Catchments In Queensland Research Articles

CMIP5 Decadal Precipitation over an Australian Catchment

The fidelity of the decadal experiment in Coupled Model Intercomparison Project Phase-5 (CMIP5) has been examined, over different climate variables for multiple temporal and spatial scales, in many previous studies. However, most of the studies were for the temperature and temperature-based climate indices. A quite limited study was conducted on precipitation of decadal experiment, and no attention was paid to the catchment level. This study evaluates the performances of eight GCMs (MIROC4h, EC-EARTH, MRI-CGCM3, MPI-ESM-MR, MPI-ESM-LR, MIROC5, CMCC-CM, and CanCM4) for the monthly hindcast precipitation of decadal experiment over the Brisbane River catchment in Queensland, Australia. First, the GCMs datasets were spatially interpolated onto a spatial resolution of 0.05 × 0.05° (5 × 5 km) matching with the grids of observed data and then were cut for the catchment. Next, model outputs were evaluated for temporal skills, dry and wet periods, and total precipitation (over time and space) based on the observed values. Skill test results revealed that model performances varied over the initialization years and showed comparatively higher scores from the initialization year 1990 and onward. Models with finer spatial resolutions showed comparatively better performances as opposed to the models of coarse spatial resolutions, where MIROC4h outperformed followed by EC-EARTH and MRI-CGCM3. Based on the performances, models were grouped into three categories, where models (MIROC4h, EC-EARTH, and MRI-CGCM3) with high performances fell in the first category, and middle (MPI-ESM-LR and MPI-ESM-MR) and comparatively low-performing models (MIROC5, CanCM4, and CMCC-CM) fell in the second and third categories, respectively. To compare the performances of multi-model ensembles’ mean (MMEMs), three MMEMs were formed. The arithmetic mean of the first category formed MMEM1, the second and third categories formed MMEM2, and all eight models formed MMEM3. The performances of MMEMs were also assessed using the same skill tests, and MMEM2 performed best, which suggests that evaluation of models’ performances is highly important before the formation of MMEM.

Do regenerative grazing management practices improve vegetation and soil health in grazed rangelands? Preliminary insights from a space-for-time study in the Great Barrier Reef catchments, Australia

Regenerative grazing, which generally involves some form of rotational grazing with strategic rest, is increasingly seen as a profitable management approach that will accelerate landscape recovery. However, there is limited quantitative evidence supporting the benefits of this approach in northern Australia. This space-for-time study collected vegetation and soil data from a range of properties in the Burdekin catchment in Queensland that have implemented regenerative grazing strategies for between 5 and 20 years. Data were also collected at adjacent control sites that did not undergo regenerative grazing, but where more traditional continuous set-stocking grazing approaches were applied. Coincident data were also collected from several sites where grazing had been excluded for ~30 years. Data suggested that improvements in vegetation, soil and land condition can be obtained from implementing regenerative grazing principles, although it is likely to take at least 3–5 years, and up to 15–20 years for statistically significant improvements to be measurable at a site, particularly for areas that are moving from a degraded baseline condition. Vegetation attributes such as plant biomass and basal area and litter incorporation all appeared to be better surrogates than percentage ground cover for representing improved landscape condition and soil health. Sites that maintained remotely sensed percentage ground cover at or above the minimally disturbed reference benchmark levels for >10 years, as well as having statistically higher biomass, basal area and litter, had significant increases in total nitrogen (TN) and soil organic carbon (SOC) relative to the local control site. Although there are indications that regenerative grazing can lead to improvements in land condition, this study does not enable us to conclude whether regenerative grazing will accelerate improvements compared with other best-practice grazing land management (GLM) approaches, and further research on the social and economic dimensions of regenerative grazing is needed.

