar, indicating they derive from the same sources. Approximately 42% of the zircon population is aged <470 Ma and is interpreted to have been derived from the Tasmanides. Older zircon populations, up to ca 2.5 Ga, were largely derived from the Adelaide Superbasin and Delamerian Orogen, or from metasedimentary rocks of the Lachlan Orogen. Over 90% of rutile U–Pb ages are between 570 and 450 Ma, correlating either to Delamerian metamorphism or to detrital rutile from the Darling Basin; both sources are supported by rutile geochemistry that is indicative of a metasedimentary source. Most monazites have U–Pb ages of ca 600 Ma, which is consistent with an ultimate source from the Mt Arrowsmith Volcanics and/or Antarctica. A minor proportion of the monazite was sourced from igneous rocks of the New England Orogen. Temporal changes in sediment source regions can be inferred when considering the detrital mineral record for Copi North with other mineral sand deposits of the basin. Older (>ca 6.7 Ma) deposits such as Copi North feature a significant proportion of post-350 Ma detritus, reflecting the important role of the ancestral Darling River in supplying sediment from the north at the earliest stages of Murray Basin development. Post-6.7 Ma deposits lack a major component of detritus for far northern sources, and instead consist of sediment derived dominantly from western (Adelaide Superbasin) and eastern (Lachlan Orogen) sources, the latter delivered via the Murray River.

Satellite Video Remote Sensing for Flood Model Validation

AbstractSatellite‐based optical video sensors are poised as the next frontier in remote sensing. Satellite video offers the unique advantage of capturing the transient dynamics of floods with the potential to supply hitherto unavailable data for the assessment of hydraulic models. A prerequisite for the successful application of hydraulic models is their proper calibration and validation. In this investigation, we validate 2D flood model predictions using satellite video‐derived flood extents and velocities. Hydraulic simulations of a flood event with a 5‐year return period (discharge of 722 m3 s−1) were conducted using Hydrologic Engineering Center—River Analysis System 2D in the Darling River at Tilpa, Australia. To extract flood extents from satellite video of the studied flood event, we use a hybrid transformer‐encoder, convolutional neural network (CNN)‐decoder deep neural network. We evaluate the influence of test‐time augmentation (TTA)—the application of transformations on test satellite video image ensembles, during deep neural network inference. We employ Large Scale Particle Image Velocimetry (LSPIV) for non‐contact‐based river surface velocity estimation from sequential satellite video frames. When validating hydraulic model simulations using deep neural network segmented flood extents, critical success index peaked at 94% with an average relative improvement of 9.5% when TTA was implemented. We show that TTA offers significant value in deep neural network‐based image segmentation, compensating for aleatoric uncertainties. The correlations between model predictions and LSPIV velocities were reasonable and averaged 0.78. Overall, our investigation demonstrates the potential of optical space‐based video sensors for validating flood models and studying flood dynamics.

Satellite Video Remote Sensing for Estimation of River Discharge

AbstractWe demonstrate that river discharge can be estimated by deriving water surface velocity estimates from satellite‐derived video imagery when combined with high‐resolution topography of channel geometry. Large Scale Particle Image Velocimetry (LSPIV) was used to map surface velocity from 28 s of 5 Hz satellite video acquired at a 1.2 m nominal ground spacing over the Darling River, Tilpa, Australia, during a 1‐in‐5‐year flood. We stabilized and assessed the uncertainty of the residual motion induced by the satellite platform, enhancing our sub‐pixel motion analysis, and quantified the sensitivity of image extraction rates on computed velocities. In the absence of in situ observations, LSPIV velocity estimates were validated against predictions from a calibrated 2D hydrodynamic model. Despite the confounding influence of selecting a surface velocity depth‐averaging coefficient, inference of discharge was within 0.3%–15% compared with gauging station measurements. These results provide a valuable foundation for refining satellite video LSPIV techniques.

