Murray-Darling Research Articles

Pairing monitoring datasets with probabilistic forecasts to provide early warning of drought in Australia

Droughts are a cyclical feature of Australia's climate that have compounding impacts on agricultural productivity and the wellbeing of drought-affected communities. Understanding anticipated drought conditions in context of antecedent observations is critical to providing early warning of drought. In this study we paired probabilistic seasonal rainfall forecasts with precipitation, soil moisture and evapotranspiration data that were objectively combined using Principal Component Analysis (PCA). The final Drought Early Warning System (DEWS) maps overlay forecasting information with the multi-variate PCA-weighted maps at 1-, 3- and 6-month timescales over the common period of overlap between all datasets (1982–2018). In this study period, the 1982–1983 Ash Wednesday tinder drought and the 1997–2001 Millennium drought were investigated. We validated PCA-weighted maps with satellite vegetation data and found performance was strongest over the Murray Darling Basin region (R = 0.63, p = 0.009) and poorest over Central interior Australia (insignificant correlations). We also validated PCA-weighted maps using agricultural commodity data from ABARES. Significant negative correlations at 95 %, 99 % and 99.9 % confidence intervals were found between %-Area in drought category and crop cultivation area; export volume/value; crop yield; and rural debt. Our findings indicate that early warning of drought can be categorised by concern – wherein dry antecedent conditions and dry forecasted conditions are of the highest concern. The developed proof-of-concept DEWS contributes to the growing body of proactive drought management research. In a drought vulnerable future, operationalising and communicating drought early warnings will be critical to reducing the harmful impacts of drought on communities, economies, and environments.

Examining past and projecting future: an 800-year streamflow reconstruction of the Australian Murray river

Managing water security and sustaining ecosystem functions under future warming poses substantial challenges for semi-arid regions. The Murray–Darling Basin (MDB) is particularly vulnerable given the considerable demand for water that underpins Australia’s agricultural production and contribution to the national economy. Understanding future drought risk requires a robust assessment of natural variability in drought length, frequency, and magnitude. In the absence of long instrumental records, past drought characteristics can be inferred from paleo-records. We reconstruct over 800 years of Murray River streamflow using a suite of tree-ring chronologies from regions with strong climate teleconnections to the MDB. The reconstruction (1190–2000 CE) captures a broad spectrum of natural climate variability, not fully represented in instrumental records, contributing to an improved understanding of the occurrence rate of multi-year droughts. We found that the Millennium Drought, which occurred in the 2000s, was the most severe (joint duration, magnitude, and peak) during the 800-year reconstruction. The return period of this event is estimated to be ∼2500 years. However, droughts in the early-1200s were of a longer duration and similar magnitude to the Millennium Drought. We used climate models to assess how the occurrence probability of severe droughts might change in the future. Compared to the 800-year baseline, climate models project an increase in future drought severity. While the increase in drought occurrence is within the uncertainty range for most future projections, the driest forecast shows a significant increase in the likelihood of severe droughts compared to natural variability. Our results highlight the need for water management strategies not to rely solely on instrumental data as it may not fully represent current and future risks. Ensuring a resilient MDB under future warming will require a robust water security policy that captures a broader range of natural and anthropogenic variability than currently recognised.

Comment on sustainable salinity management in ‘the three-infrastructures framework and water risks in the Murray-Darling Basin, Australia’ by Williams et al. (2022)

ABSTRACT In their recent paper, Williams et al. (2022) evaluated salinity management in the Murray-Darling Basin (MDB) as ‘unsustainable’, and a risk to water availability and quality in the Basin. However, this evaluation was weakened first by a failure to analyse the Basin salinity strategies of the last thirty-five years, noting that these have led to Basin salinity target being met since 2010; and second to not providing Basin-specific data to support their evaluation. Contrary to Williams et al. comments, existing evidence indicates that infrastructure intended to improve water use efficiency (e.g. salt leaching, salt disposal basins) will generally reduce stream salinity. The requirement for a leaching efficiency means that there is a lower limit to water use efficiency improvements, but this is unlikely itself to be a major risk. We agree that the changes that have occurred over the last twenty years would warrant a review of salt storage options in the MDB that better matches future needs.