Tidal restoration to reduce greenhouse gas emissions from freshwater impounded coastal wetlands

Freshwater impounded wetlands are created by artificially restricting coastal wetlands connection to tides. The decrease in salinity and altered hydrology can significantly increase greenhouse gas (GHG) emissions, specifically methane (CH4). Restoration of freshwater impounded wetlands through tidal reintroduction can potentially reduce GHG emissions; however, studies in tropical regions are scare. This study investigates the potential for tidal restoration of impounded freshwater coastal wetlands by comparing their GHG emissions with tidally connected mangrove and saltmarshes in the Burdekin catchment in Queensland, Australia. We found that freshwater impounded wetlands had significantly higher CH4 emissions (3,633 ± 812 μg CH4 m−2 hour−1) than mangroves (27 ± 8 μg CH4 m−2 hour−1) and saltmarsh (13 ± 8 μg CH4 m−2 hour−1). Soil redox, moisture, carbon, nitrogen, and bulk density were all significantly correlated to methane emissions. Conversely, freshwater impounded wetlands had significantly lower nitrous oxide (N2O) emissions (−0.72 ± 0.18 μg N2O m−2 hour−1) than mangroves and saltmarsh (0.35 ± 0.29 and 1.32 ± 0.52 μg N2O m−2 hour−1 respectively). Nevertheless, when converting to CO2 equivalents (CO2‐eq), freshwater impounded wetlands emitted 91 ± 20 g CO2‐eq m−2 hour−1, compared to the much lower 0.8 ± 0.2 and 0.7 ± 0.2 g CO2‐eq m−2 hour−1 emission rates for mangroves and saltmarsh. In conclusion, restoration of freshwater impounded wetlands through tidal restoration is likely to result in reduced GHG emissions.

Using Inverse Modeling and Dual Isotopes (δ15N and δ18O of NO3) to Determine Sources of Nitrogen Export From a Complex Land Use Catchment

AbstractAttributing nitrogen export to specific land use within heterogeneous catchments remains a challenge due to the spatio‐temporal variability in conditions influencing the mobilization and fate of nitrogen species. This study demonstrates that the measurement of dual stable isotopes of nitrate, taken along with routine tributary measurement of nitrogen in nitrate (NO3−‐N) and ammonium (NH4+‐N), aids in apportioning sources of the overall nitrogen load during wet periods. An inverse modeling technique was developed to estimate the land use‐specific export rates of NO3−‐N and NH4+‐N from the Caboolture River Catchment in Queensland, Australia. Measurements of nitrogen in streamflow at 51 locations during six sampling campaigns (May 2012 to April 2013) were made along with catchment geospatial data that was used to disaggregate sub‐catchments into six land use fractions. A hydrological model was applied to compute the runoff from each fraction and water routing through the stream network. This data was used within a nitrogen mixing model with inclusion δ15NNO3 and δ18ONO3. The land uses specific export rate was computed inversely as the posterior of a Bayesian interference applied to the model. During higher rainfall periods when export rates were highest, the main land use exporting nitrogen was wetland (110 g/ha/day NO3−‐N, 27 g/ha/day NH4+‐N) resulted from mineralization and nitrification of organic N, followed by urban (16 g/ha/day NO3−‐N, 2.3 g/ha/day NH4+‐N). The advantage of using the dual isotopes in conjunction with the nitrogen concentration data was demonstrated by reduced uncertainty in the computed rates during the higher rainfall periods, relative to calculations without δ15NNO3 and δ18ONO3.

Host-Gut Microbiome Metabolic Interactions in PFAS-Impacted Freshwater Turtles (Emydura macquarii macquarii).

Per-and polyfluoroalkyl substances (PFAS) are a growing concern for humans, wildlife, and more broadly, ecosystem health. Previously, we characterised the microbial and biochemical impact of elevated PFAS on the gut microbiome of freshwater turtles (Emydura macquarii macquarii) within a contaminated catchment in Queensland, Australia. However, the understanding of PFAS impacts on this species and other aquatic organisms is still very limited, especially at the host–gut microbiome molecular interaction level. To this end, the present study aimed to apply these leading-edge omics technologies within an integrated framework that provides biological insight into the host turtle–turtle gut microbiome interactions of PFAS-impacted wild-caught freshwater turtles. For this purpose, faecal samples from PFAS-impacted turtles (n = 5) and suitable PFAS-free reference turtles (n = 5) were collected and analysed. Data from 16S rRNA gene amplicon sequencing and metabolomic profiling of the turtle faeces were integrated using MetOrigin to assign host, microbiome, and co-metabolism activities. Significant variation in microbial composition was observed between the two turtle groups. The PFAS-impacted turtles showed a higher relative abundance of Firmicutes and a lower relative abundance of Bacteroidota than the reference turtles. The faecal metabolome showed several metabolites and pathways significantly affected by PFAS exposure. Turtles exposed to PFAS displayed altered amino acid and butanoate metabolisms, as well as altered purine and pyrimidine metabolism. It is predicted from this study that PFAS-impacted both the metabolism of the host turtle and its gut microbiota which in turn has the potential to influence the host’s physiology and health.

