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Start date: 2020Subject: search.filters.subject.Water quality

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    Modelling and mapping of subsurface nitrate-attenuation index in agricultural landscapes
    (Elsevier Ltd, 2025-06) Collins SB; Singh R; Mead SR; Horne DJ; Zhang L
    Environmental management of nutrient losses from agricultural lands is required to reduce their potential impacts on the quality of groundwater and eutrophication of surface waters in agricultural landscapes. However, accurate accounting and management of nitrogen losses relies on a robust modelling of nitrogen leaching and its potential attenuation – specifically, the reduction of nitrate to gaseous forms of nitrogen – in subsurface flow pathways. Subsurface denitrification is a key process in potential nitrate attenuation, but the spatial and temporal dynamics of where and when it occurs remain poorly understood, especially at catchment-scale. In this paper, a novel Landscape Subsurface Nitrate-Attenuation Index (LSNAI) is developed to map spatially variable subsurface nitrate attenuation potential of diverse landscape units across the Manawatū-Whanganui region of New Zealand. A large data set of groundwater quality across New Zealand was collated and analysed to assess spatial and temporal variability of groundwater redox status (based on dissolved oxygen, nitrate and dissolved manganese) across different hydrogeological settings. The Extreme Gradient Boosting algorithm was used to predict landscape unit subsurface redox status by integrating the nationwide groundwater redox status data set with various landscape characteristics. Applying the hierarchical clustering analysis and unsupervised classification techniques, the LSNAI was then developed to identify and map five landscape subsurface nitrate attenuation classes, varying from very low to very high potential, based on the predicted groundwater redox status probabilities and identified soil drainage and rock type as key influencing landscape characteristics. Accuracy of the LSNAI mapping was further investigated and validated using a set of independent observations of groundwater quality and redox assessments in shallow groundwaters in the study area. This highlights the potential for further research in up-scaling mapping and modelling of landscape subsurface nitrate attenuation index to accurately account for spatial variability in subsurface nitrate attenuation potential in modelling and assessment of water quality management measures at catchment-scale in agricultural landscapes.
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    Quantification of denitrification rate in shallow groundwater using the single-well, push-pull test technique
    (Elsevier BV, Amsterdam, 2025-02) Rivas A; Singh R; Horne D; Roygard J; Matthews A; Hedley M
    Denitrification has been identified as a significant nitrate attenuation process in groundwater systems. Hence, accurate quantification of denitrification rates is consequently important for the better understanding and assessment of nitrate contamination of groundwater systems. There are, however, few studies that have investigated quantification of shallow groundwater denitrification rates using different analytical approaches or assuming different kinetic reaction models. In this study, we assessed different analytical approaches (reactant versus product) and kinetic reaction (zero-order and first-order) models analysing observations from a single-well, push-pull tests to quantify denitrification rates in shallow groundwater at two sites in the Manawatū River catchment, Lower North Island of New Zealand. Shallow groundwater denitrification rates analysed using the measurements of denitrification reactant (nitrate reduction) and zero-order kinetic models were quantified at 0.42-1.07 mg N L-1 h-1 and 0.05-0.12 mg N L-1 h-1 at the Palmerston North (PNR) and Woodville (WDV) sites, respectively. However, using first-order kinetic models, the denitrification rates were quantified at 0.03-0.09 h-1 and 0.002-0.012 h-1 at the PNR and WDV sites, respectively. These denitrification rates based on the measurements of denitrification reactant (nitrate reduction) were quantified significantly higher (6 to 60 times) than the rates estimated using the measurements of denitrification product (nitrous oxide production). However, the denitrification rate quantified based on the nitrate reduction may provide representative value of denitrification characteristics of shallow groundwater systems. This is more so when lacking practical methods to quantify all nitrogen species (i.e., total N, organic N, nitrite, nitrate, ammoniacal N, nitrous oxide, nitric oxide, and nitrogen gas) in a push-pull test. While estimates of denitrification rates also differed depending on the kinetic model used, both a zero-order and a first-order model appear to be valid to analyse and estimate denitrification rate from push-pull tests. However, a discrepancy in estimates of denitrification rates using either reactant or product and using zero- or first-order kinetics models may have implications in assessment of nitrate transport and transformation in groundwater systems. This necessitates further research and analysis for appropriate measurements and representation of spatial and temporal variability in denitrification characteristics of the shallow groundwater system.
