943 resultados para Water quality management -- Queensland -- Moreton Bay


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Florida Bay is a unique subtropical estuary that while historically oligotrophic, has been subjected to both natural and anthropogenic stressors, including hurricanes, coastal eutrophication and other impacts. These stressors have resulted in degradation of water quality in the past several decades, most evidenced by reoccurring blooms of the picocyanobacterium Synechococcus spp. Major nutrient inputs consist of freshwater flows to the eastern region from runoff and regulated canal releases, inputs from the Everglades to the central region via Taylor Slough, exchanges with the Gulf of Mexico, which include intermittent Shark River inputs to the western region, stormwater and wastewater from the Florida Keys, and atmospheric deposition. These nutrient inputs have resulted in a transition from strong phosphorus (P) limitation of phytoplankton in the eastern bay to nitrogen (N) limitation in the western bay. Large blooms of Synechococcus were most pronounced in the central bay region, in the area of transition between P and N limitation, in the mid-1990s. Although non-toxic, these blooms, which have continued intermittently through the early 2000s, resulted in significant sea-grass and benthic organism mortalities. A new suite of stressors in 2005, including the passages of Hurricanes Katrina, Rita, and Wilma, additional canal releases, and the initiation of road construction to widen the main roadway leading to the Keys, were correlated with a large Synechococcus bloom in the previously clear, strongly P- limited, northeastern region of the bay. Sustained for 3 years, this bloom was accompanied by a shift from P limitation to N limitation during its course. Nutrient bioassay experiments suggest that this bloom persisted due to the ability of Synechococcus to access organic N and P sources, microbial and geochemical cycling of organic and inorganic nutrients in the water column and between the water column and sediments (both suspended particles and benthos), and decreased grazing by benthic fauna due to their die-off.

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This report summarizes the existing data from the FIU Coastal Water Quality Monitoring Network for calendar year January 1 – December 31, 2007. This includes water quality data collected from 28 stations in Florida Bay, 22 stations in Whitewater Bay, 25 stations in Ten Thousand Islands, 25 stations in Biscayne Bay, 49 stations on the Southwest Florida Shelf (Shelf), and 28 stations in the Cape Romano-Pine Island Sound area. Each of the stations in Florida Bay were monitored on a monthly basis with monitoring beginning in March 1991; Whitewater Bay monitoring began in September 1992; Biscayne Bay monthly monitoring began September 1993; the SW Florida Shelf was sampled quarterly beginning in spring 1995; and monthly sampling in the Cape Romano-Pine Island Sound area started January 1999.

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The distribution, abundance, behaviour, and morphology of marine species is affected by spatial variability in the wave environment. Maps of wave metrics (e.g. significant wave height Hs, peak energy wave period Tp, and benthic wave orbital velocity URMS) are therefore useful for predictive ecological models of marine species and ecosystems. A number of techniques are available to generate maps of wave metrics, with varying levels of complexity in terms of input data requirements, operator knowledge, and computation time. Relatively simple "fetch-based" models are generated using geographic information system (GIS) layers of bathymetry and dominant wind speed and direction. More complex, but computationally expensive, "process-based" models are generated using numerical models such as the Simulating Waves Nearshore (SWAN) model. We generated maps of wave metrics based on both fetch-based and process-based models and asked whether predictive performance in models of benthic marine habitats differed. Predictive models of seagrass distribution for Moreton Bay, Southeast Queensland, and Lizard Island, Great Barrier Reef, Australia, were generated using maps based on each type of wave model. For Lizard Island, performance of the process-based wave maps was significantly better for describing the presence of seagrass, based on Hs, Tp, and URMS. Conversely, for the predictive model of seagrass in Moreton Bay, based on benthic light availability and Hs, there was no difference in performance using the maps of the different wave metrics. For predictive models where wave metrics are the dominant factor determining ecological processes it is recommended that process-based models be used. Our results suggest that for models where wave metrics provide secondarily useful information, either fetch- or process-based models may be equally useful.

