Groundwater and wetlands contamination with pesticides and nutrients from farms in Victoria, Australia

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This study estimates the extent of pollution in aquifers and wetlands in the agricultural region. Tests were conducted for triazines (atrazine, hexazinone, metribuzin, prometrym, simazine, desisopropyl-atrazine, and desethyl-atrazine), nitrogen and phosphorus in 23 groundwater monitoring bores susceptible to agricultural pollution and ten nearby wetlands. Results indicated that one bore exhibited elevated pesticide levels, with a total concentration of 19.43 µg/L. Nitrogen and phosphorus were detected in most groundwater bores with concentrations below 51.6 mg/L and 0.30 mg/L, respectively. Compound Atrazine was found in three wetlands below 0.064 µg/L, while simazine was detected in four wetlands below 1.2 µg/L. The study suggests that although low pesticide levels were observed in wetlands, nutrient contamination is prevalent in the aquifer at the study site. Further investigation is necessary to comprehend the impacts of pesticides and nutrients on groundwater and wetland ecosystems. These findings emphasize the importance of ongoing monitoring and research to mitigate the adverse effects of intensive agricultural practices on groundwater and wetlands, thus, holding significant implications for policymakers and researchers. Earth and environmental sciences/Environmental sciences/Environmental chemistry/Environmental monitoring Earth and environmental sciences/Environmental sciences/Environmental chemistry/Geochemistry Earth and environmental sciences/Environmental sciences/Environmental chemistry/Pollution remediation Physical sciences/Chemistry/Environmental chemistry/Geochemistry Physical sciences/Chemistry/Environmental chemistry/Pollution remediation Earth and environmental sciences/Limnology Earth and environmental sciences/Solid earth sciences/Geochemistry Earth and environmental sciences/Environmental sciences/Environmental chemistry Earth and environmental sciences/Environmental sciences/Environmental impact Pesticides nutrients triazines contamination groundwater wetlands Figures Figure 1 Figure 2 Figure 3 1. Introduction Water availability is crucial for the productivity of natural and agricultural ecosystems (Nemani et al., 2003 ), with groundwater quality and quantity being vital for human development and sustaining groundwater-dependent ecosystems (Eamus et al., 2006 ). In regions like Victoria, Australia, intensive agriculture poses contamination risks to both surface water and groundwater. Triazine herbicides, extensively used on canola crops and for governmental landscaping and road maintenance, are among the key pollutants (Regional Roads Victoria, 2019 ). These pesticides directly threaten various aquatic organisms and have significant adverse effects on human health (Schäfer et al., 2011 ; Cohen, 2007 ; Sengupta and Banerjee, 2014 ; Swan, 2006 ). Atrazine, a commonly used herbicide, has been linked to reduced sperm quality in small mammals and embryonic toxicity (Feyzi Dehkhargani et al., 2011 ; Bigsby et al., 1999 ). Despite being permitted in Australia and Canada, atrazine and its mixtures are banned in the European Union (European Commission, 2004), highlighting the need to understand pesticide mobility and impacts (Kearney and Helling, 1982 ). The Glenelg Hopkins Catchment (GHC), spanning over 26,000 km2, is predominantly used for agriculture, with 80% allocated to agricultural activities (VLUIS, 2017). While vital for Australian agriculture (GH CMA, 2018 ), it hosts ecologically significant wetlands like the Victorian Western Districts Lakes (DNRE, 2002b ), serving as habitats for threatened species (CMA, 2014 ). Some wetlands rely on groundwater, making them susceptible to fluctuations in quality (GH CMA, 2006 ). Despite their ecological significance, there's a dearth of research on the impact of agricultural practices on groundwater and wetlands within this catchment. Although some studies explored groundwater nutrients' effects on wetlands, inconclusive results were attributed to small sample sizes (Raisin, Bartley, and Croome, 1999 ). Notably, the Victorian Strategic Direction Statement overlooks agricultural pollution in groundwater as a threat to wetlands. Over the past two decades, triazine-based products' use in Victorian agriculture has surged, particularly with canola production (VLUIS). Multiple herbicide and fungicide applications are made throughout the cropping season, emphasizing reliance on these chemicals for pest management. Herbicides recommended by Regional Roads Victoria for road conservation purposes also pose risks to aquatic ecosystems, jeopardizing wetlands and contributing to algal blooms (Rabalais, 2002 ). The active chemical ingredients of these herbicides are listed in Table 1 . Table 1 Commercial herbicides with their chemical active ingredients (Conboy, Jhonson, Mclean et al., 2018 ) Altiplano Triflur Atradex/ Atrazine Ultra Avadex Burst Butisan Clomazone, Napropamide Trifluralin, Liquid hydrocarbon Atrazine Potassium salt of glyphosate Triallate, Liquid Hydrocarbon Propyzamide Metazachlor Despite sporadic efforts, studies investigating pesticide and nutrient pollution in Victoria are scarce. Most pesticide studies in groundwater date back to before 2007, necessitating updated assessments given escalating pesticide usage trends. Recent reviews identified atrazine, simazine, chlorpyriphos, and DDT as commonly detected pesticides in Victoria, reflecting international trends like New Zealand's national pesticide survey. However, nutrient data gaps exacerbate pesticide contamination assessment challenges. Financial and logistical constraints, coupled with the absence of specific guidelines for groundwater pesticide surveys, hinder robust assessments. Despite acknowledgments of the need for hydrogeological risk assessments, the lack of comprehensive guidelines for estimating aquifer vulnerability underscores the need for standardized methodologies. This study aims to assess agriculture's impact on groundwater quality in shallow aquifers and wetlands within the study area. Water samples from high, medium, and low-risk zones were analyzed for triazine herbicides, nitrogen, phosphorus, pH, temperature, and electrical conductivity. 2. Results 2.1. Sample size We identified a total of 47 monitoring bores and 10 wetlands for our study. However, out of the 47 selected monitoring bores, 24 were found to be inaccessible due to various reasons, such as being situated on private land, having an internal diameter less than 60mm, or being physically inaccessible. Therefore, only 23 bores were accessible for testing. The findings from the field survey are summarized in Table 2 . Table 2 Sample size, the GH CMA Sample size and total monitoring bores 47 Total sites visited 24 Bores were inaccessible or with no water 17 Bores visited in the first field survey 6 Bores were sampled in the second field survey 10 Wetlands Areas with the lowest vulnerability values were observed in the Grampians National Park and the eastern region of the study area, encompassing areas between Casterton, Coleraine, and Merino. Conversely, the most vulnerable regions were situated along the ocean side and in the area between the Grampians, Dunkeld, Ararat, and Skipton. It is noteworthy that this latter region also serves as the primary agricultural production hub within the catchment. 