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    Thin film electrochemical sensor for water quality monitoring : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering, Massey University, Auckland, New Zealand
    (Massey University, 2023-12-11) Lal, Kartikay
    Freshwater is the most precious natural resource, essential for supporting life. Aquatic ecosystems flourish in freshwater sources, and many regions around the world depend on aquatic food sources, such as fish. Nitrogen and phosphorous are the two nutrients, in particular, that are essential for growth of aquatic plants and algae. However, with rising population and anthropogenic activities, excessive amounts of such nutrients enter our waterways through various natural processes, thereby degrading the quality of freshwater sources. Elevated levels of nitrate-nitrogen content, in particular, lead to consequences for both aquatic life as well as human health, which has been a cause for concern for many decades. As recommended by the World Health Organization, the maximum permissible nitrate level in water is 11.3 mg/L. These levels are often exceeded in coastal areas or freshwater bodies that are close to agricultural land. Therefore, it is essential to monitor nitrate levels in freshwater sources in real-time, which can be achieved by employing detection methods commonly used to detect ionic content in water. Hence, a comprehensive review was carried out on various field-deployable electrochemical and optical detection methods that could be employed for in-situ detection of nitrate ions in water. The primary focus was on electrochemical methods that could be integrated with low-cost planar electrodes to achieve targeted detection of nitrate ions in water. Designing resilient sensors for real-time monitoring of water quality is a challenging task due to the harsh environment to which they are subjected. There is a significant need for sensors with attributes such as repeatability, sensitivity, low-cost, and selectivity. These attributes were first explored by evaluating the performance of silver and copper materials on three distinct geometric patterns of electrodes. The experiments produced promising results with interdigitated pattern of copper electrodes that were successful in detecting 0.1-0.5 mg/L of nitrate ions in deionised water. The interdigitated geometric pattern of electrodes were further analyzed in four distinct materials namely, silver, gold, copper, and tin with real-world freshwater samples that were collected from three different freshwater bodies. The water samples were used to synthesize varying concentrations of nitrate ions. The results showed tin electrodes performed better over other materials for nitrate concentrations from 0.1-1 mg/L in complex matrix of real-world sample. The nitrate sensor eventually needs to be deployed in freshwater bodies, hence a real-time water quality monitoring system was also built that incorporated sensors to monitor five basic water quality parameters with the aim to monitor and study the quality of water around the local area.
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    Nitrate enrichment does not affect enteropathogenic Escherichia coli in aquatic microcosms but may affect other strains present in aquatic habitats
    (PeerJ, Inc, 2022-09-27) Davis MT; Canning AD; Midwinter AC; Death RG; Oehlmann J
    Eutrophication of the planet's aquatic systems is increasing at an unprecedented rate. In freshwater systems, nitrate-one of the nutrients responsible for eutrophication-is linked to biodiversity losses and ecosystem degradation. One of the main sources of freshwater nitrate pollution in New Zealand is agriculture. New Zealand's pastoral farming system relies heavily on the application of chemical fertilisers. These fertilisers in combination with animal urine, also high in nitrogen, result in high rates of nitrogen leaching into adjacent aquatic systems. In addition to nitrogen, livestock waste commonly carries human and animal enteropathogenic bacteria, many of which can survive in freshwater environments. Two strains of enteropathogenic bacteria found in New Zealand cattle, are K99 and Shiga-toxin producing Escherichia coli (STEC). To better understand the effects of ambient nitrate concentrations in the water column on environmental enteropathogenic bacteria survival, a microcosm experiment with three nitrate-nitrogen concentrations (0, 1, and 3 mg NO3-N /L), two enteropathogenic bacterial strains (STEC O26-human, and K99-animal), and two water types (sterile and containing natural microbiota) was run. Both STEC O26 and K99 reached 500 CFU/10 ml in both water types at all three nitrate concentrations within 24 hours and remained at those levels for the full 91 days of the experiment. Although enteropathogenic strains showed no response to water column nitrate concentrations, the survival of background Escherichia coli, imported as part of the in-stream microbiota did, surviving longer in 1 and 3 mg NO3-N/Lconcentrations (P < 0.001). While further work is needed to fully understand how nitrate enrichment and in-stream microbiota may affect the viability of human and animal pathogens in freshwater systems, it is clear that these two New Zealand strains of STEC O26 and K99 can persist in river water for extended periods alongside some natural microbiota.
