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Diffuse Water Pollution Modeling, Monitoring and Mitigation

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A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".

Deadline for manuscript submissions: closed (30 September 2019) | Viewed by 10868

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Special Issue Editor

Dr. Andy Vinten

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Guest Editor

The James Hutton Institute, Aberdeen, United Kingdom
Interests: mitigation of sediment and P from arable farmland; cost-effectiveness analysis of diffuse pollution mitigation; use of turbidity as proxy for estimating sorbed pollutant loads

Special Issue Information

Dear Colleagues,

Diffuse water pollution can be defined as pollution that is “weather-driven”. As global efforts to reduce point source pollution have increased, the problem of diffuse pollution has emerged as a separate issue, requiring a very different set of mitigation tools. Weather-driven loads vary greatly over space and time. This makes monitoring of loads and identification of sources a challenge for instrumentation and data analysis. Apportionment of sources through modelling can help, but this presents challenges for both calibration and validation. The pollutants of concern include soluble and colloid-sorbed components, which influence public health, ecosystem function, and business viability. Targeted approaches to mitigation require the analysis of what will be cost-effective, and the polluter-pays principle does not easily lends itself to the regulation of diffuse pollution. Policy-makers need simple instruments effective in delivering water quality benefits to justify public expenditure. In short, the scientific and governance challenges facing those addressing this emerging issue are significant. This Special Issue invites authors across the international water science community to contribute their insights and experience to addressing this problem.

Dr. Andy Vinten
Guest Editor

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Keywords

water quality
eutrophication
bathing waters
drinking water
groundwater
sustainable drainage
best management practices
screening tools
Bayesian models
ecosystem services
high-frequency monitoring

Published Papers (4 papers)

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Research

15 pages, 4801 KiB

Open AccessArticle

An Appraisal of Potential for Sowing of Nasturtium officinale into Streams to Mitigate Nutrient Pollution in Eastern Scotland

by Andy Vinten and Patrick Bowden-Smith

Int. J. Environ. Res. Public Health 2020, 17(3), 895; https://doi.org/10.3390/ijerph17030895 - 31 Jan 2020

Cited by 3 | Viewed by 2051

Abstract

This study examines a farmer-led initiative to sow watercress (Nasturtium officinale) in field ditches. The objective was to assess the potential of this practice to mitigate summer nutrient loads in rivers. Two ditches—one seeded, the other unseeded—on a mixed-livestock farm in Eastern Scotland were monitored during the spring-summer of 2014–2016. The un-replicated trial design limited statistical analysis. However, changes in N and P concentrations along the two ditches were measured. In the watercress-seeded ditch, N retention of 0.092 g/m²/d (p < 0.001, SE = 0.020) and P retention of 0.0092 g/m²/d (p = 0.001, SE = 0.0028) occurred, while total organic C in the water increased along the ditch. Retention was close to zero for the unseeded ditch. The seeded ditch was also found to have more dry matter production and lower stream temperature. The impact of plastic covering (to increase spring temperature) on vegetation and nutrient removal was also assessed on replicate 5-m sections of the ditches. No significant impact on N and P removal was found; however, the release of C increased significantly in the plastic-covered sections. The rise in air temperature (up to > 30 °C) promoted a greater growth of opportunist species (nettle (Urtica), rush (Juncus), and grasses. These observations were used to make a simple assessment of the potential catchment scale impact of seeding watercress into first and second order streams in the nearby Lunan Water catchment. It was concluded that this could make a significant contribution to the reduction of nutrient loads. Full article

(This article belongs to the Special Issue Diffuse Water Pollution Modeling, Monitoring and Mitigation)

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24 pages, 5527 KiB

Open AccessArticle

An Assessment of the Performance of the PLUS+ Tool in Supporting the Evaluation of Water Framework Directive Compliance in Scottish Standing Waters

by David Donnelly, Rachel C. Helliwell, Linda May and Brian McCreadie

Int. J. Environ. Res. Public Health 2020, 17(2), 391; https://doi.org/10.3390/ijerph17020391 - 07 Jan 2020