2.2. Groundwater monitoring bores and wetlands selection After filtering the water from the SOBN monitoring bores, we identified 351 active monitoring bores suitable for testing. Overlaying the land use map with the SOBN map aided in identifying areas and monitoring bores susceptible to agricultural pollution, as illustrated in Fig. 3 . Wetlands were selected based on the land use map, which delineated areas designated for canola cropping. Consequently, a total of 23 bores and 10 wetlands were selected across the GHC. 2.3. Groundwater nutrient results Groundwater samples underwent analysis to determine the concentrations of NOx and DRP, serving as pollution indicators. The findings revealed elevated pollution levels at several bore locations. NOx concentrations ranged from 0.04 mg/L to 51.6 mg/L, with bore 112233 exhibiting the highest concentration, surpassing the Australian threshold value for nitrogen as NOx in freshwater (0.04 mg/L). Similarly, DRP concentrations varied from 0.015 mg/L to 0.30 mg/L, with bore 112233 also recording the highest concentration, exceeding the Australian trigger value of 0.015 mg/L specified for slightly disturbed ecosystems in lowland river ecosystems, as outlined in Table 3 of the ANZECC/ARMCANZ ( 2000 ) guidelines. These outcomes indicate a considerable proportion of bores exhibiting NOx and DRP pollution concentrations above threshold values, signifying a potential risk of groundwater contamination. Bore 98253, situated outside the study area in a confined aquifer, was excluded from linear correlation analysis. Table 3 Results for NOx and DRP in GW bores N Bore ID NOx DRP N Bore ID NOx DRP 1 11170 6.54 0.02 12 111528 < 0.01 0.08 2 45807 0.52 0.04 13 111530 0.08 0.06 3 82181 < 0.01 < 0.01 14 111690 0.02 0.01 4 83447 0.12 < 0.01 15 111696 0.03 0.09 5 87757 0.03 < 0.01 16 112232 2.17 0.11 6 98253 0.25 0.01 17 112233A 51.6 0.30 7 102412 < 0.01 < 0.01 18 112237 0.06 0.03 8 102621 1.16 < 0.01 19 141235 0.01 < 0.01 9 103343 4.20 < 0.01 20 141307 4.37 0.07 10 110108 2.49 0.08 21 146024 < 0.01 < 0.01 11 111527 1.00 < 0.01 22 146025 < 0.01 < 0.01 23 112233B 2.53 < 0.01 2.4. Groundwater triazines results Table 4 presents the outcomes of herbicide analysis conducted on groundwater samples. Among the 23 monitoring bores examined, only bore 112233 exhibited traces of pesticides. Subsequently, a follow-up field survey was undertaken for this bore, treating the second sampling as an independent sample. Notably, no pesticides were detected during the second sampling of bore 112233. The reporting limit for triazines was approximately 0.1 µg/L, and the total concentration observed in this bore was 19.52 µg/L in August 2017. However, upon revisiting the location in April 2018, no traces of triazines were detected, as depicted in the table. Further laboratory analyses unveiled an excessive presence of coal attributed to the burning of agricultural paddocks situated approximately 800m away from the groundwater monitoring bore. Agricultural land burning is a common practice employed to clear remnants of previous crop plants. The resulting coal acts as active carbon, effectively adsorbing pollutants, including nutrients and herbicides. Table 4 Groundwater triazine concentrations [µg/L] N Bore ID Atrazine Hexazinone Metribuzin Prometryn Simazine Desisopropyl-atrazine Desethyl-atrazine 17 112233A 0.017 < 0.01 6.3 < 0.01 0.12 13 < 0.1 23 112233B < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 2.5. Wetlands nutrients results Table 5 illustrates the outcomes of nutrient analysis conducted in wetlands. The majority of nutrient concentrations were observed to fall below the threshold values delineated in the ANZECC/ARMCANZ ( 2000 ) wetlands water quality guidelines. For instance, Victorian guidelines specify threshold values of 0.04 mg/L for NOx and 0.015 mg/L for DRP in inland lakes (EPA, 2010 ). Apart from a few exceptions (Bull Rush, Lake Bookar, and Linlithgow), where DRP values slightly exceeded 0.015 mg/L, the phosphorus concentrations remained within acceptable limits. It is crucial to recognize that the limit of detection for nutrients was approximately 0.01 mg/L, and the results represent a single sampling point within the littoral zone. Given these constraints, caution is warranted when interpreting the nutrient concentration findings in wetlands. Table 5 Wetlands nutrients results [mg/L] Wetland NOx (mg/L) DRP (mg/L) Bull rush < 0.01 0.16 Buninjon Lake < 0.01 0.02 Cobden Terang Volcanic < 0.01 < 0.01 Dergholm Park < 0.01 < 0.01 Lake Bookar 0.04 0.47 Lake Kennedy < 0.01 0.09 Linlithgow < 0.01 0.22 Maroona Wetland 0.05 < 0.01 Rookies Hill 0.05 0.02 Yatmarone Wetland 0.02 < 0.01 Traces of the herbicides atrazine and simazine were identified in five wetlands. Atrazine was detected in Bull Rush, Lake Kennedy, and Dergholm Park, with concentrations of 0.049 µg/L, 0.064 µg/L, and 0.036 µg/L, respectively. Simazine, on the other hand, was found in Bull Rush, Lake Kennedy, Buninjon Lake, and Lake Bookar, with concentrations approximately at 0.16 µg/L, 1.2 µg/L, 0.064 µg/L, and 0.097 µg/L, respectively. A summary of atrazine and simazine presence in selected wetlands within the GH CMA is provided in Table 6 , with Lake Kennedy exhibiting the highest concentrations for both atrazine (0.064 µg/L) and simazine (1.2 µg/L). The AANZECC/ARMCANZ ( 2000 ) guidelines establish freshwater ecosystem thresholds of 13.0 µg/L for atrazine and 3.2 µg/L for simazine. All detected concentrations fell below these thresholds. However, it is important to exercise caution as the measurements were derived from single-point samples within the littoral zone. Among the wetlands surveyed, atrazine contamination was evident in 30%, while simazine was present in 40% of the wetlands. Table 6 Triazine detection in wetlands at the GH CMA, Victoria, Aus. (µg/L) Wetland Atrazine Hexazinone Metribuzin Prometryn Simazine Desisopropyl-atrazine Desethyl-atrazine Bull Rush 0.049 < 0.01 < 0.01 < 0.01 0.16 < 0.1 < 0.1 Lake Kennedy 0.064 < 0.01 < 0.01 < 0.01 1.2 < 0.1 < 0.1 Buninjon Lake < 0.01 < 0.01 < 0.01 < 0.01 0.064 < 0.1 < 0.1 Cobden Terang < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.1 < 0.1 Dergholm Park 0.036 < 0.01 < 0.01 < 0.01 < 0.01 < 0.1 < 0.1 Lake Bookar < 0.01 < 0.01 < 0.01 < 0.01 0.097 < 0.1 < 0.1 Linlithgow < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.1 < 0.1 Yatmarone < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.1 < 0.1 Rookie Hills < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 Maroona < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 < 0.1 3. Discussion This study reveals the impact of agricultural activities on groundwater within the GHC region. Among the 23 sampled bores, 65% (15 out of 23) exhibited NOx concentrations surpassing Australian guideline thresholds, while 43.47% (10 out of 23) exceeded the threshold values for DRP. Notably, Bore 112233 displayed notably high concentrations of total triazine herbicides, including atrazine, metribuzin, simazine, and desethyl-atrazine. Despite representing the 4.3 percentile of the sample size, its elevated triazine levels underscore its significance in assessing groundwater pollution dimensions. In terms of wetland ecosystems, nutrient levels were generally within acceptable limits, aligning with Victorian Lakes