The Cressbrook Creek alluvial aquifer system, Southeast Queensland : hydrochemistry and isotopes to determine hydrological processes and response to floods

This study developed an understanding of hydrological processes within the Cressbrook Creek catchment of the upper Brisbane River, in particular for the alluvial aquifers. Those aquifers within the lower catchment are used for intensive irrigation, and have been impacted by long-term drought followed by flooding. The study utilised water chemistry, isotopic characters and hydraulic measurements to determine factors such as recharge, links between creeks and groundwater, and variations in water quality. The catchment-wide study will enable improved management of the local water resources.

Process variability of pollutant build-up on urban road surfaces

Knowledge of the pollutant build-up process is a key requirement for developing stormwater pollution mitigation strategies. In this context, process variability is a concept which needs to be understood in-depth. Analysis of particulate build-up on three road surfaces in an urban catchment confirmed that particles <150µm and >150µm have characteristically different build-up patterns, and these patterns are consistent over different field conditions. Three theoretical build-up patterns were developed based on the size-fractionated particulate build-up patterns, and these patterns explain the variability in particle behavior and the variation in particle-bound pollutant load and composition over the antecedent dry period. Behavioral variability of particles <150µm was found to exert the most significant influence on the build-up process variability. As characterization of process variability is particularly important in stormwater quality modeling, it is recommended that the influence of behavioral variability of particles <150µm on pollutant build-up should be specifically addressed. This would eliminate model deficiencies in the replication of the build-up process and facilitate the accounting of the inherent process uncertainty, and thereby enhance the water quality predictions.

Mid-Holocene Aboriginal occupation of offshore islands in northern Australia? A reassessment of Wurdukanhan, Mornington Island, southern Gulf of Carpentaria, Australia

Claims for mid-Holocene Aboriginal occupation at the shell matrix site of Wurdukanhan, Mornington Island, Gulf of Carpentaria, Australia, are reassessed through an analysis of the excavated assemblage coupled with new surveys and an extensive dating program. Memmott et al. (2006, pp. 38, 39) reported basal ages of c.5000–5500 years from Wurdukanhan as 'the oldest date yet obtained for any archaeological site on the coast of the southern Gulf of Carpentaria' and used these dates to argue for 'a relatively lengthy occupation since at least the mid-Holocene'. If substantiated, with the exception of western Torres Strait, these claims make Mornington Island the only offshore island used across northern Australia in the mid-Holocene where it is conventionally thought that Aboriginal people only (re)colonised islands after sea-level maximum was achieved after the mid-Holocene. Our analysis of Wurdukanhan demonstrates high shellfish taxa diversity, high rates of natural shell predation and high densities of foraminifera throughout the deposit demonstrating a natural origin for the assemblage. Results are considered in the context of other dated shell matrix sites in the area and a geomorphological model for landscape development of the Sandalwood River catchment.

Phylogeography of two freshwater prawn species from far-northern Queensland

The distribution of a freshwater species is often dependent on its ability to disperse within the riverine system. Species with high dispersal abilities tend to be widespread, whereas those with restricted dispersal tend to be geographically restricted and are usually given higher conservation priority. Population structure was compared between a widespread freshwater prawn species, Macrobrachium australiense, and a narrow-range endemic freshwater prawn, Macrobrachium koombooloomba. The distribution of M. australiense and M. koombooloomba did not overlap, although suggested historical river-boundary rearrangements indicate that there has been the potential for dispersal into neighbouring catchments. A fragment of the mtDNA CO1 gene was analysed and a Mantel test revealed a significant isolation by distance effect for both species. Significant overall FST values confirmed that both species exhibited low levels of dispersal, a prediction for populations inhabiting a fragmented upland environment. The level of structure in M. australiense is surprising for a widely distributed species. Not all M. australiense populations conformed to the stream-hierarchy model, with results being best explained by historical river realignment or cross-catchment dispersal. The fact that both species show limited dispersal highlights the importance of conservation in highland areas for both endemic and widely spread species.