The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps

With growing concerns over water management in rivers worldwide, researchers are seeking innovative solutions to monitor and understand changing flood patterns. In a noteworthy advancement, stakeholders interested in the changing flood patterns of the Murray Darling Basin (MDB) in Australia, covering an area of 1 million km2, can now access a consistent timeseries of water depth maps for the entire basin. The dataset covers the period from 1988 to 2022 at two-monthly timestep and was developed using remotely sensed imagery and a flood depth estimation model at a spatial resolution of ≈30 m, providing a comprehensive picture of maximum observed inundation depth across the MDB. Validation against 13 hydrodynamic model outputs for different parts of the MDB yielded a mean absolute error of 0.49 m, demonstrating reasonable accuracy and reliability of the dataset. The resulting dataset is best suited to system-wide analysis but might also be useful for those interested in the history of flooding at specific locations in the system. We provide the dataset, visualization tools, and examples to support ongoing research.

Challenges of classifying and mapping perennial freshwater systems within highly variable climate zones: A case study in the Murray Darling Basin, Australia

Perennial freshwater systems are valuable natural resources that provide important ecological services globally. However, in highly variable climates, such as Australia, water availability in rivers and streams can vary greatly from year to year and from decade to decade. Further, across Australia and many other regions, perennial river systems are projected to decrease because of anthropogenic climate change, placing the ecosystems they support under additional pressure. Quantifying the potential impacts of climate change on perennial freshwater systems requires robust databases of existing water features with accurate classifications. This is a challenge for rivers that display a high degree of interannual variability since the river classification can be dependent on the period of available data. In this study, we carry out a regional scale comparison of three different spatial databases commonly used in environmental and ecological assessments of perennial systems of Australia, namely Geodata, Geofabric and Water Observations from Space (WOfS). Focusing on the southern Murray Darling Basin (MDB), due to its national and international significance and its highly variable flow regimes, we show that no single spatial database is reliable by itself in terms of perennial water classification, with notable differences likely arising from variations in the periods analysed and methods used to classify the systems. Further, an analysis of high-quality gauged streamflow data (with approximately 40-year daily records) for four sub-catchments, and long-term simulation data (>100 years) for two sub-catchments in the lower MDB, confirm that flow persistence can be non-stationary through time, with some ‘perennial’ systems exhibiting sustained periods of cease to flow (i.e. becoming non-perennial) during prolonged droughts. This study demonstrates that due consideration is required in developing baseline classification of perennial freshwater systems for assessing future changes and measuring adaptive capacity.

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

Storage of water in farm dams is important to support irrigation, stock requirements and domestic uses when reticulated water is unavailable. Farm dams that fill by intercepting landscape runoff change the total volume and seasonality of catchment streamflow, potentially impacting water policy outcomes. While numerous studies have quantified how climate change and farm dams independently change streamflow characteristics, few studies have investigated their interactions. This study investigates the interactions between farm dams and climate change in the Murray-Darling Basin of southern and eastern Australia. We use hydrological modelling that explicitly represent farm dams and remotely sensed data describing historical farm dam development to assess the impacts of farm dams for 112 catchments on catchment runoff under current and future climates. Our analysis compares current and future runoff estimates to those derived without explicitly incorporating farm dam impacts to better understand the importance of farm dams in water resources assessments.We find that modelling farm dams in these catchments improves the performance of the hydrological model relative to a traditional rainfall-runoff model ignoring the effects of farm dams. The current level of farm dam development in the Murray-Darling Basin is estimated to reduce annual catchment runoff by 13% (in the range of 8%–19%) under the historical climate across the 112 catchments investigated here. We find that explicitly modelling farm dams increases the sensitivity of simulated streamflow to climate by approximately 10%. This is primarily because farm dams introduce additional catchment storage and water extractions that do not directly follow processes represented in traditional rainfall-runoff models.Our analysis offers important information for water policymakers in Australia and globally. Firstly, explicit modelling of farm dams is critical to understanding the future availability of water resources. Secondly, explicit modelling of farm dams allows their impacts on catchment runoff to be explored under current and future climates, and for policies to manage the impacts of dams to be investigated.