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    Detecting genes associated with antimicrobial resistance and pathogen virulence in three New Zealand rivers
    (PeerJ, Inc, 2021-12-03) Davis M; Midwinter AC; Cosgrove R; Death RG; Oehlmann J
    The emergence of clinically significant antimicrobial resistance (AMR) in bacteria is frequently attributed to the use of antimicrobials in humans and livestock and is often found concurrently with human and animal pathogens. However, the incidence and natural drivers of antimicrobial resistance and pathogenic virulence in the environment, including waterways and ground water, are poorly understood. Freshwater monitoring for microbial pollution relies on culturing bacterial species indicative of faecal pollution, but detection of genes linked to antimicrobial resistance and/or those linked to virulence is a potentially superior alternative. We collected water and sediment samples in the autumn and spring from three rivers in Canterbury, New Zealand; sites were above and below reaches draining intensive dairy farming. Samples were tested for loci associated with the AMR-related group 1 CTX-M enzyme production (bla CTX-M) and Shiga toxin producing Escherichia coli (STEC). The bla CTX-M locus was only detected during spring and was more prevalent downstream of intensive dairy farms. Loci associated with STEC were detected in both the autumn and spring, again predominantly downstream of intensive dairying. This cross-sectional study suggests that targeted testing of environmental DNA is a useful tool for monitoring waterways. Further studies are now needed to extend our observations across seasons and to examine the relationship between the presence of these genetic elements and the incidence of disease in humans.
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    Ecology of ponds : anthropogenic and environmental effects on biodiversity : a thesis presented in partial fulfilment of the requirement for the degree of Doctor of Philosophy in Conservation Biology at Massey University, Auckland, New Zealand
    (Massey University, 2022) Kuranchie, Abigail
    Ponds are a vital component of the freshwater ecosystem but have been understudied worldwide. The paucity of research is especially disturbing due to increasing pressure on freshwater ecosystems. Pond ecosystems are vulnerable due to anthropogenic activities and changing environmental conditions. Ponds are the most ubiquitous freshwater ecosystems found in the Auckland Region of New Zealand. Despite their abundance (occurring in all landscapes) and significant ecological role, there is a lack of knowledge on the ecology of pond ecosystems in New Zealand. Further, literature on the impact of land use/ land cover (LULC) and human population density on pond water quality and biodiversity is lacking globally. I studied aspects of ponds (natural and man-made) ecology in the Auckland region by assessing both abiotic and biotic factors in the summer and winter seasons. Specifically, my study focused on six aspects of the ecology of pond ecosystems: i) the relationship between water quality and LULC at multiple spatial scales across the seasons, ii) the temporal community composition of macroinvertebrates and the relationship between the communities and the abiotic factors, iii) the influence of anthropogenic activities (measured as human population density and as pond types or function) on the macroinvertebrate communities, iv) the phytoplankton communities in ponds across the seasons, v) the limiting nutrient(s) in periphyton biomass in ponds using an in-situ experiment, and finally, vi) a single case study tracking a newly formed pond in a restoration area and development of its macroinvertebrate community over one year. I sampled 50 ponds in the Auckland region across two seasons (summer and winter) to assess pond water quality (evaluated using seven physicochemical variables: pH, percentage dissolved oxygen '% DO', conductivity, temperature, total dissolved solids 'TDS', salinity, nitrate, phosphate and ammoniacal nitrogen). My aim was to understand the relationship between water quality and the landscape features (physical variables and LULC types: ‘forest, grass, and impervious surface’) at multiple spatial scales (10m, 100m, 500m and pond catchment) from the pond. I found a significant seasonal difference in the water quality of ponds. All the water quality variables measured apart from ammoniacal nitrogen were higher in summer, suggesting that the water was of lower quality at that time. Also, the effect of LULC on the physicochemical water quality parameters varied spatially and seasonally. LULC at the catchment and 500m scale influenced the water quality in winter, while the LULC at 100m affected the water quality in summer. The results highlight the critical and complex role of environmental factors and LULC in determining the water quality in ponds. I assessed the macroinvertebrate community compositions and water quality in 12 ponds across two seasons for two years. I found an average of 15 macroinvertebrate taxa in focal ponds. Insects were the most diverse group found, although Crustacea were most abundant. The community composition of the macroinvertebrates varied among ponds and varied across seasons and years. Macroinvertebrates were more abundant, and the community was more diverse in summer. The % DO in the ponds was negatively correlated to the macroinvertebrate abundance. My results suggest that macroinvertebrates and water quality in ponds are temporally variable. I assessed the influence of anthropogenic activities on the macroinvertebrate communities of 11 ponds. Four categories of human population density were used (rural, small urban, large urban, and major urban; in order of increasing human population) to group ponds for analysis. By applying taxonomic and trait-based (functional feeding groups) approaches, I found that high human population density was negatively associated with the macroinvertebrate communities, especially in summer. Ponds in rural areas had the highest diversity