Spatio-Temporal Analysis and Contribution of Agricultural Drought in Daling River Basin: A VIC Model-Based Soil Moisture Simulation and SMAPI Evaluation

Soil moisture is a crucial factor that directly influences agricultural drought. As such, investigating drought-monitoring methods utilizing soil moisture data is of significant importance for accurately evaluating and predicting agricultural drought. However, the current soil moisture data for the Daling River Basin is insufficient. Therefore, the variable infiltration capacity (VIC) hydrological model was utilized to simulate soil moisture in the Daling River Basin. The simulated data were then analyzed in conjunction with the standardized moisture anomaly index (SMAPI) to analyze and evaluate the spatio-temporal characteristics of agricultural drought in the Darling River Basin. The results indicate that the frequency of drought occurrence in the basin follows a seasonal pattern of winter &gt; spring &gt; autumn &gt; summer. Between 1981 and 2019, 24 out of 39 years experienced slight or greater drought, 15 years experienced moderate or more severe drought, and 4 years experienced severe drought. Drought conditions have become exceptionally severe in the 21st century. Specifically, the frequency of drought occurrence from 2001 to 2019 was nearly 10 times higher compared to the period from 1981 to 2000. The droughts were most severe in the southeast and southwest of the Daling River Basin, while the northeast and northwest experienced relatively mild drought. Agricultural drought is influenced by numerous complex factors. The contribution of climate change (CC) and other factors (OF) to agricultural drought was quantified by using a partial derivative under six different scenarios. Results showed that SMAPI was positively correlated with precipitation and solar radiation, while negatively correlated with temperature. From 1981 to 2000, SMAPI exhibited an increasing trend that accounted for 61.66% of variability, while a decreasing trend accounted for 38.34%. From 2001 to 2019, SMAPI exhibited a significant decreasing trend that accounted for 93.53% of the variability, while the increasing trend only accounted for 6.47%. CC was the dominant factor in most of the areas with increased SMAPI. OF was the main controlling factor for areas with decreased SMAPI.

Changes in Magnitude and Shifts in Timing of Australian Flood Peaks

We analysed changes in magnitude and timing of the largest annual observed daily flow (Amax), in each water year, for 596 stations in high-value water resource catchments and flood risk locations across Australia. These stations are either included in the Bureau of Meteorology’s Hydrologic Reference Stations or used in its operational flood forecasting services. Monotonic trend (which is either consistently increasing or decreasing) analyses of the magnitude and timing of flood peaks (estimated using Amax) were performed using the Theil–Sen and Mann–Kendall approaches and circular statistics to identify the strength of seasonality and timing. We analysed regional significance across different drainage divisions using the Walker test. Monotonic decreasing trends in Amax flood magnitude were found in the Murray–Darling River Basin and in other drainage divisions in Victoria, southwest and midwest of Western Australia and South Australia. No significant obvious pattern in Amax magnitude was detected in northern Queensland, coastal NSW, central Australia and Tasmania. Monotonic increasing trends were only found in the Tanami–Timor Sea Coast drainage division in northern Australia. Monotonic trends in Amax magnitude were regionally significant at the drainage division scale. We found two distinct patterns in flood seasonality and timing. In the northern and southern parts of Australia, flood peaks generally occur from February to March and August to October, respectively. The strength of this seasonality varies across the country. Weaker seasonality was detected for locations in the Murray–Darling River Basin, and stronger seasonality was evident in northern Australia, the southwest of Western Australia, South Australia, Victoria and Tasmania. The trends of seasonality and timing reveal that in general, flood peaks have occurred later in the water year in recent years. In northern Australia, flood peaks have generally occurred earlier, at a rate of 12 days/decade. In Victoria, New South Wales and Tasmania, the trends in timing are generally mixed. However, in the southwest of Western Australia, the largest change in timing was evident, with Amax peaks commencing later at a rate of 15 days/decade. Decadal variability in flood timing was found at the drainage division scale as well. Most stations show a decreasing trend in Amax magnitude, but how that trend is associated with the change in timing is not clear.