DROUGHT AND HOTTER TEMPERATURE IMPACTS ON SUICIDE: EVIDENCE FROM THE MURRAY–DARLING BASIN, AUSTRALIA

The Murray–Darling Basin (MDB) is Australia’s prime agricultural region, where drought and hotter weather pose a significant threat to rural residents’ mental health – hence increasing their potential suicide risk. We investigate the impact of drought and hotter temperatures on monthly suicide within local areas in the MDB, from 2006–2016. Using Poisson fixed-effects regression modeling, we found that extreme drought and hotter temperatures were associated with increased total suicide rates. The effects of extreme drought and temperature on suicide were heterogeneous across gender and age groups, with younger men more vulnerable. Areas with higher percentages of Indigenous and farmer populations were identified as hot spots, and were vulnerable to increased temperatures and extreme drought. Green space coverage (and to some extent higher incomes) moderated the drought and suicide relationship. Providing targeted interventions in vulnerable groups and hot spot areas is warranted to reduce the suicide effect of climate change.

Bloomin’ Ridiculous: Climate Change, Water Contamination and Algal Blooms in a Land Down Under

Climate and anthropogenic change, particularly agricultural runoff, increase blue-green algae/cyanobacteria blooms. This article researches cyanobacteria alert-level identification, management, and risk communication in Lake Hume, Australia. Two methods, document and content analysis, evidence contamination events and risk communication, reflect water governance and data management limitations. Results found that Lake Hume had amber or red alerts for only one week, December 2021–December 2022. This failed to prevent government tourism promotion of recreational usage, contravening water authority red alert advice. Lake-use restrictions lacked compliance enforcement. Events during amber alerts lacked risk communication to vulnerable populations (children). Lake Hume’s governance by the Murray–Darling Basin Authority restricted risk communication to one authority that reproduced generic advice in minimal outlets/time points. Geophysical signage failed to address diversity needs (language, literacy, age, and disabilities). No risk communication was found for residents with diseases exacerbated by aerosolization. Despite WHO promoting cyanotoxin investigation, Australian research is absent in international literature. Further, Lake Hume cyanobacteria produce potentially carcinogenic microcystein. This coexists with census data revealing cancer rates higher than the national average in a waterside town. The results demonstrate the need to incorporate robust public health risk assessments, communication, and management into water management and advocate international legislation changes based on evidence-based research to reduce blooms and prevent agricultural runoff.

Is my model fit for purpose? Validating a population model for predicting freshwater fish responses to flow management