trigger values for nitrogen as NOx and phosphorus as DRP. However, herbicide contamination was observed, with atrazine detected in 30% (3 out of 10) of the wetlands and simazine in 40% (4 out of 10). It is worth noting that the wetland sampling methodology may not fully capture ecosystem-wide pesticide exposure, warranting further investigation into pesticide sources. The identification of nutrient and pesticide contamination in a single bore suggests the potential risk of aquifer pollution from agrochemicals. The fluctuating occurrence of pesticides in bore 112233 highlights the complexity of groundwater pollution dynamics, reflecting land management practices by farmers. Thus, further research is imperative to deepen our understanding of groundwater pollution trends in agricultural settings. Future investigations should focus on elucidating pesticide pathways to groundwater and wetlands at both regional and state levels, employing more comprehensive sampling and monitoring strategies. Addressing the aforementioned limitations underscores the necessity for improved groundwater risk assessment tools. 4. Materials and Methods 4.1. Study Area The Glenelg Hopkins Catchment Management Authority (GH CMA) is situated in the southwestern region of the Victorian State (Fig. 1 ), bordered by the Wimmera CMA to the north, the Corangamite CMA to the east, South Australia to the west, and the Tasman Sea to the south (CMA, 2013 ). For a comprehensive understanding of the study area and aquifer's hydrogeological configuration, please consult Cervantes-Servin et al. Groundwater depth in GH Victoria, Australia, varies seasonally, with the water table closer to the surface during winter and deeper in summer, typically ranging from 0.0m to 6.0m below the surface on average. The landscape across the 26,000 square kilometres of land is diverse, featuring prominent features like the Grampians National Park, the Flat Volcanic Plains, Central Highlands, and Dundas Tablelands (CMA, 2013 ; GH CMA, 2018 ). This area encompasses various land uses, including agriculture, water reservoirs, nature conservation areas, lakes, wetlands, energy production sites, and urban areas. Dominant crops in agriculture include canola, wheat, barley, oats, and winter pastures (Conboy et al., 2018 ). The GHC ranks among the most productive agricultural regions in Australia, being the fourth CMA nationwide and the top in Victoria for agricultural productivity. In the fiscal year 2017–2018, agricultural production revenue totalled approximately AU $ 2,184 million (GH CMA, 2018 ). 4.2. Groundwater monitoring bores We visited 33 sites, being most of them groundwater bores as seen in Fig. 2 . The GHC has more than 351 active groundwater monitoring bores according to the Groundwater Monitoring System of the State Observation Bore Network (SOBN) ( http://data.water.vic.gov.au/ ). In Fig. 2 we can see the location across the study site, to do this we covered the entire Grampians region across the 220 Kilometers length of the region. The State Monitoring Wells were overlaid onto the region map and clipped using ArcMap10.4. 4.3. Wetlands and groundwater sample collection Water samples were manually collected from wetlands during the period of 2017–2018. Sampling took place at the shoreline of each wetland and within the first 4.0 meters from the waterline. To obtain the samples, a sealed 500ml dark glass bottle was submerged into the water at a depth of 0.5 meters, and the lid was opened to allow water to fill the bottle without oxygen. The specific sampling locations for each wetland are detailed in Table 2 . The sampling objective was to gather water samples using simple equipment while still providing strong data of water quality. Samples were handled according to the protocols outlined in "A guide to the sampling and analysis of waters, wastewaters, soils and wastes" (EPA, 2000 ) and "Sampling and analysis of waters, wastewaters, soils and wastes" (EPA, 2009 ). 4.4. Groundwater Quality Sampling Groundwater quality samples were collected and preserved in 500ml dark glass bottles. For each bore, three 500ml bottles were filled with water and kept cool with ice during transportation. Upon arrival, the samples were stored at 4°C in a dark room until laboratory analysis. The methodology employed for groundwater bore sampling followed the low flow groundwater sampling technique. This method utilized a pneumatic low flow pump (Sample Pro–Micropurge Portable Pump), a water quality multiparameter device (YSI Pro), and a 2.0L probe. The pump was activated using a pneumatic compressor and air controller. Parameters such as pH, temperature, and conductivity were stabilized to ensure accurate groundwater flow. Samples were extracted from the bores in accordance with the Victorian groundwater sampling guidelines (EPA, 2000 ). The samples were dispatched to accredited laboratories in Melbourne, Victoria, for analysis. The National Measurement Institute (NMI) conducted the analysis for the initial groundwater sampling campaign, while the Department of Industry, Innovation, and Science at The Australian Government and the Australian Laboratory Services (ALS) conducted the analysis for the subsequent groundwater sampling campaign. The samples underwent testing for nitrogen as NOx (NO 2 - and NO 3 -) and phosphorus as dissolved reactive phosphorus (DRP) using the discrete analyser method. Additionally, the samples were examined for the triazine herbicide suite, comprising atrazine, hexazinone, metribuzin, prometrym, simazine, desisopropyl atrazine, and desisopropyl atrazine. Liquid chromatography was employed to detect the presence of triazine herbicides. The reporting limit for NOx and DRP was 0.01 mg/L, while the reporting limit for the triazine suite was 0.01 µg/L. Declarations Acknowledgments This research was supported by Melbourne Water, Melbourne School of Engineering at The University of Melbourne, RMIT School of Science at The Royal Melbourne Institute of Technology, and the "Consejo Nacional de Ciencia y Tecnología CONACYT-Mexico" under the International Postgraduate Scholarship Program. We also acknowledge the farmers support and aid at the GH region during this investigation. Author contributions A. I. C-S.: Conceptualization; data analysis; funding acquisition; investigation; methodology; resources; writing original draft; review and editing; M. A.: Conceptualization; data analysis; funding acquisition; methodology; resources; supervision; review and editing; J. M.: Data analysis, methodology; V. P.: Conceptualization; data analysis; funding acquisition; methodology; resources; fieldwork supervision, laboratory work supervision; review and editing. By this means, we the authors give legal consent for the publication of this research. Funding This research was sponsored by Melbourne Water, Melbourne School of Engineering at The University of Melbourne, The RMIT School of Science at The Royal Melbourne Institute of Technology and The Mexican Council of Science and Technology “Consejo Nacional de Ciencia y Tecnologia (CONACYT)” under the international postgraduate scholarship program. Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Additional information Correspondence and requests for materials should be addressed to A. I. C-S. Competing interests: The authors declare no competing interests. References Alister, C. A., Gomez, P. A., Rojas, S., et al. (2009). Pendimethalin and oxyfluorfen degradation under two irrigation conditions over four years application. Journal of Environmental Science and Health, Part B, 44 (4), 337–343. doi: 10.1080/03601230902800986 ANZECC/ARMCANZ. (2000). 