Constraining the response of continental-scale groundwater flow to climate change.

Numerical models of groundwater flow play a critical role for water management scenarios under climate extremes. Large-scale models play a key role in determining long range flow pathways from continental interiors to the oceans, yet struggle to simulate the local flow patterns offered by small-scale models. We have developed a highly scalable numerical framework to model continental groundwater flow which capture the intricate flow pathways between deep aquifers and the near-surface. The coupled thermal-hydraulic basin structure is inferred from hydraulic head measurements, recharge estimates from geochemical proxies, and borehole temperature data using a Bayesian framework. We use it to model the deep groundwater flow beneath the Sydney-Gunnedah-Bowen Basin, part of Australia's largest aquifer system. Coastal aquifers have flow rates of up to 0.3 m/day, and a corresponding groundwater residence time of just 2,000 years. In contrast, our model predicts slow flow rates of 0.005 m/day for inland aquifers, resulting in a groundwater residence time of [Formula: see text] 400,000 years. Perturbing the model to account for a drop in borehole water levels since 2000, we find that lengthened inland flow pathways depart significantly from pre-2000 streamlines as groundwater is drawn further from recharge zones in a drying climate. Our results illustrate that progressively increasing water extraction from inland aquifers may permanently alter long-range flow pathways. Our open-source modelling approach can be extended to any basin and may help inform policies on the sustainable management of groundwater.

Space-time modelling of groundwater level and salinity.

Soil salinization resulting from shallow saline groundwater is a major global environmental issue causing land degradation, especially in semi-arid regions such as Australia. The adverse impact of shallow saline groundwater on soil salinization varies in space and time due to the variation in groundwater levels and salt concentration. Understanding the spatio-temporal variation is therefore vital to develop an effective salinity management strategy. In New South Wales, Australia, a hydrogeological landscape unit approach is generally applied, based on spatial information and expert operators, classifying the landscape in relation to landscape and climate. In this paper, a data science approach (random forest model) is introduced, based on historical groundwater quality and quantity data providing predictions in a 4-dimensional space. As a case study, we demonstrate the spatio-temporal factors impacting standing water levels (SWL) and associated salinity and predict the spatial and temporal variability in the Muttama catchment (1059 km2), in NSW, south eastern Australia. The random forest model explains 77% of the variance in the groundwater salinity (electrical conductivity) and 65% of the SWL. Spatial factors were the most significant variables determining the space-time variation in groundwater salinity and the occurrence of groundwater at the surface. Drilled piezometer depth and elevation are dominant factors controlling SWL, while salinity is mainly determined by underlying geology. The methodology in this study predicts salinity and SWL in the landscape at fine scales, through time, improving options for salinity management.

Biodegradation and Abiotic Degradation of Trifluralin: A Commonly Used Herbicide with a Poorly Understood Environmental Fate.

Trifluralin is a widely used dinitroaniline herbicide, which can persist in the environment and has substantial ecotoxicity, especially to aquatic organisms. Trifluralin is very insoluble in water (0.22 mg/L at 20 °C) and highly volatile (vapor pressure of 6.7 mPa at 20 °C); these physicochemical properties determine a large part of its environmental fate, which includes rapid loss from soils if surface-applied, strong binding to soil organic matter, and negligible leaching into water. The trifluralin structure contains a tertiary amino group, two nitro-groups and a trifluoromethyl- group. Despite the strongly xenobiotic character of some of these substituents, biodegradation of trifluralin does occur, and pure cultures of bacteria and fungi capable of partially degrading the molecule either by dealkylation or nitro-group reduction have been identified. There are many unanswered questions about the environmental fate and metabolism of this herbicide; the genes and enzymes responsible for biodegradation are largely unknown, the relative roles of abiotic processes vs growth-linked biodegradation vs cometabolism are unresolved, and the impact of different environmental factors on the rates and extents of biodegradation are not clear. Here, we summarize the relevant literature on the persistence and environmental fate of trifluralin with a focus on biodegradation pathways and mechanisms, and we identify the current major knowledge gaps for future research.

Detecting the impact of land cover change on observed rainfall.