Climate change mitigation discourses in the institutional instruments that shape catchment governance in Queensland, Australia

ABSTRACT Agriculture and Land Use, Land-Use Change and Forestry (LULUCF) sectors account for almost 25 per cent of global greenhouse gas emissions through livestock farming, land clearing, and land use activities such as cropping, changing grassland into settlement or deforestation. The LULUCF is a key sector for carbon sink capacity. Despite desperate need for stronger climate change mitigation efforts, there has been little attention paid to the institutional instruments that govern the mitigation potential of the agriculture and LULUCF sectors in Australia. Using Australia's Lockyer Valley catchment in Queensland as an example, this study investigates the dominant discourses about climate change that are conveyed in the institutional instruments (legislation, policies, strategies, and plans) that apply to catchment scale governance. We employ Bacchi's approach to policy analysis, to understand the dominant discourses, silences, and underlying power dynamics that shape institutional instruments in a catchment setting. The key findings reveal (1) a discourse that is alert to the impacts of climate change while largely ignoring its link to greenhouse gas emissions; (2) a pronounced silence about emissions from agriculture and LULUCF in institutional instruments; and (3) a general development paradigm that couples economic growth with carbon emissions.

Monthly Rainfall Prediction at Catchment Level with the Facebook Prophet Model Using Observed and CMIP5 Decadal Data

Early prediction of rainfall is important for the planning of agriculture, water infrastructure, and other socio-economic developments. The near-term prediction (e.g., 10 years) of hydrologic data is a recent development in GCM (General Circulation Model) simulations, e.g., the CMIP5 (Coupled Modelled Intercomparison Project Phase 5) decadal experiments. The prediction of monthly rainfall on a decadal time scale is an important step for catchment management. Previous studies have considered stochastic models using observed time series data only for rainfall prediction, but no studies have used GCM decadal data together with observed data at the catchment level. This study used the Facebook Prophet (FBP) model and six machine learning (ML) regression algorithms for the prediction of monthly rainfall on a decadal time scale for the Brisbane River catchment in Queensland, Australia. Monthly hindcast decadal precipitation data of eight GCMs (EC-EARTH MIROC4h, MRI-CGCM3, MPI-ESM-LR, MPI-ESM-MR, MIROC5, CanCM4, and CMCC-CM) were downloaded from the CMIP5 data portal, and the observed data were collected from the Australian Bureau of Meteorology. At first, the FBP model was used for predictions based on: (i) the observed data only; and (ii) a combination of observed and CMIP5 decadal data. In the next step, predictions were performed through ML regressions where CMIP5 decadal data were used as features and corresponding observed data were used as target variables. The prediction skills were assessed through several skill tests, including Pearson Correlation Coefficient (PCC), Anomaly Correlation Coefficient (ACC), Index of Agreement (IA), and Mean Absolute Error (MAE). Upon comparing the skills, this study found that predictions based on a combination of observed and CMIP5 decadal data through the FBP model provided better skills than the predictions based on the observed data only. The optimal performance of the FBP model, especially for the dry periods, was mainly due to its multiplicative seasonality function.

Opportunities for coastal wetland restoration for blue carbon with co-benefits for biodiversity, coastal fisheries, and water quality

Coastal wetlands are known to sequester significant amounts of carbon dioxide, while also providing valuable ecosystem services. We assessed the economic feasibility of restoring coastal wetlands for climate change mitigation by reinstating tidal flows on floodplain, agricultural land of the Wet Tropics catchments in Queensland, Australia. We assessed whether potential carbon credits would be sufficient to incentivise conversion of the land, or whether additional ecosystem service payments would be required. We explored the co-benefits for biodiversity, fisheries, and nitrogen removal using a prioritisation approach to identify profitable restoration solutions that maximise these benefits. We identified 5,046 ha of potential restorable area that could abate 221,006 tonnes of carbon dioxide-equivalent (CO2-e) annually from carbon sequestration in vegetation and soils and avoided greenhouse gas emissions. Cost-benefit analysis over 25 years demonstrate that 3,399 ha (67%) would be profitable under conventional farm management practice using the current Australian carbon price ($13.85 per tonne CO2-e), which increased to 4,534 ha (90%) at a higher carbon price ($25 per tonne CO2-e). The profitability of coastal wetland restoration was enhanced by a higher carbon price, which can be achieved by bundling ecosystem services, or through stacking ecosystem service payments. Prioritising restoration sites by cost-effectiveness and co-benefits can achieve multiple ecosystem services for a substantial profit.