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AMBIO: A Journal of the Human Environment, 31 (2), 102–112. doi: 10.1579/0044-7447-31.2.102 Raisin, G., Bartley, J., & Croome, R. (1999). Groundwater influence on the water balance and nutrient budget of a small natural wetland in Northeastern Victoria, Australia. Ecological Engineering, 12 (1–2), 133–147. doi: 10.1016/s0925-8574(98)00059-7 Rojíčková, R., & Maršálek, B. (1999). Selection and sensitivity comparisons of algal species for toxicity testing. Chemosphere, 38 (14), 3329–3338. Rose, G., & Kibria, G. (2006). Pesticide Monitoring in Goulburn-Murray Water’s irrigation Supply Channels Covering the Six Irrigation Areas (2004–2005 Irrigation Season Study Report). In: Department of Primary Industries, Victoria, Australia. Schäfer, R. B., van den Brink, P. J., & Liess, M. (2011). Impacts of pesticides on freshwater ecosystems. Ecological impacts of toxic chemicals, 111–137. Sengupta, P., & Banerjee, R. (2014). Environmental toxins: Alarming impacts of pesticides on male fertility. Human & Experimental Toxicology, 33 (10), 1017. Retrieved from https://ezp.lib.unimelb.edu.au/login?url=https://search.ebscohost.com/login. aspx?direct=true&db=edb&AN=98895730&site=eds-live&scope=site SKM. (1995). Summary of 1994/95 pesticide sampling program (Groundwater Report No. 37). Retrieved from Victoria, Australia: SKM. (2002). Goulburn-Murray water sediment toxicants - Biocide and metal levels in drain sediments of the Shepparton irrigation region . Retrieved from Victoria, Australia: Steinheimer, T. R., Ross, L. J., & Spittler, T. D. (2000). Agrochemical Movement: Perspective and Scale-of-Study Overview. In Agrochemical Fate and Movement (Vol. 751, pp. 2–18): American Chemical Society. Swan, S. H. (2006). Semen quality in fertile US men in relation to geographical area and pesticide exposure. International Journal of Andrology, 29 (1), 62–68. doi: 10.1111/j.1365-2605.2005.00620.x US EPA. (2001). Oxyfluorfen: toxicology chapter for RED. Pesticides and toxic substances. US Environmental Protection Agency Office of Prevention . Retrieved from Washington, D.C.: Victoria, A. (2019). The Victorian Land Use Information System . Retrieved from: https://vro.agriculture.vic.gov.au/dpi/vro/vrosite.nsf/pages/vluis Victoria, R. R. (2019, May 30). [Road herbicides furniture list 2019]. Watkins, K. L., Bauld, J., & Ivkovic, K. M. (1999). A groundwater quality assessment of the Goulburn Catchment Victoria: Kyabram-Tongala . Canberra: Bureau of Rural Sciences. Wenig, D. (1997). Pesticide contamination of shallow aquifers at Ardmona, Girgarre and Kyvalley, Shepparton Irrigation Region, Victoria : University of Melbourne, School of Earth Sciences. Wightwick, A., & Allinson, G. (2007). Pesticide residues in Victorian waterways: a review. Australasian Journal of Ecotoxicology, 13 (3), 91. Yen, J.-H., Sheu, W.-S., & Wang, Y.-S. (2003). Dissipation of the herbicide oxyfluorfen in subtropical soils and its potential to contaminate groundwater. Ecotoxicology and environmental safety, 54 (2), 151–156. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4361284","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":343180346,"identity":"11d872a4-3175-48d0-9ee2-3397ccda75f3","order_by":0,"name":"Adrian Ixcoatl Cervantes‑Servin","email":"data:image/png;base64,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","orcid":"","institution":"The University of Melbourne","correspondingAuthor":true,"prefix":"","firstName":"Adrian","middleName":"Ixcoatl","lastName":"Cervantes‑Servin","suffix":""},{"id":343180347,"identity":"d48bef8d-68b8-4242-a59c-a5a326a2988b","order_by":1,"name":"Meenakshi Arora","email":"","orcid":"","institution":"The University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Meenakshi","middleName":"","lastName":"Arora","suffix":""},{"id":343180348,"identity":"d4a55d52-f04b-4668-99ac-33cddaa55c5d","order_by":2,"name":"Jackie Myers","email":"","orcid":"","institution":"RMIT University","correspondingAuthor":false,"prefix":"","firstName":"Jackie","middleName":"","lastName":"Myers","suffix":""},{"id":343180349,"identity":"2269783a-e13f-425b-98fa-cea00654b35a","order_by":3,"name":"Vincent Pettigrove","email":"","orcid":"","institution":"RMIT University","correspondingAuthor":false,"prefix":"","firstName":"Vincent","middleName":"","lastName":"Pettigrove","suffix":""}],"badges":[],"createdAt":"2024-05-03 00:23:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4361284/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4361284/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63358080,"identity":"078d1bae-562f-413e-b3e3-f1d7ec625206","added_by":"auto","created_at":"2024-08-27 09:39:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":260599,"visible":true,"origin":"","legend":"\u003cp\u003eThe Glenelg Hopkins CMA, Victoria, Australia.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4361284/v1/6355421497df6237688724c8.png"},{"id":63358102,"identity":"f50a5c63-8822-4610-b03c-e83016fd80a4","added_by":"auto","created_at":"2024-08-27 09:39:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":295440,"visible":true,"origin":"","legend":"\u003cp\u003eSampling sites at the Glenelg Hopkins region. Victoria, Australia.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4361284/v1/b32daf5fd73661b32623cecb.png"},{"id":63358085,"identity":"2dfa416e-8883-4d98-affa-6f1cd4c62ec1","added_by":"auto","created_at":"2024-08-27 09:39:03","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":130675,"visible":true,"origin":"","legend":"\u003cp\u003eSelected groundwater monitoring bores\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4361284/v1/8c494a47b8b15b8d917879b2.jpg"},{"id":65239812,"identity":"4929cd01-dc32-4420-8baf-d94f2be0acd6","added_by":"auto","created_at":"2024-09-25 06:24:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1215740,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4361284/v1/1de50333-b24c-493e-b2bf-59cccc6a6e52.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Groundwater and wetlands contamination with pesticides and nutrients from farms in Victoria, Australia","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWater availability is crucial for the productivity of natural and agricultural ecosystems (Nemani et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), with groundwater quality and quantity being vital for human development and sustaining groundwater-dependent ecosystems (Eamus et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In regions like Victoria, Australia, intensive agriculture poses contamination risks to both surface water and groundwater. Triazine herbicides, extensively used on canola crops and for governmental landscaping and road maintenance, are among the key pollutants (Regional Roads Victoria, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These pesticides directly threaten various aquatic organisms and have significant adverse effects on human health (Sch\u0026auml;fer et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Cohen, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sengupta and