of macroinvertebrates and the highest composition of functional foraging group relative to the other areas assessed. This finding suggests that ponds in rural areas had the lowest anthropogenic impact. Ornamental ponds were rich in macroinvertebrates, primarily due to a comparatively more heterogenous pond habitat. I sampled and analysed the phytoplankton community composition of 12 ponds in summer and winter. Overall, the communities were dominated by taxa in the phylum Chlorophyta (green algae) and class Bacillariophyceae (Diatoms). Although I did find seasonal differences in the phytoplankton communities, these were influenced by temperature and conductivity. In addition, ponds within areas of denser human populations had the most motile diatoms in summer, suggesting high siltation. Despite being moderately polluted, these results show that all ponds generally had healthy phytoplankton communities. Furthermore, by using an in-situ nutrient diffusion experiment, I found that nitrogen is likely to be the limiting nutrient for periphyton growth in ponds. Finally, I sampled and monitored a newly created and a nearby established pond for a year to obtain insights into the progression of a pond from creation into a functional ecosystem using macroinvertebrates as indicators. I found that Crustaceans were the first to colonise the new pond. The macroinvertebrate community in the new pond was more taxonomically distinct than the established pond at the end of the first year of its creation. Shannon Weiner's diversity index was similar between the ponds, and environmental factors influenced the macroinvertebrate abundance. My results indicate that new ponds can create new habitats and boost local freshwater biodiversity. By combining water quality analyses, and detailed biodiversity assessment, my thesis demonstrates that pond ecosystems support a high diversity of macroinvertebrates and phytoplankton. Environmental variables, LULC, and human population density influence the biodiversity in ponds, and the extent, relationship, and impact of these are complex and vary seasonally. My study provides new baseline information and valuable insights for future research on pond ecosystems in New Zealand.
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    Self-assembled optical diffraction sensor for water quality monitoring : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering, Massey University, Albany, New Zealand
    (Massey University, 2020) Jaywant, Swapna
    Water contamination is one of the current global issues; the freshwater sources being extremely restricted are causing a drinking water crisis in many countries. An increase in water contamination continuously decreases water quality. Generally, water pollution includes pathogenic, nutrients, and chemical (organic & inorganic) contaminants. Inorganic contamination involves metallic particles such as arsenic, lead, etc. Of these contaminants, arsenic (As) is a major concern due to its mutagenic and carcinogenic effects on human health. The World Health Organisation has recommended the maximum contamination limit (MCL) for arsenic in drinking water to be 10 µg/L. Countries like Bangladesh, China, Vietnam, India, Chile, USA, and Canada are contaminated with arsenic. Arsenic species are also found in New Zealand in 28 geothermal features from the Taupo Volcanic Zone and the Waikato region. Thus, a rising level of arsenic in drinking water creates the need to periodically monitor its levels in potable water. Commercially available methods are either laboratory-based or kit based techniques. The most common laboratory-based arsenic detection methods are reliable. However, these are expensive due to the requirement for specific instrumentation. Hence, they are not considered to be field-effective for arsenic detection. On the other hand, commercially available kit-based methods are portable but are not considered to be safe and reliable due to the production of toxic by-products. The development of a portable and sensitive arsenic sensor with high throughput could be an asset. In this research, we present a novel sensor with a unique surface modification technique to detect arsenite (As(III)) contamination of water. Here, the approach involves the potential usage of self-assembled optical diffraction patterns of a thiol compound (dithiothreitol or glutathione) on the gold-coated glass. The self-assembled patterns are obtained through a microcontact printing (µCP) procedure. Gold binds with the thiol compound through an Au-S linkage. In addition to this, As(III) has an affinity towards amino acids, amines, peptides, and organic micro molecules due to As-O or As-S linkages. The research indicates that the total time taken by the µCP process to transfer the patterns successfully on to the gold-coated substrate is inversely proportional to the concentration of the thiol molecules and pH value of the solvent. Further, the signal enhancement of these thiol-based self-assembled patterns allows for detection of the As(III) contamination. Simultaneously, the automated fluidic system is designed to provide fluid handling. The system is developed with the help of off-the-shelf and/or in-house fabricated components. The characterisation of fluidic components proved that the low-cost fluidic components work reliably in the fluidic network and can be used in sensing applications for pumping, mixing, and circulation purposes. We also explore the possibility of using fused deposition modelling and selective laser sintering technology for the printing of the flow chamber through printing microchannels. These two technologies have been compared in terms of the minimum possible channel size, fluid ow-rate, and leakage. Overall, we developed a sensing scheme of a portable self-assembled diffraction sensor for As(III) detection. The developed sensor can detect dissolved As(III) up to 20 µg/L. The µCP of a dithiothreitol pattern has not been found in the literature yet. Hence, this research also provides a guide towards µCP of dithiothreitol on a gold-coated substrate.