Indigenous fish traps and fish weirs on the Darling (Baaka) River, south‐eastern Australia, and their influence on the ecology and morphology of the river and floodplains

ABSTRACTFish traps and fish weirs built by Indigenous people in the Barwon‐Darling River system of the Murray Darling Basin (MDB), south‐eastern Australia, are an important component of their traditional social, spiritual and economic systems. The celebrated Brewarrina stone fish traps (Ngunnhu) on the Barwon River are the largest and best documented stone fish traps in the Basin. However, there has been minimal research on the many other stone fish traps in this system. This paper focusses on the in‐stream stone fish traps downstream of Brewarrina along the Darling (Baaka) River, some still partly extant, remembered, or documented in historical material. Wooden and earthen bank fish traps and weirs, while not as enduring and archaeologically visible as stone fish traps, were frequently used on the Darling (Baaka) floodplain lakes, swamps and billabongs. Archaeological evidence, traditional cultural knowledge and historical materials are utilised to document the complex social processes and modification of landscapes associated with fish traps and weirs. By demonstrating that Barkandji were active and successful managers of the river and its ecology prior to colonisation, and that much of this cultural knowledge is retained by current generations, the authors make a case for them to renew their custodianship and a decision‐making role in water management.

Resilience to hydrological droughts in the northern Murray-Darling Basin, Australia

We respond to the problem of declining streamflows in the northern Murray–Darling Basin, Australia, a region that suffers from hydrological droughts and a drying trend. We partitioned the effect of meteorological trends from anthropogenic drivers on annual streamflow, quantified the effect of annual streamflow decline on waterbird abundance, estimated the effects of streamflow change on a measure of ecosystem resilience, and calculated the net benefits of in-stream water reallocation. The anthropogenic drivers of hydrological droughts were assessed by comparing the Lower Darling (hereafter the Barka) River, which has large recorded water extractions, with the adjacent Paroo River, which has very little recorded water extractions. Findings include: (1) only about one-third of the recent reduced streamflow of the Barka River is due to a meteorological drying trend; (2) statistically significant declines in waterbird species richness and abundance have occurred on both rivers between 1983–2000 and 2001–2020; (3) declines in waterbird abundance have been much larger along the Barka River than the Paroo River; and (4) ecosystem resilience, as measured by waterbird abundance, wasgreater on the Paroo River. Our four-step framework is applicable in any catchment with adequate time-series data and supports adaptive responses to hydrological droughts. This article is part of the Royal Society Science+ meeting issue ‘Drought risk in the Anthropocene’.

Machine Learning Assessment of the Impact of Global Warming on the Climate Drivers of Water Supply to Australia’s Northern Murray-Darling Basin

Droughts and long dry spells, interspersed with intense rainfall events, have been characteristic of the northern Murray-Darling Basin (NMDB), a major Australian agricultural region. The NMDB precipitation results from weather systems ranging from thunderstorms to larger scale events. The larger scale events exhibit high seasonal and annual rainfall variability. To detect attributes shaping the NMDB precipitation patterns, and hence net water inflows to the vast Darling River catchment area, numerous (45) possible attributes were assessed for their influence on rainfall trends. Four periods were assessed: annual, April–May (early cool-season), June–September (remaining cool-season), and October–March (warm-season). Linear and non-linear regression machine learning (ML) methods were used to identify the dominant attributes. We show the impact of climate drivers on the increasingly dry April–May months on annual precipitation and warmer temperatures since the early 1990s. The NMDB water supply was further reduced during 1992–2018 by the lack of compensating rainfall trends for the April–May decline. The identified attributes include ENSO, the Southern Annular Mode, the Indian Ocean Dipole, and both local and global sea surface temperatures. A key finding is the prominence of global warming as an attribute, both individually and in combination with other climate drivers.