Banerjee, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Swan, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Atrazine, a commonly used herbicide, has been linked to reduced sperm quality in small mammals and embryonic toxicity (Feyzi Dehkhargani et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Bigsby et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Despite being permitted in Australia and Canada, atrazine and its mixtures are banned in the European Union (European Commission, 2004), highlighting the need to understand pesticide mobility and impacts (Kearney and Helling, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1982\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Glenelg Hopkins Catchment (GHC), spanning over 26,000 km2, is predominantly used for agriculture, with 80% allocated to agricultural activities (VLUIS, 2017). While vital for Australian agriculture (GH CMA, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), it hosts ecologically significant wetlands like the Victorian Western Districts Lakes (DNRE, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2002b\u003c/span\u003e), serving as habitats for threatened species (CMA, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Some wetlands rely on groundwater, making them susceptible to fluctuations in quality (GH CMA, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Despite their ecological significance, there's a dearth of research on the impact of agricultural practices on groundwater and wetlands within this catchment. Although some studies explored groundwater nutrients' effects on wetlands, inconclusive results were attributed to small sample sizes (Raisin, Bartley, and Croome, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Notably, the Victorian Strategic Direction Statement overlooks agricultural pollution in groundwater as a threat to wetlands.\u003c/p\u003e \u003cp\u003eOver the past two decades, triazine-based products' use in Victorian agriculture has surged, particularly with canola production (VLUIS). Multiple herbicide and fungicide applications are made throughout the cropping season, emphasizing reliance on these chemicals for pest management. Herbicides recommended by Regional Roads Victoria for road conservation purposes also pose risks to aquatic ecosystems, jeopardizing wetlands and contributing to algal blooms (Rabalais, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The active chemical ingredients of these herbicides are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCommercial herbicides with their chemical active ingredients (Conboy, Jhonson, Mclean et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAltiplano\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTriflur\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAtradex/\u003c/p\u003e \u003cp\u003eAtrazine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUltra\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAvadex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBurst\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eButisan\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClomazone,\u003c/p\u003e \u003cp\u003eNapropamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrifluralin,\u003c/p\u003e \u003cp\u003eLiquid hydrocarbon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAtrazine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePotassium salt of glyphosate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTriallate,\u003c/p\u003e \u003cp\u003eLiquid\u003c/p\u003e \u003cp\u003eHydrocarbon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePropyzamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMetazachlor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDespite sporadic efforts, studies investigating pesticide and nutrient pollution in Victoria are scarce. Most pesticide studies in groundwater date back to before 2007, necessitating updated assessments given escalating pesticide usage trends. Recent reviews identified atrazine, simazine, chlorpyriphos, and DDT as commonly detected pesticides in Victoria, reflecting international trends like New Zealand's national pesticide survey. However, nutrient data gaps exacerbate pesticide contamination assessment challenges. Financial and logistical constraints, coupled with the absence of specific guidelines for groundwater pesticide surveys, hinder robust assessments. Despite acknowledgments of the need for hydrogeological risk assessments, the lack of comprehensive guidelines for estimating aquifer vulnerability underscores the need for standardized methodologies.\u003c/p\u003e \u003cp\u003eThis study aims to assess agriculture's impact on groundwater quality in shallow aquifers and wetlands within the study area. Water samples from high, medium, and low-risk zones were analyzed for triazine herbicides, nitrogen, phosphorus, pH, temperature, and electrical conductivity.\u003c/p\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Sample size\u003c/h2\u003e \u003cp\u003eWe identified a total of 47 monitoring bores and 10 wetlands for our study. However, out of the 47 selected monitoring bores, 24 were found to be inaccessible due to various reasons, such as being situated on private land, having an internal diameter less than 60mm, or being physically inaccessible. Therefore, only 23 bores were accessible for testing. The findings from the field survey are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample size, the GH CMA\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"1\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample size and total monitoring bores\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e47 Total sites visited\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24 Bores were inaccessible or with no water\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17 Bores visited in the first field survey\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6 Bores were sampled in the second field survey\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 Wetlands\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAreas with the lowest vulnerability values were observed in the Grampians National Park and the eastern region of the study area, encompassing areas between Casterton, Coleraine, and Merino. Conversely, the most vulnerable regions were situated along the ocean side and in the area between the Grampians, Dunkeld, Ararat, and Skipton. It is noteworthy that this latter region also serves as the primary agricultural production hub within the catchment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Groundwater monitoring bores and wetlands selection\u003c/h2\u003e \u003cp\u003eAfter filtering the water from the SOBN monitoring bores, we identified 351 active monitoring bores suitable for testing. Overlaying the land use map with the SOBN map aided in identifying areas and monitoring bores susceptible to agricultural pollution, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Wetlands were selected based on the land use map, which delineated areas designated for canola cropping. Consequently, a total of 23 bores and 10 wetlands were selected across the GHC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Groundwater nutrient results\u003c/h2\u003e \u003cp\u003eGroundwater samples underwent analysis to determine the concentrations of NOx and DRP, serving as pollution