AbstractModels based on ecological processes (process‐explicit models) are often used to predict ecosystem responses to environmental changes or management scenarios. However, models are imperfect and need to be validated, ideally by testing their assumptions and outputs against independent empirical data sets. Examples of validation of process‐explicit models are rare. Recently, stochastic population models have been developed to predict the likely responses (over 10–120 years) of a riverine fish (golden perch, Macquaria ambigua) to flow management in the Murray–Darling Basin (MDB) in eastern Australia, one of the world's most regulated river basins. Declines in golden perch (and other species) are a direct consequence of altered hydrology, and managers require information to predict how fish will respond to possible future hydrological conditions to guide substantial investments in flow management. Here, we use two independent field data sets to validate our population model. We compared model predictions to observed trends to ask: (1) How do predicted population sizes and growth rates compare with observed data? (2) Does the correlation between predicted and observed population sizes and growth rates vary among populations? (3) Does the correlation between predicted and observed population sizes and growth rates vary across observed hydrological conditions? (4) How do modeled and observed fish movement rates compare? We found reasonable correlations between fish population sizes and growth rates as predicted by the model and observed in independent data sets for several populations (Aim 1), but the strength of these correlations varied among populations (Aim 2) and hydrological conditions (Aim 3). Predicted and observed fish movement rates were strongly correlated (Aim 4). Population models are frequently used in conservation decision‐making but are rarely validated. We demonstrate that: (1) validation can identify model strengths and weaknesses; (2) observed data sets often have inherent limitations that can preclude robust validations; (3) validation is likely to be more common if appropriate observed data sets are available; and (4) validation should consider the purpose of modeling. Wider consideration of these messages would contribute to more critical examinations of models, so they can be most appropriately used in conservation decision‐making.

Using Ensemble Streamflow Forecasts to Inform Seasonal Outlooks for Water Allocations in the Murray Darling Basin

Using Ensemble Streamflow Forecasts to Inform Seasonal Outlooks for Water Allocations in the Murray Darling Basin

Characterising the regional growth of on-farm storages and their implications for water resources under a changing climate

Water demand for agricultural activities has caused a growth in small on-farm storages (i.e., ≥ 0.1 ha to ≤ 10 ha) in many areas worldwide, thereby increasing the capture of landscape runoff which otherwise would enter the catchment drainage system. The cumulative effects of these on-farm storages (colloquially known as farm ponds or farm dams) can result in reduced mean annual flows, particularly during dry years. Climate change, which will very likely exacerbate extreme weather conditions including droughts, may accelerate the growth of farm dams in semi-arid agricultural areas with limited access to surface water. The aim of this study is to evaluate farm dam development and total farm dam water volumes at regional scales using Landsat water indices (WIs). The Murray-Darling Basin (MDB, 1.061 million km2) in south and eastern Australia, which has experienced a sustained growth in farm dams in the 1990s and early 2000s, is used as a case study. Using a pixel validation dataset, four WIs were trialled for their capabilities to detect the presence of water in farm dams. Of the WIs tested here, AWEIshadow showed the best performance. As a result, AWEIshadow was used to establish the year in which water was first observed (i.e., its year of commission) in 727,081 farm dams across the MDB and to calculate the total farm dam volume in the region. Farm dams’ volume in the MDB increased more than twofold between 1990 and 2020, from 1241.0 MCM (million cubic meters) to 2,629.5 MCM. The growth differed across MDB regions, generally accelerating during the ‘Millennium Drought’ (2001–2009). In the entire MDB, there was rapid development in the 1990s with 3.1% growth. Growth was 2.5% from 2000 to 2010, tapering off to 0.6% from 2010 to 2020.In Robertson et al. (this issue), the year-by-year growth in farm dams’ volume were used in a rainfall-runoff model thereby incorporating the time-varying effects of farm dams. Robertson et al. (this issue) show that explicitly modelling farm dams improves the model’s performance relative to a traditional rainfall-runoff model that ignores the effects of farm dams. Hence, this improves the capability of assessing the direct impacts of farm dams and their potential growth in climate change studies.

Australian country paper: Integrated approaches to irrigation management in the future

AbstractIrrigation in Australia expanded dramatically during the early to mid‐twentieth century under an economic and social development regime of government. This led to overallocation and overuse of many of the country's water resources to the detriment of the rivers and riverine environments. To address this degradation federal and state governments have come together to implement a range of reforms at national, basin and catchment level to return water to the rivers but not at the expense of rural communities and a range of policy reforms to implement water resource best management practice including cost recovery pricing, accuracy in measurement (resource availability and extraction). The three most significant components of these reforms are the Murray–Darling Basin Plan, the National Water Initiative and the Sustainable Rural Water Use and Infrastructure Programme (SRWUIP). These actions are complemented by infrastructure and management improvements at on‐ and off‐farm levels and examples are documented.