Statistical Analysis of Field-Based Stormwater Filtration Performance for the Ecosol Litter Basket

Increasing specificity in water quality regulations for the discharge of stormwater to the environment has increased the requirement to more accurately characterize the performance of filtration interventions. This work presents a statistical performance analysis for the Ecosol Litter Basket, an at source filtration device, based on an extensive field study. The field evaluation of the Ecosol Litter Basket, a primary stormwater filtration device, was performed over a three-year period in an urban catchment in Queensland, Australia. A total of 29 rainfall events were recorded, of which between 13 to 16 events were evaluated as qualifying for the purposes of characterizing the removal efficiency. A variety of pollutant removal evaluation metrics, including concentration-based and total load-based metrics, were utilized in this study to characterize the efficacy of the device for removing a range of pollutants. Two approaches are proposed to facilitate the analysis: a nonlinear regression approach to more effectively deal with nonlinear patterns in the influent and effluent data; and the regression of concentrations (ROC), which is an additional concentration-based metric. A statistical analysis of the results demonstrated that the differences between influent and effluent streams for TSS are significantly different in their mean and median, and the removal efficiency of the Ecosol Litter Basket was evaluated to be 57–65% for TSS with the influent event mean concentration (EMC) up to 142 mg/L.

Stormwater Filtration Performance for the Ecosol Storm Pit (Class 2): Statistical Analysis of Field Data

An independent field performance evaluation for a secondary stormwater filtration device, named the Ecosol Strom Pit (Class 2), was performed between May 2017 and July 2019 in an urban catchment in Queensland, Australia. During the testing period, a total of 37 rainfall events were recorded, of which between 15 and 21 events were evaluated as qualifying for the purposes of characterizing the removal efficiency performance of the device. A statistical analysis of the event mean concentrations (EMCs) of the flow streams through the device indicate a statistically significant difference between the influent and effluent streams. A variety of pollutant removal evaluation metrics, including concentration-based and total load-based metrics, were utilized in this study to characterise the efficacy of the device. Two new approaches are proposed for facilitation the analysis: a nonlinear regression approach to more effectively deal with nonlinear patterns in the influent and effluent data and the regression of concentration (ROC), which is an added concentration-based metrics. In summary, the removal efficiencies of the Ecosol Storm Pit (Class 2) were evaluated to be 72–74% for total suspended solids (TSS), 45–50% for total phosphorus (TP), 41–45% for total nitrogen (TN), 27–32% for total heavy metals (THM), 79–85% for total petroleum hydrocarbons (TPH), and 80–88% for total recoverable hydrocarbons (TRH).

An evaluation of a multi-day rainfall – runoff volume – peak discharge transform for flood frequency estimation

ABSTRACT A new method to estimate design discharge quantiles is described based on converting multi-day rainfall P to flood event runoff RO, factored to generate discharge Q. The so-called PROQ transfer function is founded on simple flood volume-peak and GRADEX rainfall-runoff tanh relationships. Performance testing of PROQ, in both at-site and regional design flood contexts up to 1 in 100 annual exceedance probability, was made using south east Queensland streamgauge data. A statistical comparison against proven methods showed that the PROQ transform has significant potential as an alternative for design flood estimation. An example of how PROQ can be used within a design flood framework and recommendations for further enhancement are provided. Abbreviations: AEP: Annual exceedance probability; AMS: Annual maximum series, extracted from the flood record at a gauge site; ANOVA: Analysis of variance; ARR: Australian Rainfall and Runoff guidelines; A-S: At-site. Describes a set of methods to estimate design flood quantiles by statistical analysis of the flood record at an individual gauge site; E: Nash–Sutcliffe efficiency; FFA: Flood frequency analysis; G-B: Multiple Grubbs-Beck test recommended by ARR 2019 for low flow censoring. Used for at-site flood frequency analysis; GEV: General extreme value probability distribution; GRADEX: Gradient of extreme values. Design flood probability concept originating in France based on parallelism of rainfall and runoff quantile curves; L: Retention of rainfall within the catchment during flood event, expressed as a depth; LP3: Log Pearson 3 probability distribution; P: Rainfall depth; PRM: Probabilistic Rational Method. An ARR method for ungauged, undeveloped Australian catchments superseded in 2016; PROQ: Transfer function based on converting P to RO and then factoring RO to estimate Q; PW: Palmen and Weeks. Regional method for ungauged, undeveloped Queensland catchments developed by Palmen and Weeks (2011); R: Retention curve number. Used in probabilistic charting of design floods based on PROQ; RE: Absolute relative error; REG: Regional. Describes a set of methods to estimate design flood quantiles using information obtained from at-site analyses of several representative catchments within a region; RO: Flood event runoff depth; SR30: Strike rate of estimates within ±30% tolerance.