indicators. The findings revealed elevated pollution levels at several bore locations. NOx concentrations ranged from 0.04 mg/L to 51.6 mg/L, with bore 112233 exhibiting the highest concentration, surpassing the Australian threshold value for nitrogen as NOx in freshwater (0.04 mg/L). Similarly, DRP concentrations varied from 0.015 mg/L to 0.30 mg/L, with bore 112233 also recording the highest concentration, exceeding the Australian trigger value of 0.015 mg/L specified for slightly disturbed ecosystems in lowland river ecosystems, as outlined in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e of the ANZECC/ARMCANZ (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) guidelines. These outcomes indicate a considerable proportion of bores exhibiting NOx and DRP pollution concentrations above threshold values, signifying a potential risk of groundwater contamination. Bore 98253, situated outside the study area in a confined aquifer, was excluded from linear correlation analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults for NOx and DRP in GW bores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBore ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNOx\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDRP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBore ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNOx\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDRP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e111528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e111530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e111690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e111696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e112232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e112233A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e51.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e112237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e141235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e141307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e110108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e146024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e146025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e112233B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Groundwater triazines results\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the outcomes of herbicide analysis conducted on groundwater samples. Among the 23 monitoring bores examined, only bore 112233 exhibited traces of pesticides. Subsequently, a follow-up field survey was undertaken for this bore, treating the second sampling as an independent sample. Notably, no pesticides were detected during the second sampling of bore 112233. The reporting limit for triazines was approximately 0.1 \u0026micro;g/L, and the total concentration observed in this bore was 19.52 \u0026micro;g/L in August 2017. However, upon revisiting the location in April 2018, no traces of triazines were detected, as depicted in the table. Further laboratory analyses unveiled an excessive presence of coal attributed to the burning of agricultural paddocks situated approximately 800m away from the groundwater monitoring bore. Agricultural land burning is a common practice employed to clear remnants of previous crop plants. The resulting coal acts as active carbon, effectively adsorbing pollutants, including nutrients and herbicides.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGroundwater triazine concentrations [\u0026micro;g/L]\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBore ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAtrazine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHexazinone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMetribuzin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePrometryn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSimazine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDesisopropyl-atrazine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDesethyl-atrazine\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112233A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112233B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Wetlands nutrients results\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the outcomes of nutrient analysis conducted in wetlands. The majority of nutrient concentrations were observed to fall below the threshold values delineated in the ANZECC/ARMCANZ (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) wetlands water quality guidelines. For instance, Victorian guidelines specify threshold values of 0.04 mg/L for NOx and 0.015 mg/L for DRP in inland lakes (EPA, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Apart from a few exceptions (Bull Rush, Lake Bookar, and Linlithgow), where DRP values slightly exceeded 0.015 mg/L, the phosphorus concentrations remained within acceptable limits. It is crucial to recognize that the limit of detection for nutrients was approximately 0.01 mg/L, and the results represent a single sampling point within the littoral zone. Given these constraints, caution is warranted when interpreting the nutrient concentration findings in wetlands.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWetlands nutrients results [mg/L]\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWetland\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNOx\u003c/p\u003e \u003cp\u003e(mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDRP\u003c/p\u003e \u003cp\u003e(mg/L)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBull rush\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuninjon Lake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobden Terang Volcanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDergholm Park\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLake Bookar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLake Kennedy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLinlithgow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaroona Wetland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRookies Hill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYatmarone Wetland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTraces of the herbicides atrazine and simazine were identified in five wetlands. Atrazine was detected in Bull Rush, Lake Kennedy, and Dergholm Park, with concentrations of 0.049 \u0026micro;g/L, 0.064 \u0026micro;g/L, and 0.036 \u0026micro;g/L, respectively. Simazine, on the other hand, was found in Bull Rush, Lake Kennedy, Buninjon Lake, and Lake Bookar, with concentrations approximately at 0.16 \u0026micro;g/L, 1.2 \u0026micro;g/L, 0.064 \u0026micro;g/L, and 0.097 \u0026micro;g/L, respectively. A summary of atrazine and simazine presence in selected wetlands within the GH CMA is provided in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, with Lake Kennedy exhibiting the highest concentrations for both atrazine (0.064 \u0026micro;g/L) and simazine (1.2 \u0026micro;g/L).\u003c/p\u003e \u003cp\u003eThe AANZECC/ARMCANZ (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) guidelines establish freshwater ecosystem thresholds of 13.0 \u0026micro;g/L for atrazine and 3.2 \u0026micro;g/L for simazine. All detected concentrations fell below these thresholds. However, it is important to exercise caution as the measurements were derived from single-point samples within the littoral zone. Among the wetlands surveyed, atrazine contamination was evident in 30%, while simazine was present in 40% of the wetlands.