Merging Landsat and airborne LiDAR observations for continuous monitoring of floodplain water extent, depth and volume

The Darling River system in Australia is under pressure from water extraction and climate change. Management interventions such as environmental flow releases require understanding of water storage dynamics and the connectivity of floodplains and wetlands. Such knowledge can be gleaned from the long observational record of the Landsat series of satellite sensors and high (<5 m) resolution digital elevation models derived from airborne light detection and ranging (LiDAR). Here, for the first time, we develop and demonstrate an approach to reconstruct 16-day floodplain water dynamics, including extent, depth, and volume for a long Landsat time series (1987 to present). Time series mapping of surface water extent at 5-m resolution was achieved by topographic downscaling of Landsat-derived surface water data. We propose a simple and effective algorithm to restore missing data in the images caused by, e.g., cloud and shadows, swath edges and the Landsat 7 Scan Line Corrector (SLC) failure, thereby increasing the number of useable images five-fold. The 5-m surface water extent maps clearly delineate the narrow river channel and the boundary of floodplain wetlands. They can capture the development, peak and retreat of flood events. By combining Landsat and airborne LiDAR observations, we produced time series of surface water depth mapping at 5-m resolution, accounting for the degree of hydraulic surface water connectivity. Based on these maps, we derived 16-day floodplain volume dynamics for 1987 to present. The correlation coefficient between upstream river flow records and floodplain volume time series was 0.88, indicating that the estimates were robust. The algorithms developed can be used for ongoing very high-resolution mapping to assist in managing human water use and environmental health in the Murray-Darling Basin.

Small artificial impoundments have big implications for hydrology and freshwater biodiversity

Headwater streams are critical for freshwater ecosystems. Global and continental studies consistently show major dams as dominant sources of hydrological stress threatening biodiversity in the world’s major rivers, but cumulative impacts from small artificial impoundments (SAIs) concentrated in headwater streams have rarely been acknowledged. Using the Murray Darling River basin (Australia) and the Arkansas River basin (US) as case studies, we examined the hydrological impacts of SAIs. The extent of their influence is considerable, altering hydrology in 280–380% more waterways as compared to major dams. Hydrological impacts are concentrated in smaller streams (catchment area &lt;100 km2), raising concerns that the often diverse and highly endemic biota found in these systems may be under threat. Adjusting existing biodiversity planning and management approaches to address the cumulative effects of many small and widely distributed artificial impoundments presents a rapidly emerging challenge for ecologically sustainable water management.

Introduction to the special edition on overabundant macropods

Introduction to the special edition on overabundant macropods

The Fish Health Risk Indicator: linking water quality and river flow data with fish health to improve our predictive capacity around fish death events

Severe drought conditions contributed to three mass fish mortality events in the Darling River near Menindee, part of the Murray–Darling Basin, Australia, during the summer of 2018–19. An independent assessment recommended the need for improved modelling approaches to identify when sections of rivers may be more susceptible to fish kill events. We present a geographic information system (GIS)-based tool that combines meteorological forecasts with river flow and algal biomass datasets to identify river reaches where additional stresses on fish health may produce an increased risk of mass fish deaths. At present the tool is still in development and will require the addition of extra datasets and testing using historical datasets to further validate its accuracy. Despite the tool being in its development stage, the decision support tool has been widely accepted and provides natural resource managers with a rapid way to understand and communicate risks to fish health, supporting improved water management options across the Murray–Darling Basin that may ultimately help reduce the frequency and severity of large-scale fish mortality events.

Key steps to improve the assessment, evaluation and management of fish kills: lessons from the Murray–Darling River system, Australia

Fish kills are very visible, with high levels of public scrutiny and major effects on populations. In 2018–19, extensive fish kills in the lower Darling River, south-eastern Australia, resulted in the deaths of millions of fish, including threatened and popular, iconic angling and important cultural species. This distressed local communities and the broader Australian society, who questioned the competence of fish and water management. Fish kills are increasing in frequency and severity, exacerbated by climate change. This paper reports on eight major fish-kill case studies across the Murray–Darling Basin that were examined to assess management adequacy. Field assessments and reporting have been poor, not documenting all species or numbers affected. Few values of fishes (cultural, conservation, recreational, social, ecological, economic) have been assessed and replacement or management costs not determined. There is a need to philosophically change our approach to take fish kills more seriously. More comprehensive approaches to assessment, evaluation and management are needed. Responsibilities for fish kills should be clarified and include water and habitat management agencies. Post-kill recovery plans that include the replacement of lost ecological assets should be published and enacted. This paper provides a fresh perspective on fish kills, with 15 key recommendations applicable to improve future management worldwide.