Validation of the Primary Care Pathway Model for Management of Orthopedic Injuries: Results of a Prospective, Queensland Study.

Objective:A “virtual fracture clinic” (VFC) is viewed as a safe, cost effective method of managing suitable low risk orthopedic injuries without direct orthopedic review. This method is used throughout the Glasgow Royal Infirmary (GRI) and National Health System (NHS) as a cornerstone for efficient patient care. This study assessed the outcomes of a newly implemented Queensland based Primary Care Pathway (PCP) for management of simple orthopedic injuries.Methods:A prospective cohort was formed of patients presenting over a 4-week period with an acute orthopedic injury to either the Emergency Department (ED) or Primary Care Providers within the Logan Hospital catchment in Queensland, Australia. Patients were triaged to either a PCP management protocol with General Practitioners (GP), Allied-Health Professionals (AHP) or to a traditional in-person Fracture Clinic (FC) orthopedic review. Patients were followed for 6-months. Data were collected about epidemiology, complications, appropriate allocation, and injury type.Results:A total of 1283 patients were referred over the study period, of which 267 were triaged to PCP management. ED referrals accounted for 62.5% of appropriate referrals to either clinic. Upper limb injuries were the most common conditions managed through the PCP. Patients managed by the PCP model of care experienced a 4.29% complication rate over the 6-month follow-up period.Conclusion:The PCP model of care is effective in managing criteria specific, low risk orthopedic injuries with a low rate of complications (4.29%) without direct orthopedic FC review. Use of a PCP reduces demand on hospital resources, and provides a safe, cost-effective alternative to a resource-restricted outpatient service.

Settling for dams?: planning for sustainable Indigenous livelihoods within large-scale irrigated agricultural development in north Queensland, Australia

Large-scale irrigated production of food, fuel and fibre has received new impetus from rising population and consumption levels and from structural changes in agribusiness, notably financialisation and vertical and horizontal consolidation. In Australia, these trends have provided new justifications for pre-existing economic and nationalist aspirations for water and irrigated agricultural development in the pastoral-dominated tropical north. Indigenous Australians have the longest history of past attachment to northern land and waterscapes, the highest degree of current socioeconomic marginalisation, and the strongest focus on the intergenerational equity and sustainability of development. This qualitative study undertaken with senior Indigenous custodians in two North Queensland catchments identified that major irrigation development posed significant risks, but may also contribute to diversified local Indigenous livelihoods. In particular, well structured development may enable the employment-related resettlement of depopulated traditional lands in the upper catchments, inverting the more commonly reported relationship between dam development and local residence. Yet the catchment-scale impacts from such development means that any complementarity between local Indigenous and developer aspirations in the immediate development zone does not necessarily entail complementarity with downstream Indigenous livelihood needs and aspirations. Regional coordination of Indigenous livelihood plans is required to establish effective baselines for negotiating sustainable development outcomes.