A protected flow breaks the drought for golden perch (Macquaria ambigua) spawning along an extensive semi‐arid river system

AbstractFreshwater ecosystems are under extreme stress due to anthropogenic influences including changing climate, river regulation and water abstraction. Improving our understanding of the hydrological determinants of key life‐history processes of fish, as well as the spatial scales over which these processes occur, is fundamental to inform effective recovery actions. We monitored the spawning response of native fish to a drought‐breaking long‐distance flow pulse that was protected from extraction by a legal intervention order in Australia's northern Murray–Darling Basin. Sampling sites were distributed across >1600 km of the Barwon–Darling River and three of its major tributaries. Larvae of the pelagophilic golden perch (Macquaria ambigua) were captured at all sites, with the size and age distribution indicative of both mainstem and tributary spawning. A mismatch between estimated hatch dates and river discharge at some locations suggested substantial flow‐assisted dispersal from upstream spawning sites, although this was site‐specific and more prevalent at downstream locations. Early life growth rates were the highest at tributary sites compared with mainstem sites, and within mainstem sites, golden perch grew faster in upper reaches compared with lower reaches. The present study provides insight into the environmental benefit of a post‐drought protected flow event whereby connected lotic habitats promoted fish spawning and dispersal over a large spatial scale. Protection of future flow events should occur to support the conservation of golden perch and other pelagophil species, particularly following future drought periods which are forecast to become more intense and frequent.

On the timing of megafaunal extinction and associated floristic consequences in Australia through the lens of functional palaeoecology

The timing and cause of megafaunal extinctions are an enduring focus of research interest and debate. Despite the developments in the analysis of coprophilous fungal spores (CFS), the proxy for reconstructing past megaherbivore changes, the environmental consequences of this fauna loss remain understudied. This is partly due to the general obscurity of such a signal in pollen records, as well as limitations in disentangling human and extinction ecological impact, and the lack of spatial information of megafauna changes in site-level sedimentary records. In Australia, the debate centres on the possibility that habitat loss through climate change, vegetation-fire change, human intervention, or a combination of these factors led to the extinction of some large animals during the Late Pleistocene. Pollen and plant isotope studies have also demonstrated that vegetation-fire responses following the Late Pleistocene megafaunal extinctions were characterized by increased vegetation density and fire activity due to reduced grazing/browsing pressure. Here, we use a well-dated marine sedimentary core record from the Murray Darling Basin in southern Australia and apply palynological and functional palaeoecological approaches to reconstruct the Late Pleistocene megafaunal abundance changes, the timing and potential cause of extinction across the basin and investigate if extinction was associated with any signal of trait-based vegetation changes. We infer megafaunal abundance changes from the abundance of CFS and compare this with climatic proxies from the same core. We then link modern observations of fruit, seed and fire response traits of plant genera within the basin to the fossil pollen record to reconstruct palaeo vegetation community traits and determine if extinction was associated with any changes in plant community trait composition. Closely-spaced 14C dates obtained from planktonic foraminifera and δ18O tie points place a major decline in CFS, and thus the timing of extinction, within the basin at ∼43.3 ka. While climate-driven environmental changes largely controlled megafaunal presence, human arrival and frequent landscape burning are considered the most likely primary cause of extinction or, at the very least, megafauna decline in the Murray Darling Basin. We also found that the proposed period of megafaunal decline was also accompanied and followed by a decline in the prevalence of plants with larger seeds and fruits that were likely to have been once dispersed by megaherbivores. Our study supports the idea of a human-driven megafaunal extinction in mainland Australia and that the extinction caused changes in vegetation due to reduced plant dispersal and herbivory. However, high fire activity primarily linked to these vegetation changes was not observed, as humans were already practicing landscape burning before the period of megafaunal extinction and likely continued to do so afterward.