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTriazine detection in wetlands at the GH CMA, Victoria, Aus. (\u0026micro;g/L)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWetland\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAtrazine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHexazinone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMetribuzin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePrometryn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSimazine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDesisopropyl-atrazine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDesethyl-atrazine\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBull Rush\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLake Kennedy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuninjon Lake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobden Terang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDergholm Park\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLake Bookar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLinlithgow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYatmarone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRookie Hills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaroona\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eThis study reveals the impact of agricultural activities on groundwater within the GHC region. Among the 23 sampled bores, 65% (15 out of 23) exhibited NOx concentrations surpassing Australian guideline thresholds, while 43.47% (10 out of 23) exceeded the threshold values for DRP. Notably, Bore 112233 displayed notably high concentrations of total triazine herbicides, including atrazine, metribuzin, simazine, and desethyl-atrazine. Despite representing the 4.3 percentile of the sample size, its elevated triazine levels underscore its significance in assessing groundwater pollution dimensions.\u003c/p\u003e \u003cp\u003eIn terms of wetland ecosystems, nutrient levels were generally within acceptable limits, aligning with Victorian Lakes trigger values for nitrogen as NOx and phosphorus as DRP. However, herbicide contamination was observed, with atrazine detected in 30% (3 out of 10) of the wetlands and simazine in 40% (4 out of 10). It is worth noting that the wetland sampling methodology may not fully capture ecosystem-wide pesticide exposure, warranting further investigation into pesticide sources.\u003c/p\u003e \u003cp\u003eThe identification of nutrient and pesticide contamination in a single bore suggests the potential risk of aquifer pollution from agrochemicals. The fluctuating occurrence of pesticides in bore 112233 highlights the complexity of groundwater pollution dynamics, reflecting land management practices by farmers. Thus, further research is imperative to deepen our understanding of groundwater pollution trends in agricultural settings.\u003c/p\u003e \u003cp\u003eFuture investigations should focus on elucidating pesticide pathways to groundwater and wetlands at both regional and state levels, employing more comprehensive sampling and monitoring strategies. Addressing the aforementioned limitations underscores the necessity for improved groundwater risk assessment tools.\u003c/p\u003e"},{"header":"4. Materials and Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Study Area\u003c/h2\u003e \u003cp\u003eThe Glenelg Hopkins Catchment Management Authority (GH CMA) is situated in the southwestern region of the Victorian State (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e), bordered by the Wimmera CMA to the north, the Corangamite CMA to the east, South Australia to the west, and the Tasman Sea to the south (CMA, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). For a comprehensive understanding of the study area and aquifer's hydrogeological configuration, please consult Cervantes-Servin et al. Groundwater depth in GH Victoria, Australia, varies seasonally, with the water table closer to the surface during winter and deeper in summer, typically ranging from 0.0m to 6.0m below the surface on average. The landscape across the 26,000 square kilometres of land is diverse, featuring prominent features like the Grampians National Park, the Flat Volcanic Plains, Central Highlands, and Dundas Tablelands (CMA, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; GH CMA, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This area encompasses various land uses, including agriculture, water reservoirs, nature conservation areas, lakes, wetlands, energy production sites, and urban areas. Dominant crops in agriculture include canola, wheat, barley, oats, and winter pastures (Conboy et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The GHC ranks among the most productive agricultural regions in Australia, being the fourth CMA nationwide and the top in Victoria for agricultural productivity. In the fiscal year 2017\u0026ndash;2018, agricultural production revenue totalled approximately AU\u003cspan\u003e$\u003c/span\u003e2,184\u0026nbsp;million (GH CMA, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Groundwater monitoring bores\u003c/h2\u003e \u003cp\u003eWe visited 33 sites, being most of them groundwater bores as seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The GHC has more than 351 active groundwater monitoring bores according to the Groundwater Monitoring System of the State Observation Bore Network (SOBN) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://data.water.vic.gov.au/\u003c/span\u003e\u003cspan address=\"http://data.water.vic.gov.au/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). In Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e we can see the location across the study site, to do this we covered the entire Grampians region across the 220 Kilometers length of the region. The State Monitoring Wells were overlaid onto the region map and clipped using ArcMap10.4.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Wetlands and groundwater sample collection\u003c/h2\u003e \u003cp\u003eWater samples were manually collected from wetlands during the period of 2017\u0026ndash;2018. Sampling took place at the shoreline of each wetland and within the first 4.0 meters from the waterline. To obtain the samples, a sealed 500ml dark glass bottle was submerged into the water at a depth of 0.5 meters, and the lid was opened to allow water to fill the bottle without oxygen. The specific sampling locations for each wetland are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The sampling objective was to gather water samples using simple equipment while still providing strong data of water quality. Samples were handled according to the protocols outlined in \"A guide to the sampling and analysis of waters, wastewaters, soils and wastes\" (EPA, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and \"Sampling and analysis of waters, wastewaters, soils and wastes\" (EPA, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Groundwater Quality Sampling\u003c/h2\u003e \u003cp\u003eGroundwater quality samples were collected and preserved in 500ml dark glass bottles. For each bore, three 500ml bottles were filled with water and kept cool with ice during transportation. Upon arrival, the samples were stored at 4\u0026deg;C in a dark room until laboratory analysis.