MANAGEMENT EFFECTS ON GROUND COVER CLUMPINESS: SCALING FROM FIELD TO SENTINEL-2 COVER ESTIMATES

Abstract. Significant progress has been made in the development of cover data and derived products based on remotely sensed fractional cover information and field data across Australia, and these cover data sets are now used for quantifying and monitoring grazing land condition. The availability of a dense time-series of nearly 30 years of cover data to describe the spatial and temporal patterns in landscape changes over time can help with monitoring the effectiveness of grazing land management practice change. With the advent of higher spatial resolution data, such as that provided by the Copernicus Sentinel 2 series of satellites, we can look beyond reporting purely on cover amount and more closely at the operational monitoring and reporting on spatial arrangement of cover and its links with land condition. We collected high spatial resolution cover transects at 20 cm intervals over the Wambiana grazing trials in the Burdekin catchment in Queensland, Australia. Spatial variance analysis was used to determine the cover autocorrelation at various support intervals. Coincident Sentinel-2 imagery was collected and processed over all the sites providing imagery to link with the field data. We show that the spatial arrangement and temporal dynamics of cover are important indicators of grazing land condition for both productivity and water quality outcomes. The metrics and products derived from this research will assist land managers to prioritize investment and practice change strategies for long term sustainability and improved water quality, particularly in the Great Barrier Reef catchments.

Dynamics of sediment carbon stocks across intertidal wetland habitats of Moreton Bay, Australia.

Coastal wetlands are known for high carbon storage within their sediments, but our understanding of the variation in carbon storage among intertidal habitats, particularly over geomorphological settings and along elevation gradients, is limited. Here, we collected 352 cores from 18 sites across Moreton Bay, Australia. We assessed variation in sediment organic carbon (OC) stocks among different geomorphological settings (wetlands within riverine settings along with those with reduced riverine influence located on tide-dominated sand islands), across elevation gradients, with distance from shore and among habitat and vegetation types. We used mid-infrared (MIR) spectroscopy combined with analytical data and partial least squares regression to quantify the carbon content of ~2500 sediment samples and provide fine-scale spatial coverage of sediment OC stocks to 150cm depth. We found sites in river deltas had larger OC stocks (175-504 Mg/ha) than those in nonriverine settings (44-271 Mg/ha). Variation in OC stocks among nonriverine sites was high in comparison with riverine and mixed geomorphic settings, with sites closer to riverine outflow from the east and south of Moreton Bay having higher stocks than those located on the sand islands in the northwest of the bay. Sediment OC stocks increased with elevation within nonriverine settings, but not in riverine geomorphic settings. Sediment OC stocks did not differ between mangrove and saltmarsh habitats. OC stocks did, however, differ between dominant species across the research area and within geomorphic settings. At the landscape scale, the coastal wetlands of the South East Queensland catchments (17,792ha) are comprised of approximately 4,100,000-5,200,000 Mg of sediment OC. Comparatively high variation in OC storage between riverine and nonriverine geomorphic settings indicates that the availability of mineral sediments and terrestrial derived OC may exert a strong influence over OC storage potential across intertidal wetland systems.

Global transcriptomic profiling in barramundi (Lates calcarifer) from rivers impacted by differing agricultural land uses.

Most catchments discharging into the Great Barrier Reef lagoon have elevated loads of suspended sediment, nutrients, and pesticides, including photosystem II inhibiting herbicides, associated with upstream agricultural land use. To investigate potential impacts of declining water quality on fish physiology, RNA sequencing (RNASeq) was used to characterize and compare the hepatic transcriptomes of barramundi (Lates calcarifer) captured from 2 of these tropical river catchments in Queensland, Australia. The Daintree and Tully Rivers differ in upstream land uses, as well as sediment, nutrient, and pesticide loads, with the area of agricultural land use and contaminant loads lower in the Daintree. In fish collected from the Tully River, transcripts involved in fatty acid metabolism, amino acid metabolism, and citrate cycling were also more abundant, suggesting elevated circulating cortisol concentrations, whereas transcripts involved in immune responses were less abundant. Fish from the Tully also had an increased abundance of transcripts associated with xenobiotic metabolism. Previous laboratory-based studies observed similar patterns in fish and amphibians exposed to the agricultural herbicide atrazine. If these transcriptomic patterns are manifested at the whole organism level, the differences in water quality between the 2 rivers may alter fish growth and fitness. Environ Toxicol Chem 2017;36:103-112. © 2016 SETAC.