Cited by 3 | Viewed by 2739

Abstract

Phosphorus is one of the main causes of waterbodies in Scotland being at less than good ecological status (GES) in terms of the water framework directive (WFD). In Scotland, there are more than 8000 standing waters, defined as lakes and reservoirs that have a surface area of more than 1 hectare. Only about 330 of these are monitored routinely to assess compliance with the WFD. The export coefficient tool PLUS+ (phosphorus land use and slope) has been developed to estimate total phosphorus (TP) concentrations in the unmonitored sites; modelled values are then compared to WFD target concentrations for high, good, moderate, poor, and bad status to assess compliance. These type-specific or site-specific targets are set by the regulatory authority and form part of a suite of physical, chemical, and ecological targets that are used to assess GES, all of which must be met. During development, the PLUS+ tool was applied to 323 monitored catchments and 7471 unmonitored catchments. The efficacy of the tool was assessed against TP concentrations observed in 2014 and found to perform well in the rural catchments. 51% of standing waters had the same modelled and observed WFD class (i.e., High, Good, Moderate, Poor, Bad), and a further 40% of standing waters had a modelled WFD class that was within one class of observed water quality. The tool performed less well in catchments with larger inputs of TP from urban sources (e.g., sewage). The greatest deviations between measured and modelled classes were explained by the shortage of information on wastewater treatment works, fish farms, migratory birds, levels of uncertainty in TP measurements, and the amount of in-lake re-cycling of P. The limitations of the tool are assessed using data from six well documented case study sites and recommendations for improving the model performance are proposed. Full article

(This article belongs to the Special Issue Diffuse Water Pollution Modeling, Monitoring and Mitigation)

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13 pages, 2420 KiB

Open AccessArticle

Assessing Risk of E. coli Resuspension from Intertidal Estuarine Sediments: Implications for Water Quality

by Adam J. Wyness, David M. Paterson, James E. V. Rimmer, Emma C. Defew, Marc I. Stutter and Lisa M. Avery

Int. J. Environ. Res. Public Health 2019, 16(18), 3255; https://doi.org/10.3390/ijerph16183255 - 05 Sep 2019

Cited by 4 | Viewed by 2992

Abstract

Estuarine sediments are a reservoir for faecal bacteria, such as E. coli, where they reside at greater concentrations and for longer periods than in the overlying water. Faecal bacteria in sediments do not usually pose significant risk to human health until resuspended into the water column, where transmission routes to humans are facilitated. The erosion resistance and corresponding E. coli loading of intertidal estuarine sediments was monitored in two Scottish estuaries to identify sediments that posed a risk of resuspending large amounts of E. coli. In addition, models were constructed in an attempt to identify sediment characteristics leading to higher erosion resistance. Sediments that exhibited low erosion resistance and a high E. coli loading occurred in the upper- and mid-reaches of the estuaries where sediments had higher organic content and smaller particle sizes, and arose predominantly during winter and autumn, with some incidences during summer. Models using sediment characteristics explained 57.2% and 35.7% of sediment shear strength and surface stability variance respectively, with organic matter content and season being important factors for both. However large proportions of the variance remained unexplained. Sediments that posed a risk of resuspending high amounts of faecal bacteria could be characterised by season and sediment type, and this should be considered in the future modelling of bathing water quality. Full article

(This article belongs to the Special Issue Diffuse Water Pollution Modeling, Monitoring and Mitigation)

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14 pages, 1431 KiB

Open AccessArticle

Modelling of Indicator Escherichia coli Contamination in Sentinel Oysters and Estuarine Water

by Saharuetai Jeamsripong and Edward R. Atwill

Int. J. Environ. Res. Public Health 2019, 16(11), 1971; https://doi.org/10.3390/ijerph16111971 - 04 Jun 2019

Cited by 7 | Viewed by 2818

Abstract

This study was performed to improve the ability to predict the concentrations of Escherichia coli in oyster meat and estuarine waters by using environmental parameters, and microbiological and heavy metal contamination from shellfish growing area in southern Thailand. Oyster meat (n = 144) and estuarine waters (n = 96) were tested for microbiological and heavy metal contamination from March 2016 to February 2017. Prevalence and mean concentrations of E. coli were 93.1% and 4.6 × 10³ most probable number (MPN)/g in oyster meat, and 78.1% and 2.2 × 10² MPN/100 mL in estuarine water. Average 7-day precipitation, ambient air temperature, and the presence of Salmonella were associated with the concentrations of E. coli in oyster meat (p < 0.05). Raw data (MPN/g of oyster meat and MPN/100 mL of estuarine water) and log-transformed data (logMPN/g of oyster meat and logMPN/100 mL of estuarine water) of E. coli concentrations were examined within two contrasting regression models. However, the more valid predictions were conducted using non-log transformed values. These findings indicate that non-log transformed data can be used for building more accurate statistical models in microbiological food safety, and that significant environmental parameters can be used as a part of a rapid warning system to predict levels of E. coli before harvesting oysters. Full article

(This article belongs to the Special Issue Diffuse Water Pollution Modeling, Monitoring and Mitigation)

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