Evaluating and optimising performance of multi-species call recognisers for ecoacoustic restoration monitoring.

Monitoring the effect of ecosystem restoration can be difficult and time-consuming. Autonomous sensors, such as acoustic recorders, can aid monitoring across long time scales. This project successfully developed, tested and implemented call recognisers for eight species of frog in the Murray-Darling Basin. Recognisers for all but one species performed well and substantially better than many species recognisers reported in the literature. We achieved this through a comprehensive development phase, which carefully considered and refined the representativeness of training data, as well as the construction (amplitude cut-off) and the similarity thresholds (score cut-offs) of each call template used. Recogniser performance was high for almost all species examined. Recognisers for Crinia signifera, Limnodynastes fletcherii, Limnodynastes dumerilii, Litoria peronii and Crinia parinsignifera all performed well, with most templates having receiver operating characteristics values (the proportion of true positive and true negatives) over 0.7, and some much higher. Recognisers for L. peronii, L. fletcherii and L. dumerilii performed particularly well in the training data set, which allowed for responses to environmental watering events, a restoration activity, to be clearly observed. While slightly more involved than building recognisers using commercial packages, the workflows ensure that a high-quality recogniser can be built and the performance fine-tuned using multiple parameters. Using the same framework, recognisers can be improved on in future iterations. We believe that multi-species recognisers are a highly effective and precise way to detect the effects of ecosystem restoration.

Managing Water for Environmental Provision and Horticultural Production in South Australia’s Riverland

This paper outlines and analyses preliminary research in South Australia’s Riverland, part of Australia’s largest river system, the Murray–Darling Basin, and one of the nation’s most important horticultural production areas. It focuses on the Renmark Irrigation Trust (RIT), which supplies water to c570 irrigators. Management of the Basin is controversial, with conflicting demands from stakeholders, including smallholder irrigators, broadacre farming, indigenous groups, and the environment. Climate change and the water market have contributed to uncertainty over environmental sustainability. Using sequential mixed methods, including a questionnaire survey, focus groups and interviews, we investigate the chief risks perceived by irrigators and their future-plans in face of concerns over variable water flows and economic uncertainty. We highlight the RIT’s contribution to river restoration and investigate its plans for additional on-farm water stewardship. We reveal high levels of uncertainty among irrigators regarding their future viability, including unintended consequences from the water market, the controversial role of water brokers, and environmental viability of the river system. The growth of ‘lifestyle blocks’ occupied by hobby farmers has added both to landscape diversity and fragmentation. To maintain a resilient horticultural industry, there may need to be adjustments to water management in the Basin to protect smallholders’ livelihoods whilst continuing to meet specified environmental needs.

Tributary Inflows to a Regulated River Influence Bacterial Communities and Increase Bacterial Carbon Assimilation

Inflows from unregulated tributaries change the physical, chemical, and biotic conditions in receiving regulated rivers, impacting microbial community structure and metabolic function. Understanding how tributary inflows affect bacterial carbon production (BCP) is integral to understanding energy transfer in riverine ecosystems. To investigate the role of tributary inflows on bacterial community composition and BCP, a ~90th percentile natural flow event was sampled over 5 days along the Lachlan River and its tributaries within the Murray-Darling Basin of eastern Australia. Increased tributary inflows after rainfall corresponded with a significantly different and more diverse bacterial community in the regulated mainstem. The major contributor to this difference was an increase in relative abundance of bacterial groups with a potential metabolic preference for humic substances (Burkholderiaceae Polynucleobacter, Alcaligenaceae GKS98 freshwater group, Saccharimonadia) and a significant decrease in Spirosomaceae Pseudarcicella, known to metabolise algal exudates. Increases in orthophosphate and river discharge explained 31% of community change, suggesting a combination of resource delivery and microbial community coalescence as major drivers. BCP initially decreased significantly with tributary inflows, but the total load of carbon assimilated by bacteria increased by up to 20 times with flow due to increased water volume. The significant drivers of BCP were dissolved organic carbon, water temperature, and conductivity. Notably, BCP was not correlated with bacterial diversity or community composition. Tributary inflows were shown to alter mainstem bacterial community structure and metabolic function to take advantage of fresh terrestrial dissolved organic material, resulting in substantial changes to riverine carbon assimilation over small times scales.