Spatio-temporal assimilation of modelled catchment loads with monitoring data in the Great Barrier Reef

Soil erosion and sediment transport into waterways and the ocean can adversely affect water clarity, leading to the deterioration of marine ecosystems such as the iconic Great Barrier Reef (GBR) in Australia. Quantifying a sediment load and its associated uncertainty is an important task in delineating how changes in management practices can contribute to improvements in water quality, and therefore continued sustainability of the GBR. However, monitoring data are spatially (and often temporally) sparse, making load estimation complicated, particularly when there are lengthy periods between sampling or during peak flow periods of major events when samples cannot be safely taken. We develop a spatio-temporal statistical model that is mechanistically motivated by a process-based deterministic model called Dynamic SedNet. The model is developed within a Bayesian hierarchical modelling framework that uses dimension reduction to accommodate seasonal and spatial patterns to assimilate monitored sediment concentration and flow data with output from Dynamic SedNet. The approach is applied in the Upper Burdekin catchment in Queensland, Australia, where we obtain daily estimates of sediment concentrations, stream discharge volumes and sediment loads at 411 spatial locations across 20 years. Our approach provides a method for assimilating both monitoring data and modelled output, providing a statistically rigorous method for quantifying uncertainty through space and time that was previously unavailable through process-based models.

Monitoring temporal changes in use of two cathinones in a large urban catchment in Queensland, Australia

Wastewater analysis was used to examine prevalence and temporal trends in the use of two cathinones, methylone and mephedrone, in an urban population (>200,000 people) in South East Queensland, Australia. Wastewater samples were collected from the inlet of the sewage treatment plant that serviced the catchment from 2011 to 2013. Liquid chromatography coupled with tandem mass spectrometry was used to measure mephedrone and methylone in wastewater sample using direct injection mode. Mephedrone was not detected in any samples while methylone was detected in 45% of the samples. Daily mass loads of methylone were normalized to the population and used to evaluate methylone use in the catchment. Methylone mass loads peaked in 2012 but there was no clear temporal trend over the monitoring period. The prevalence of methylone use in the catchment was associated with the use of MDMA, the more popular analogue of methylone, as indicated by other complementary sources. Methylone use was stable in the study catchment during the monitoring period whereas mephedrone use has been declining after its peak in 2010. More research is needed on the pharmacokinetics of emerging illicit drugs to improve the applicability of wastewater analysis in monitoring their use in the population.

Modeling residual hydrologic errors with Bayesian inference

Hydrologic modelers are confronted with the challenge of producing estimates of the uncertainty associated with model predictions across an array of catchments and hydrologic flow regimes. Formal Bayesian approaches are commonly employed for parameter calibration and uncertainty analysis, but are often criticized for making strong assumptions about the nature of model residuals via the likelihood function that may not be well satisfied (or even checked). This technical note outlines a residual error model (likelihood function) specification framework that aims to provide guidance for the application of more appropriate residual error models through a nested approach that is both flexible and extendible. The framework synthesizes many previously employed residual error models and has been applied to four synthetic datasets (of differing error structure) and a real dataset from the Black River catchment in Queensland, Australia. Each residual error model was investigated and assessed under a top-down approach focused on its ability to properly characterize the errors. The results of these test applications indicate that a multifaceted assessment strategy is necessary to determine the adequacy of an individual likelihood function.

An examination of geochemical modelling approaches to tracing sediment sources incorporating distribution mixing and elemental correlations

AbstractThe identification of sediment sources is fundamental to the management of increasingly scarce water resources. Tracing the origin of sediment with elemental geochemistry is a well‐established approach to determining sediment provenance. Fundamental to the confident apportionment of sediment to their lithogenic sources is the modelling process. Recent approaches have incorporated distributions throughout the modelling process including source contribution terms for two end‐member sources. The shift from modelling source samples to modelling samples drawn from distributions has removed relationships, including potential correlations between elemental concentrations, from the modelling process. Here, we present a novel modelling approach that re‐incorporates correlations between elemental concentrations and models distributions for source contribution terms for multiple source end members. Artificial mixtures, based on catchment sources samples, were created to test the accuracy of this correlated distribution model and also examine modelling approaches used in the literature. The most accurate model incorporates correlations between elements, uses the absolute mixing model difference and does not use any weighting. This model was then applied to identify the sources of sediment in three South East Queensland catchments and demonstrated that Quaternary Alluvium is the most dominant source of sediment in these catchments (μ 44%, σ 12%). This study demonstrates that it is important to understand how different weightings may impact modelling results. Copyright © 2014 John Wiley & Sons, Ltd.