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Knowledge of how biota can be used to monitor ecosystem health and assess impacts by human alterations such as land use and management measures taken at different spatial scales is critical for improving the ecological quality of aquatic ecosystems. This knowledge in Uganda is very limited or unavailable yet it is needed to better understand the relationship between environmental factors at different spatial scales, assemblage structure and taxon richness of aquatic ecosystems. In this study, benthic invertebrate community patterns were sampled between June 2001 and April 2002 and analysed in relation to water quality and catchment land use patterns from three shallow near-shore bays characterized by three major land uses patterns: urban (Murchison Bay); semi-urban (Fielding Bay); rural (Hannington Bay). Variations in density and guild composition of benthic macro-invertebrates communities were evaluated using GIS techniques along an urban-rural gradient of land use and differences in community composition were related to dissolved oxygen and conductivity variation. Based on numerical abundance and tolerance values, Hilsenhoff's Biotic Index ofthe invertebrates was determined in order to evaluate the relative importance of water quality in the three bays. Murchison Bay supported a relatively taxa-poor invertebrate assemblage mainly comprising stenotopic and eurytopic populations of pollution-tolerant groups such as worms and Chironomus sp. with an overall depression in species diversity. On the contrary, the communities in Fielding and Hannington bays were quite similar and supported distinct and diverse assemblages including pollution-intolerant forms such as Ephemeroptera (mayflies), Odonata (dragonflies). The Hilsenhoff Biotic Index in Murchison Bay was 6.53. (indicating poor water quality) compared to 6.34 for Fielding Bay and 5.78 for Hannington Bay (both indicating fair water quality). The characterization of maximum taxa richness balanced among taxa groups with good representation of intolerant individuals in Hannington Bay relative to Fielding and Murchison bays concludes that the bay is the cleanest in terms of water quality. Contrary, the dominance of few taxa with many tolerant iqdividuals present in Murchison Bay indicates that the bay is degraded in terms of water quality. These result are ofimportance when planning conservation and management measures, implementing large-scale biomonitoring programs, and predicting how human alterations (e.g nutrient loading) affect water ecosystems. Therefore, analysis of water quality in relation to macro-invertebrate community composition patterns as bio-indicators can lead to further understanding of their responses to environmental manipulations and perturbations.

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This research project was driven by the recurring complaints and concerns voiced in the media by residents living in the Valley area of the community of Happy Valley-Goose Bay, Labrador. Drinking water in this town is supplied by two water treatment plants (a municipality treatment plant and a DND treatment plant), which use raw water from two different sources (groundwater from multiple wells versus surface water from Spring Gulch brook) and use two different processes of drinking-water treatment. In fact, the drinking water supplied in the Valley area has a unique distribution arrangement. To meet demand, the Valley area is served by a blend of treated waters from a storage reservoir (Sandhill reservoir), which is fed by both water treatment plants. Most of the time, treated water from the municipal treatment plant dominates in the mixture. As water travels through the distribution system and household plumbing, specific reactions can occur either in the water itself and/or at the solid–liquid interface at the pipe walls; this is strongly influenced by the physical and chemical characteristics of the water. These reactions can introduce undesirable chemical compounds and/or favor the growth of bacteria in the drinking water, causing the deterioration of the quality of water reaching the consumer taps. In the distribution system in general, these chemical constituents and bacteria may pose potential threats to health or the water’s aesthetic qualities (smell, taste or appearance). Drinking water should be not only safe, but also palatable.

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Water quality issues are heavily dependent on land development and management decisions within river and lake catchments or watersheds. Economic benefits of urbanisation may be short‐ lived without cleaner environmental outcomes. However, whole‐of‐catchment thinking is not, as yet, as frequent a consideration in urban planning and development in China as it is in many other countries. Water is predominantly seen as a resource to be ‘owned’ by different jurisdictions and allocated to numerous users, both within a catchment and between catchments. An alternative to this approach is to think of water in the same way as other commodities that must be kept moving through a complex transport system. Water must ultimately arrive at particular destinations in the biosphere, although it travels across a broad landscape and may be held up temporarily at certain places along the way. While water extraction can be heavily controlled, water pollution is far more difficult to regulate. Both have significant impacts on water availability and flows both now and in the future. As Chinese cities strive to improve economic conditions for their citizens, new centres are being rebuilt and environmental valued