Assessment of the causes and solutions to the significant 2018–19 fish deaths in the Lower Darling River, New South Wales, Australia

In late 2018 to early 2019, three significant fish death events occurred in the Lower Darling River, Australia, with mortality estimates of millions of fish. We examined the proximate and ultimate causes of these events. We determined that not only were the conditions existing at the time a significant contributing factor, but that antecedent conditions, particularly during the period 2010–17, also contributed. The extreme hot and dry climate during 2018, extending into 2019, shaped the conditions that saw a large fish biomass, which had flourished in the Darling River and Menindee Lakes since favourable spawning conditions in 2016, isolated in weir pools, with no means of escaping upstream or downstream. Strong and persistent weir pool stratification created hypoxic conditions in the hypolimnion. A series of sudden cool changes subsequently initiated rapid and sudden mixing of the stratified waters, causing depletion of oxygen throughout the water column and resulting in the fish deaths. The events were also shaped by broader climatic, hydrological and basin management contexts that placed the Lower Darling River at risk of such fish deaths. Our observations have implications for future river management, and we make several suggestions how policy makers and river operators can minimise fish death risks into the future.

How fish kills affected traditional (Baakandji) and non-traditional communities on the Lower Darling–

In the summer of 2018–19 mass fish kills occurred in the Lower Darling (Baaka) River in south-eastern Australia. The fish kills received national and international attention and have been the focus of numerous government agency and independent assessments. Although fish kills have previously been recorded in the Lower Darling region, the size and rapid succession of the 2018–19 ‘Menindee’ fish kills made them unprecedented in the Murray–Darling Basin, placing significant pressure on the native fish community. Although the deaths of millions of fish were documented, the significant negative effect that the fish kills had on local communities, particularly the traditional Baakandji people, was largely ignored. The social and cultural aspects of such events can have major non-economic effects on local communities. In this paper we document heart-felt feelings conveyed by local community members. Their sense of loss, despair and helplessness is compounded by frustration regarding water management and policy decision making in the Murray–Darling Basin. However, these tragic events have increased understanding of traditional Baakandji connection to the river and its fish and, together with local recovery efforts, now provide prospects for enhanced community and agency cooperation to improve the health of the lower Darling Baaka River and restore its native fish populations.

Field trials to determine the efficacy of aerators to mitigate hypoxia in inland waterways

Following a series of fish deaths in the lower Darling River in the austral summer of 2018–19, several field trials were undertaken over two summers to determine the efficacy of various aerators to mitigate the effects of hypoxia to prevent fish deaths. The aerators evaluated included: low-powered, solar bubble-plume diffusers; high-flow, single-port Venturi systems; pontoon-mounted multi-port Venturi systems; and an ultra-fine bubble generator. The effectiveness of bubble diffusers appears related to their power, the number of units used and their running time. Pontoon-mounted multi-port Venturi aerators and high-flow, single-port Venturi aerators were much more successful in maintaining oxygen levels and may have prevented fish deaths in the Darling River in early 2019. However, the Venturi aerators were expensive to run, consuming hundreds to thousands of litres of diesel fuel per week. Trial of an ultra-fine oxygen bubble pump showed promise because it supersaturated the water with dissolved oxygen while not elevating total gas pressure to levels that would cause gas-bubble trauma in fish. Although aerators may play a role in emergency responses to hypoxic fish deaths, they have limitations regarding their area of influence (at best thousands of square metres) and their cost to deploy and operate.

