The influence of stormwater infiltration on downslope groundwater chemistry.

Stormwater infiltration basins have been used extensively around the world to restore urban hydrology towards more natural flow and water quality regimes. There is, however, significant uncertainty in the fate of infiltrated water and accompanying contaminants that depends on multiple factors including media characteristics, interactions with downslope vegetation, legacy contaminants, and presence of underground infrastructure. Understanding the influence of such factors is thus central to the design and siting of infiltration basins. An extensive field program was established to collect monthly data on ground water quality, including nutrients and major ion concentrations, in a bore network downstream of a stormwater infiltration basin in Victoria, Australia. The groundwater samples were analysed for temperature, pH, EC, turbidity, major ions (Na+, Ca2+, K+, Mg2+, Cl-, SO42-, NO3-, CO32-, HCO3-), NOx and heavy metals. The collected data were used to understand the origin and fate of water and solutes in the subsurface and their interactions with the soil matrix. The results revealed that Ca-HCO3, Na-Cl water types predominate in the study area, grouped in 3 clusters; shallow fresh groundwater in the vicinity of the basin (near basin), deep saline groundwater further downstream of the basin (near-stream) and a mid-section where rock-water interaction (Na-HCO3 water) through cation exchange control the chemistry of groundwater. The results also suggest that as the water moves downstream of the basin, it experiences significant evapotranspiration and concentration due to the presence of deep-rooted vegetation. The results suggest that while infiltration basins can remove infiltrated contaminants, the infiltrated stormwater can mobilise legacy contaminants such as nitrate. Overall, the efficacy of infiltration basins in urban regions depends substantially on the downstream vegetation, urban underground infrastructure and the presence of legacy contaminants in the soils. These all need to be considered in the design of stormwater infiltration basins.

A multi-model approach to assessing the impacts of catchment characteristics on spatial water quality in the Great Barrier Reef catchments.

Water quality monitoring programs often collect large amounts of data with limited attention given to the assessment of the dominant drivers of spatial and temporal water quality variations at the catchment scale. This study uses a multi-model approach: a) to identify the influential catchment characteristics affecting spatial variability in water quality; and b) to predict spatial variability in water quality more reliably and robustly. Tropical catchments in the Great Barrier Reef (GBR) area, Australia, were used as a case study. We developed statistical models using 58 catchment characteristics to predict the spatial variability in water quality in 32 GBR catchments. An exhaustive search method coupled with multi-model inference approaches were used to identify important catchment characteristics and predict the spatial variation in water quality across catchments. Bootstrapping and cross-validation approaches were used to assess the uncertainty in identified important factors and robustness of multi-model structure, respectively. The results indicate that water quality variables were generally most influenced by the natural characteristics of catchments (e.g., soil type and annual rainfall), while anthropogenic characteristics (i.e., land use) also showed significant influence on dissolved nutrient species (e.g., NOX, NH4 and FRP). The multi-model structures developed in this work were able to predict average event-mean concentration well, with Nash-Sutcliffe coefficient ranging from 0.68 to 0.96. This work provides data-driven evidence for catchment managers, which can help them develop effective water quality management strategies.

A simulation-based approach to assess the power of trend detection in high- and low-frequency water quality records.

To provide more precise understanding of water quality changes, continuous sampling is being used more in surface water quality monitoring networks. However, it remains unclear how much improvement continuous monitoring provides over spot sampling, in identifying water quality changes over time. This study aims (1) to assess our ability to detect trends using water quality data of both high and low frequencies and (2) to assess the value of using high-frequency data as a surrogate to help detect trends in other constituents. Statistical regression models were used to identify temporal trends and then to assess the trend detection power of high-frequency (15 min) and low-frequency (monthly) data for turbidity and electrical conductivity (EC) data collected across Victoria, Australia. In addition, we developed surrogate models to simulate five sediment and nutrients constituents from runoff, turbidity and EC. A simulation-based statistical approach was then used to the compare the power to detect trends between the low- and high-frequency water quality records. Results show that high-frequency sampling shows clear benefits in trend detection power for turbidity, EC, as well as simulated sediment and nutrients, especially over short data periods. For detecting a 1% annual trend with 5 years of data, up to 97% and 94% improvements on the trend detection probability are offered by high-frequency data compared with monthly data, for turbidity and EC, respectively. Our results highlight the benefits of upgrading monitoring networks with wider application of high-frequency sampling.

Water sources accessed by arid zone riparian trees in highly saline environments, Australia.

The flow regimes of arid zone rivers are often highly variable, and shallow groundwater in the alluvial aquifers can be very saline, thus constraining the availability and quality of the major water sources available to riparian trees-soil water, shallow groundwater and stream water. We have identified water sources and strategies used by riparian trees in more highly saline and arid conditions than previously studied for riparian trees of arid zone rivers. Our research focused on the riparian species Eucalyptus coolabah, one of the major riparian trees of ephemeral arid zone rivers in Australia. The water sources available to this riparian tree were examined using delta(18)O isotope data from xylem, soil water, groundwater and surface water. Additionally, soil chloride and matric potential data were used to infer zones of water availability for root uptake. Despite the saline conditions, the trees used a mixture of soil water and groundwater sources, but they did not use surface water directly. The study identified three strategies used to cope with typically high groundwater and soil water salinities. Firstly, the trees preferentially grow in zones of most frequent flushing by infiltrating streamflow, such as the bank-tops of channels. Secondly, the trees limit water use by having low transpiration rates. Thirdly, the trees are able to extract water at very low osmotic potentials, with water uptake continuing at chloride concentrations of at least 20,000-30,000 mg L(-1).