Decomposing the Institutional Structure of Interstate River Basins Using Institutional Grammar and Institutional Analysis and Development Framework

Rules play a core role in building a water management institution. However, the rules for water resource regulation in subnational interstate river basins remain inadequately explored. Furthermore, a lack of tools for detailed and systematic analysis of these rules hinders water managers from developing better water management strategies. Accordingly, in this paper, we combine institutional grammar and the institutional analysis and development framework’s rule typology to identify the formal rules regulating the water resources of Australia’s Murray-Darling Basin (MDB) and generate insights regarding the characteristics and key actors in the MDB’s institutional structure. Specifically, we study the position, boundary, choice, aggregation, information, scope, and payoff rules that regulate water in different MDB contexts. Overall, the MDB’s institutional structure emphasizes the choice and information rules that control actors’ actions and the availability of information. Aggregation rules, which regulate collective action, are found in every context. Nevertheless, the composition of the identified rules differs across the basin’s contexts, indicating that the focus of the basin’s institutional instrument differs across situations. We further analyze choice and aggregation rules to investigate the basin actors’ roles and interdependencies. The results reveal that decisions concerning administration, water distribution, monitoring, and infrastructure development are made collectively, except with respect to basin plan development, where decision-making is the responsibility of a single actor. Our proposed approach can therefore be used to thoroughly analyze any complex interstate institutional water structure. Overall, our findings foster a comprehensive understanding of the structure of interstate water institutions while facilitating the development of a systematic water institution analysis tool.

A Polanyian Perspective on the Conflict Between Neoliberal Economics and Countrymindedness in Australian Drought and Water Policy

This article evaluates the successes and failures of Australian drought and water policy reforms. By analysing the influence of the ideas central to neoliberal economics and countrymindedness on the development and implementation of the National Drought Policy and the Murray Darling Basin Plan, we illustrate that drought and water policy reforms in Australia can be explained in the context of Karl Polanyi's double movement theory. We demonstrate that founding Australia's agricultural policy on economic assumptions is unlikely to be well‐received in a nation that exhibits widespread sympathy for the plight of agricultural producers. As such, we postulate that neoliberal agricultural policies that ignore the relevant social and historical context will be unpopular and vulnerable to a countermovement that undermines the intent and hinders the implementation of the policy.

How can management of uncertainty in sustainable diversion limits be advanced in the review of the Murray-Darling Basin Plan?

ABSTRACT This paper explores how scientific uncertainty was addressed in the Australian Government’s decision-making process leading to the establishment of the ‘sustainable diversion limit’ (SDL) for the Murray-Darling Basin Plan in 2012. Our research draws on a systematic document analysis to generate an argument map representing the reasoning presented in government reports and legislation, as well as interviews with current and former public servants and researchers who have knowledge of the decision-making process. Looking towards the review of the Basin Plan, this analysis provides additional evidence for a number of areas to be discussed to advance the management of uncertainty in the associated decision-making. First, there is a need to address the challenges to adaptive management, as adaptive management delegates much of the uncertainty to future changes in policy as improved knowledge is gained. Second, there is a need to generate and use new knowledge for the review since the legislative mandate to use the ‘best available science’ enabled the use of pre-existing models and historical climate data. Third, there is a need for dialogue on handling of trade-offs between objectives given that uncertainty creates space for political pressures from interest groups. Fourth, there should be wider transparency about uncertainty in decision-making processes.