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Background: The quality of stormwater runoff from ports is significant as it can be an important source of pollution to the marine environment. This is also a significant issue for the Port of Brisbane as it is located in an area of high environmental values. Therefore, it is imperative to develop an in-depth understanding of stormwater runoff quality to ensure that appropriate strategies are in place for quality improvement, where necessary. To this end, the Port of Brisbane Corporation aimed to develop a port specific stormwater model for the Fisherman Islands facility. The need has to be considered in the context of the proposed future developments of the Port area. ----------------- The Project: The research project is an outcome of the collaborative Partnership between the Port of Brisbane Corporation (POBC) and Queensland University of Technology (QUT). A key feature of this Partnership is that it seeks to undertake research to assist the Port in strengthening the environmental custodianship of the Port area through ‘cutting edge’ research and its translation into practical application. ------------------ The project was separated into two stages. The first stage developed a quantitative understanding of the generation potential of pollutant loads in the existing land uses. This knowledge was then used as input for the stormwater quality model developed in the subsequent stage. The aim is to expand this model across the yet to be developed port expansion area. This is in order to predict pollutant loads associated with stormwater flows from this area with the longer term objective of contributing to the development of ecological risk mitigation strategies for future expansion scenarios. ----------------- Study approach: Stage 1 of the overall study confirmed that Port land uses are unique in terms of the anthropogenic activities occurring on them. This uniqueness in land use results in distinctive stormwater quality characteristics different to other conventional urban land uses. Therefore, it was not scientifically valid to consider the Port as belonging to a single land use category or to consider as being similar to any typical urban land use. The approach adopted in this study was very different to conventional modelling studies where modelling parameters are developed using calibration. The field investigations undertaken in Stage 1 of the overall study helped to create fundamental knowledge on pollutant build-up and wash-off in different Port land uses. This knowledge was then used in computer modelling so that the specific characteristics of pollutant build-up and wash-off can be replicated. This meant that no calibration processes were involved due to the use of measured parameters for build-up and wash-off. ---------------- Conclusions: Stage 2 of the study was primarily undertaken using the SWMM stormwater quality model. It is a physically based model which replicates natural processes as closely as possible. The time step used and catchment variability considered was adequate to accommodate the temporal and spatial variability of input parameters and the parameters used in the modelling reflect the true nature of rainfall-runoff and pollutant processes to the best of currently available knowledge. In this study, the initial loss values adopted for the impervious surfaces are relatively high compared to values noted in research literature. However, given the scientifically valid approach used for the field investigations, it is appropriate to adopt the initial losses derived from this study for future modelling of Port land uses. The relatively high initial losses will reduce the runoff volume generated as well as the frequency of runoff events significantly. Apart from initial losses, most of the other parameters used in SWMM modelling are generic to most modelling studies. Development of parameters for MUSIC model source nodes was one of the primary objectives of this study. MUSIC, uses the mean and standard deviation of pollutant parameters based on a normal distribution. However, based on the values generated in this study, the variation of Event Mean Concentrations (EMCs) for Port land uses within the given investigation period does not fit a normal distribution. This is possibly due to the fact that only one specific location was considered, namely the Port of Brisbane unlike in the case of the MUSIC model where a range of areas with different geographic and climatic conditions were investigated. Consequently, the assumptions used in MUSIC are not totally applicable for the analysis of water quality in Port land uses. Therefore, in using the parameters included in this report for MUSIC modelling, it is important to note that it may result in under or over estimations of annual pollutant loads. It is recommended that the annual pollutant load values given in the report should be used as a guide to assess the accuracy of the modelling outcomes. A step by step guide for using the knowledge generated from this study for MUSIC modelling is given in Table 4.6. ------------------ Recommendations: The following recommendations are provided to further strengthen the cutting edge nature of the work undertaken: * It is important to further validate the approach recommended for stormwater quality modelling at the Port. Validation will require data collection in relation to rainfall, runoff and water quality from the selected Port land uses. Additionally, the recommended modelling approach could be applied to a soon-to-be-developed area to assess ‘before’ and ‘after’ scenarios. * In the modelling study, TSS was adopted as the surrogate parameter for other pollutants. This approach was based on other urban water quality research undertaken at QUT. The validity of this approach should be further assessed for Port land uses. * The adoption of TSS as a surrogate parameter for other pollutants and the confirmation that the <150 m particle size range was predominant in suspended solids for pollutant wash-off gives rise to a number of important considerations. The ability of the existing structural stormwater mitigation measures to remove the <150 m particle size range need to be assessed. The feasibility of introducing source control measures as opposed to end-of-pipe measures for stormwater quality improvement may also need to be considered.