Population demographics of golden perch (

An understanding of population demographics and life history processes is integral to the rehabilitation of fish populations. In Australia’s highly modified Murray–Darling Basin, native fish are imperilled and fish deaths in the Darling River in 2018–19 highlighted their vulnerability. Golden perch (Macquaria ambigua) is a long-lived percichthyid that was conspicuous in the fish kills. To guide population rehabilitation in the Darling River, pre-fish kill age structure, provenance and movement of golden perch were explored using otolith microstructure and chemistry (87Sr/86Sr). Across the Lower and Mid-Darling River, recruitment was episodic, with dominant cohorts associated with years characterised by elevated discharge. There was substantial variability in age structure, recruitment source and movement patterns between the Lower and Mid-Darling River. In the Mid-Darling River, tributaries were an important recruitment source, whereas in the Lower Darling fish predominantly originated in the Darling River itself. Downstream movement of juveniles, upstream migration of adults and return movements to natal locations were important drivers of population structure. Restoring resilient golden perch populations in the Darling River will be reliant on mitigating barriers to movement, promoting a connected mosaic of recruitment sources and reinstating the hydrological and hydraulic factors associated with spawning, recruitment and dispersal. Globally, increasing water resource development and climate change will necessitate such integrated approaches to the management of long-lived migratory riverine fishes.

Contrasting natal origin and movement history informs recovery pathways for three lowland river species following a mass fish kill

Understanding the spatial and temporal scales over which key population processes occur is fundamental to effective fisheries management, especially when informing recovery actions following extreme events. In 2018–19, hypoxia-induced fish kills occurred in the lower Darling River, south-eastern Australia. We collected carcasses of three potamodromous species that perished during these events to reconstruct their lifetime movements and identify potential recovery mechanisms. Golden perch Macquaria ambigua, Murray cod Maccullochella peelii and silver perch Bidyanus bidyanus otolith 87Sr/86Sr profiles were compared with water 87Sr/86Sr ratios to better understand natal provenance and movement history, and to identify the scale at which migration influences population processes. Golden perch were predominantly locally spawned (Darling River), although we found some evidence of emigration into the nearby Murray River early in life and return movements into the Darling River. Murray cod were mainly locally spawned and thereafter lifelong residents, with some evidence of stocking supplementing populations. Silver perch were mostly immigrants, with the Murray River (&gt;500 km away) the principal source of fish. For recovery of native fish populations to be effective in the Darling River, recovery actions are required that incorporate knowledge on the relevant spatial and temporal scales over which life history processes occur.

The 2019 flash droughts in subtropical eastern Australia and their association with large-scale climate drivers

During 2017–2019, drought existed in many parts of Australia with varying degrees of severity and varied timing of development and intensification. In a broad sense, the surface climate conditions went from anomalously wet in 2016 to an official government-declared drought from the end of 2017. The drought subsequently intensified further to become most severe in mid to late 2019. Here we explore the more detailed evolution of the 2019 conditions over subtropical eastern Australia and infer its predictability through linear relationships with large-scale climate drivers. To monitor the detailed drought evolution, we use the Evaporative Stress Index (ESI) computed over a 4-week running window on a 5 km grid. Flash drought onset is defined as when there is a rapid decline in the ESI that is sustained over at least 2 weeks which ends in drought conditions. For the Central Slopes area of the upper Darling River basin, flash drought onset occurred in June, persisted over 6 months, and rapidly terminated through a flash recovery in February 2020. In the far east of Australia (East Coast regions), flash drought onset was identified later, in November and December. For the Central Slopes area, less than half the magnitude of the flash drought development in June could be explained through linear relationships with the positive Indian Ocean Dipole mode (IOD) and the central Pacific El Niño, together with the long-term trend in ESI in the region. Similarly, only about half the magnitude of the East Coast flash drought developments in November and December could be explained by the ongoing positive IOD, central Pacific El Niño, negative Southern Annular Mode, and ongoing global warming trend. Therefore, although these large-scale drivers set the stage for the likelihood of drought, successful prediction of flash drought will require more local and current information than those large-scale climate drivers alone.