An analysis of ethical issues in using wastewater analysis to monitor illicit drug use

Aims To discuss ethical issues that may arise in using WWA to monitor illicit drug use in the general population and in entertainment precincts, prisons, schools and work-places. Method Review current applications of WWA and identify ethical and social issues that may be raised with current and projected future uses of this method. Results Wastewater analysis (WWA) of drug residues is a promising method of monitoring illicit drug use that may overcome some limitations of other monitoring methods. When used for monitoring purposes in large populations, WWA does not raise major ethical concerns because individuals are not identified and the prospects of harming residents of catchment areas are remote. When WWA is used in smaller catchment areas (entertainment venues, prisons, schools or work-places) their results could, possibly, indirectly affect the occupants adversely. Researchers will need to take care in reporting their results to reduce media misreporting. Fears about possible use of WWA for mass individual surveillance by drug law enforcement officials are unlikely to be realized, but will need to be addressed because they may affect public support adversely for this type of research. Conclusions Using wastewater analysis to monitor illicit drug use in large populations does not raise major ethical concerns, but researchers need to minimize possible adverse consequences in studying smaller populations, such as workers, prisoners and students.

Monitoring illicit drug use through wastewater analysis in south east Queensland, Australia

Introduction and Aims: Wastewater analysis has become a useful technique for monitoring illicit drug use in communities. Findings have been reported from different countries in Europe and North America. We applied this technique to gauge the illicit drug consumption in an urban catchment from South East Queensland, Australia. Design and Methods: The sampling campaigns were conducted in 2009 (21st November – 2nd December) and 2010 (19th – 25th November). We collected daily composite wastewater samples from the inlet of the sewage treatment plant using continuous flow-proportional sampling. Ten illicit drug residues (parent compounds and key metabolites) in the samples were measured using liquid chromatography coupled to tandem mass spectrometer. Results: Seven compounds were quantified in all the samples. Our data indicated higher drug consumption on weekends. Cannabis was the highest used drug in both sampling periods. Compared to the first sampling campaign which indicated that cocaine and methamphetamine use exceeded ecstasy usage, the second sampling campaign suggested the use of methamphetamine exceeded that of ecstasy which in turn exceeded cocaine use. Discussion and Conclusions: The observed weekly trend of drug use in our study is in agreement with findings in other studies. The variation between two sampling periods in the prevalence of drug use may relate to the availability and prices of the drugs on markets. The cocaine use we estimated in 2009 was much greater than estimations obtained through the national household survey [1], implying under- reporting of cocaine use in surveys. Future work is underway to tackle methodological challenges for more accurate estimation.

Systematic and Day-to-Day Effects of Chemical-Derived Population Estimates on Wastewater-Based Drug Epidemiology

Population size is crucial when estimating population-normalized drug consumption (PNDC) from wastewater-based drug epidemiology (WBDE). Three conceptually different population estimates can be used: de jure (common census, residence), de facto (all persons within a sewer catchment), and chemical loads (contributors to the sampled wastewater). De facto and chemical loads will be the same where all households contribute to a central sewer system without wastewater loss. This study explored the feasibility of determining a de facto population and its effect on estimating PNDC in an urban community over an extended period. Drugs and other chemicals were analyzed in 311 daily composite wastewater samples. The daily estimated de facto population (using chemical loads) was on average 32% higher than the de jure population. Consequently, using the latter would systemically overestimate PNDC by 22%. However, the relative day-to-day pattern of drug consumption was similar regardless of the type of normalization as daily illicit drug loads appeared to vary substantially more than the population. Using chemical loads population, we objectively quantified the total methodological uncertainty of PNDC and reduced it by a factor of 2. Our study illustrated the potential benefits of using chemical loads population for obtaining more robust PNDC data in WBDE.