\u003c/p\u003e \u003cp\u003eThe methodology employed for groundwater bore sampling followed the low flow groundwater sampling technique. This method utilized a pneumatic low flow pump (Sample Pro\u0026ndash;Micropurge Portable Pump), a water quality multiparameter device (YSI Pro), and a 2.0L probe. The pump was activated using a pneumatic compressor and air controller. Parameters such as pH, temperature, and conductivity were stabilized to ensure accurate groundwater flow. Samples were extracted from the bores in accordance with the Victorian groundwater sampling guidelines (EPA, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe samples were dispatched to accredited laboratories in Melbourne, Victoria, for analysis. The National Measurement Institute (NMI) conducted the analysis for the initial groundwater sampling campaign, while the Department of Industry, Innovation, and Science at The Australian Government and the Australian Laboratory Services (ALS) conducted the analysis for the subsequent groundwater sampling campaign. The samples underwent testing for nitrogen as NOx (NO\u003csup\u003e2\u003c/sup\u003e- and NO\u003csup\u003e3\u003c/sup\u003e-) and phosphorus as dissolved reactive phosphorus (DRP) using the discrete analyser method. Additionally, the samples were examined for the triazine herbicide suite, comprising atrazine, hexazinone, metribuzin, prometrym, simazine, desisopropyl atrazine, and desisopropyl atrazine. Liquid chromatography was employed to detect the presence of triazine herbicides. The reporting limit for NOx and DRP was 0.01 mg/L, while the reporting limit for the triazine suite was 0.01 \u0026micro;g/L.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by Melbourne Water, Melbourne School of Engineering at The University of Melbourne, RMIT School of Science at The Royal Melbourne Institute of Technology, and the \u0026quot;Consejo Nacional de Ciencia y Tecnolog\u0026iacute;a CONACYT-Mexico\u0026quot; under the International Postgraduate Scholarship Program. We also acknowledge the farmers support and aid at the GH region during this investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. I. C-S.: Conceptualization; data analysis; funding acquisition; investigation; methodology; resources; writing original draft; review and editing; M. A.: Conceptualization; data analysis; funding acquisition; methodology; resources; supervision; review and editing; J. M.: Data analysis, methodology; V. P.: Conceptualization; data analysis; funding acquisition; methodology; resources; fieldwork supervision, laboratory work supervision; review and editing. By this means, we the authors give legal consent for the publication of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was sponsored by Melbourne Water, Melbourne School of Engineering at The University of Melbourne, The RMIT School of Science at The Royal Melbourne Institute of Technology and The Mexican Council of Science and Technology \u0026ldquo;Consejo Nacional de Ciencia y Tecnologia (CONACYT)\u0026rdquo; under the international postgraduate scholarship program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand requests for materials should be addressed to A. I. C-S.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlister, C. A., Gomez, P. A., Rojas, S., et al. (2009). Pendimethalin and oxyfluorfen degradation under two irrigation conditions over four years application. Journal of Environmental Science and Health, Part B, \u003cem\u003e44\u003c/em\u003e(4), 337\u0026ndash;343. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/03601230902800986\u003c/span\u003e\u003cspan address=\"10.1080/03601230902800986\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eANZECC/ARMCANZ. (2000). \u003cem\u003eAustralian and New Zealand Guidelines for Fresh and Marine Water Quality\u003c/em\u003e. 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Ecotoxicology and environmental safety, \u003cem\u003e54\u003c/em\u003e(2), 151\u0026ndash;156.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pesticides, nutrients, triazines, contamination, groundwater, wetlands","lastPublishedDoi":"10.21203/rs.3.rs-4361284/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4361284/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntensive farming in regions like the Glenelg Hopkins, Victoria, Australia, leads to substantial usage of pesticides and nutrients, posing the risk of agrochemical pollution to groundwater and wetlands. This study estimates the extent of pollution in aquifers and wetlands in the agricultural region. Tests were conducted for triazines (atrazine, hexazinone, metribuzin, prometrym, simazine, desisopropyl-atrazine, and desethyl-atrazine), nitrogen and phosphorus in 23 groundwater monitoring bores susceptible to agricultural pollution and ten nearby wetlands. Results indicated that one bore exhibited elevated pesticide levels, with a total concentration of 19.43 \u0026micro;g/L. Nitrogen and phosphorus were detected in most groundwater bores with concentrations below 51.6 mg/L and 0.30 mg/L, respectively. Compound Atrazine was found in three wetlands below 0.064 \u0026micro;g/L, while simazine was detected in four wetlands below 1.2 \u0026micro;g/L. The study suggests that although low pesticide levels were observed in wetlands, nutrient contamination is prevalent in the aquifer at the study site. Further investigation is necessary to comprehend the impacts of pesticides and nutrients on groundwater and wetland ecosystems. These findings emphasize the importance of ongoing monitoring and research to mitigate the adverse effects of intensive agricultural practices on groundwater and wetlands, thus, holding significant implications for policymakers and researchers.\u003c/p\u003e","manuscriptTitle":"Groundwater and wetlands contamination with pesticides and nutrients from farms in Victoria, Australia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-27 09:38:56","doi":"10.21203/rs.3.rs-4361284/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1531a753-3884-4bff-9b04-6626aaefc339","owner":[],"postedDate":"August 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":36360481,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry/Environmental monitoring"},{"id":36360482,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry/Geochemistry"},{"id":36360483,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry/Pollution remediation"},{"id":36360484,"name":"Physical sciences/Chemistry/Environmental chemistry/Geochemistry"},{"id":36360485,"name":"Physical sciences/Chemistry/Environmental chemistry/Pollution remediation"},{"id":36360486,"name":"Earth and environmental sciences/Limnology"},{"id":36360487,"name":"Earth and environmental sciences/Solid earth sciences/Geochemistry"},{"id":36360488,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry"},{"id":36360489,"name":"Earth and environmental sciences/Environmental sciences/Environmental impact"}],"tags":[],"updatedAt":"2024-09-25T06:23:54+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-27 09:38:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4361284","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4361284","identity":"rs-4361284","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}