Analysis of observational data to pinpoint impact of land cover change on local rainfall is difficult due to multiple environmental factors that cannot be strictly controlled. In this study we use a statistical approach to identify the relationship between removal of tree cover and rainfall with data from best available sources for two large areas in Australia. Gridded rainfall data between 1979 and 2015 was used for the areas, while large scale (exogenous) effects were represented by mean rainfall across a much larger area and climatic indicators, such as Southern Oscillation Index and Indian Ocean Dipole. Both generalised additive modelling and step trend tests were used for the analysis. For a region in south central Queensland, the reported change in tree clearing between 2002-2005 did not result in strong statistically significant precipitation changes. On the other hand, results from a bushfire affected region on the border of New South Wales and Victoria suggest significant changes in the rainfall due to changes in tree cover. This indicates the method works better when an abrupt change in the data can be clearly identified. The results from the step trend test also mainly identified a positive relationship between the tree cover and the rainfall at p < 0.1 at the NSW/Victoria region. High rainfall variability and possible regrowth could have impacted the results in the Queensland region.

Microcosm experiments and kinetic modeling of glyphosate biodegradation in soils and sediments.

Glyphosate (GLP) is one of the most widely-used herbicides globally and its toxicity to humans and the environment is controversial. GLP is biodegradable, but little is known about the importance of site exposure history and other environmental variables on the rate and pathway of biodegradation. Here, GLP was added to microcosms of soils and sediments with different exposure histories and these were incubated with amendments of glucose, ammonium, and phosphate. GLP concentrations were measured with a newly-developed HPLC method capable of tolerating high concentrations of ammonium and amino acids. GLP biodegradation occurred after a lag-time proportional to the level of GLP pre-exposure in anthropogenically-impacted samples (soils and sediments), while no degradation occurred in samples from a pristine sediment after 180 days of incubation. Exposure history did not influence the rate of GLP degradation, after the lag-time was elapsed. Addition of C, N, and P triggered GLP degradation in pristine sediment and shortened the lag-time before degradation in other samples. In all microcosms, GLP was metabolised into aminomethylphosphonic acid (AMPA), which was highly persistent, and thus appears to be a more problematic pollutant than GLP. Bacterial communities changed along the gradients of anthropogenic impacts, but in some cases, taxonomically very-similar communities showed dramatically different activities with GLP. Our findings reveal important interactions between agriculturally-relevant nutrients and herbicides.

Glyphosate dispersion, degradation, and aquifer contamination in vineyards and wheat fields in the Po Valley, Italy.

Biodegradation of glyphosate (GLP) and its metabolite aminomethylphosphonic acid (AMPA) was numerically assessed for a vineyard and a wheat field in the Po Valley, Italy. Calculation of the Hazard Quotient suggested that GLP and AMPA can pose a risk of aquifer contamination in the top 1.5 m depth within 50 years of GLP use. Numerical results relative to soil GLP and AMPA concentrations, and GLP age, half life, and turnover time show that GLP was equivalently removed through hydrolysis and oxidation, but the latter produced AMPA. Biodegradation processes in the root zone removed more than 90% of applied GLP and more than 23% of the produced AMPA between two consecutive applications. Doubling organic carbon availability enhanced GLP and AMPA biodegradation, especially GLP hydrolysis to sarcosine. This work highlights that GLP and AMPA removal is controlled by soil water dynamics that depend on ecohydrological boundary conditions, and by carbon sources availability to biodegraders.

Can a growth model be used to describe forest carbon and water balance after fuel reduction burning in temperate forests?

Empirical evidence from Australia shows that fuel reduction burning significantly reduces the incidence and extent of unplanned fires. However, the integration of environmental values into fire management operations is not yet well-defined and requires further research and development. WAVES, a plant growth model that incorporates Soil-Vegetation-Atmosphere Transfer, was used to simulate the hydrological and ecological effects of three fuel management scenarios on a forest ecosystem. WAVES was applied using inputs from a set of forest plots for one year after three potential scenarios: (1) all litter removed, (2) all litter and 50% of the understorey removed, (3) all litter and understorey removed. Modelled outputs were compared with sites modelled with no-fuel reduction treatment (Unburnt). The key change between unburnt and fuel reduced forests was a significant increase in soil moisture after fire. Predictions of the recovery of aboveground carbon as plant biomass were driven by model structure and thus variability in available light and soil moisture at a local scale. Similarly, effects of fuel reduction burning on water processes were mainly due to changes in vegetation interception capacity (i.e. regrowth) and soil evaporation. Predicted effects of fuel reduction burning on total evapotranspiration (ET) - the major component of water balance - were marginal and not significant, even though a considerable proportion of ET had effectively been transferred from understorey to overstorey. In common with many plant growth models, outputs from WAVES are dictated by the assumption that overstorey trees continue to grow irrespective of their age or stage of maturity. Large areas of eucalypt forests and woodlands in SE Australia are well beyond their aggrading phase and are instead over-mature. The ability of these forests to rapidly respond to greater availability of water remains uncertain.