A Model to Estimate the Population Contributing to the Wastewater Using Samples Collected on Census Day

An important uncertainty when estimating per capita consumption of, for example, illicit drugs by means of wastewater analysis (sometimes referred to as “sewage epidemiology”) relates to the size and variability of the de facto population in the catchment of interest. In the absence of a day-specific direct population count any indirect surrogate model to estimate population size lacks a standard to assess associated uncertainties. Therefore, the objective of this study was to collect wastewater samples at a unique opportunity, that is, on a census day, as a basis for a model to estimate the number of people contributing to a given wastewater sample. Mass loads for a wide range of pharmaceuticals and personal care products were quantified in influents of ten sewage treatment plants (STP) serving populations ranging from approximately 3500 to 500 000 people. Separate linear models for population size were estimated with the mass loads of the different chemical as the explanatory variable: 14 chemicals showed good, linear relationships, with highest correlations for acesulfame and gabapentin. De facto population was then estimated through Bayesian inference, by updating the population size provided by STP staff (prior knowledge) with measured chemical mass loads. Cross validation showed that large populations can be estimated fairly accurately with a few chemical mass loads quantified from 24-h composite samples. In contrast, the prior knowledge for small population sizes cannot be improved substantially despite the information of multiple chemical mass loads. In the future, observations other than chemical mass loads may improve this deficit, since Bayesian inference allows including any kind of information relating to population size.

Could wastewater analysis be a useful tool for China? — A review

Analysing wastewater samples is an innovative approach that overcomes many limitations of traditional surveys to identify and measure a range of chemicals that were consumed by or exposed to people living in a sewer catchment area. First conceptualised in 2001, much progress has been made to make wastewater analysis (WWA) a reliable and robust tool for measuring chemical consumption and/or exposure. At the moment, the most popular application of WWA, sometimes referred as sewage epidemiology, is to monitor the consumption of illicit drugs in communities around the globe, including China. The approach has been largely adopted by law enforcement agencies as a device to monitor the temporal and geographical patterns of drug consumption. In the future, the methodology can be extended to other chemicals including biomarkers of population health (e.g. environmental or oxidative stress biomarkers, lifestyle indicators or medications that are taken by different demographic groups) and pollutants that people are exposed to (e.g. polycyclic aromatic hydrocarbons, perfluorinated chemicals, and toxic pesticides). The extension of WWA to a huge range of chemicals may give rise to a field called sewage chemical-information mining (SCIM) with unexplored potentials. China has many densely populated cities with thousands of sewage treatment plants which are favourable for applying WWA/SCIM in order to help relevant authorities gather information about illicit drug consumption and population health status. However, there are some prerequisites and uncertainties of the methodology that should be addressed for SCIM to reach its full potential in China.

Degradability of creatinine under sewer conditions affects its potential to be used as biomarker in sewage epidemiology

Creatinine was proposed to be used as a population normalising factor in sewage epidemiology but its stability in the sewer system has not been assessed. This study thus aimed to evaluate the fate of creatinine under different sewer conditions using laboratory sewer reactors. The results showed that while creatinine was stable in wastewater only, it degraded quickly in reactors with the presence of sewer biofilms. The degradation followed first order kinetics with significantly higher rate in rising main condition than in gravity sewer condition. Additionally, daily loads of creatinine were determined in wastewater samples collected on Census day from 10 wastewater treatment plants around Australia. The measured loads of creatinine from those samples were much lower than expected and did not correlate with the populations across the sampled treatment plants. The results suggested that creatinine may not be a suitable biomarker for population normalisation purpose in sewage epidemiology, especially in sewer catchment with high percentage of rising mains.

Role of predictors in downscaling surface temperature to river basin in India for IPCC SRES scenarios using support vector machine

In this paper, downscaling models are developed using a support vector machine (SVM) for obtaining projections of monthly mean maximum and minimum temperatures (T-max and T-min) to river-basin scale. The effectiveness of the model is demonstrated through application to downscale the predictands for the catchment of the Malaprabha reservoir in India, which is considered to be a climatically sensitive region. The probable predictor variables are extracted from (1) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1978-2000, and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 1978-2100. The predictor variables are classified into three groups, namely A, B and C. Large-scale atmospheric variables Such as air temperature, zonal and meridional wind velocities at 925 nib which are often used for downscaling temperature are considered as predictors in Group A. Surface flux variables such as latent heat (LH), sensible heat, shortwave radiation and longwave radiation fluxes, which control temperature of the Earth's surface are tried as plausible predictors in Group B. Group C comprises of all the predictor variables in both the Groups A and B. The scatter plots and cross-correlations are used for verifying the reliability of the simulation of the predictor variables by the CGCM3 and to Study the predictor-predictand relationships. The impact of trend in predictor variables on downscaled temperature was studied. The predictor, air temperature at 925 mb showed an increasing trend, while the rest of the predictors showed no trend. The performance of the SVM models that are developed, one for each combination of predictor group, predictand, calibration period and location-based stratification (land, land and ocean) of climate variables, was evaluated. In general, the models which use predictor variables pertaining to land surface improved the performance of SVM models for downscaling T-max and T-min

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Assessing the cost-effectiveness of water quality interventions in South-East Queensland

The focus of this article is on the cost-effectiveness of mitigation strategies to reduce pollution loads and improve water quality in South-East Queensland. Scenarios were developed about the types of catchment interventions that could be considered, and the resulting changes in water quality indicators that may result. Once these catchment scenarios were modelled, the range of expected outcomes was assessed and the costs of mitigation interventions were estimated. Strategies considered include point and non-point source interventions. Predicted reductions in pollution levels were calculated for each action based on the expected population growth. The cost of the interventions included the full investment and annual running costs as well as planned public investment by the state agencies. Cost-effectiveness of strategies is likely to vary according to whether suspended sediments, nitrogen or phosphorus loads are being targeted.

Sediment and nutrient losses from exotic Pinus plantation management operations under simulated rainfall

Rainfall simulation experiments were carried out to measure runoff and soil water fluxes of suspended solids, total nitrogen, total phosphorus, dissolved organic carbon and total iron from sites in Pinus plantations on the coastal lowlands of south-eastern Queensland subjected to various operations (treatments). The operations investigated were cultivated and nil-cultivated site preparation, fertilised site preparation, clearfall harvesting and prescribed burning; these treatments were compared with an 8-y-old established plantation. Flow-weighted mean concentrations of total nitrogen and total phosphorus in surface runoff from the cultivated and nil-cultivated site-preparation, clearfall harvest, prescribed burning and 8-y-old established plantation treatments were very similar. However, both the soil water and the runoff from the fertilised site preparation treatment contained more nitrogen (N) and phosphorus (P) than the other treatments - with 3.10 mg N L-1 and 4.32 mg P L-1 (4 and 20 times more) in the runoff. Dissolved organic carbon concentrations in runoff from the nil-cultivated site-preparation and prescribed burn treatments were elevated. Iron concentrations were highest in runoff from the nil-cultivated site-preparation and 8-y-old established plantation treatments. Concentrations of suspended solids in runoff were higher from cultivated site preparation and prescribed burn treatments, and reflect the great disturbance of surface soil at these sites. The concentrations of all analytes were highest in initial runoff from plots, and generally decreased with time. Total nitrogen (mean 7.28, range 0.11-13.27 mg L-1) and total phosphorus (mean 11.60, range 0.06-83.99 mg L-1) concentrations in soil water were between 2 and 10 times greater than in surface runoff, which highlights the potential for nutrient fluxes in interflow (i.e. in the soil above the water table) through the general plantation area. Implications in regard to forest management are discussed, along with results of larger catchment-scale studies.