Water Quality In Ireland Research Articles

Agriculture and Water Quality in Ireland: New Ideas for Policy

Agriculture and Water Quality in Ireland: New Ideas for Policy

Assessing the impact of COVID-19 lockdown on surface water quality in Ireland using advanced Irish water quality index (IEWQI) model

The COVID-19 pandemic has significantly impacted various aspects of life, including environmental conditions. Surface water quality (WQ) is one area affected by lockdowns imposed to control the virus's spread. Numerous recent studies have revealed the considerable impact of COVID-19 lockdowns on surface WQ. In response, this research aimed to assess the impact of COVID-19 lockdowns on surface water quality in Ireland using an advanced WQ model. To achieve this goal, six years of water quality monitoring data from 2017 to 2022 were collected for nine water quality indicators in Cork Harbour, Ireland, before, during, and after the lockdowns. These indicators include pH, water temperature (TEMP), salinity (SAL), biological oxygen demand (BOD5), dissolved oxygen (DOX), transparency (TRAN), and three nutrient enrichment indicators—dissolved inorganic nitrogen (DIN), molybdate reactive phosphorus (MRP), and total oxidized nitrogen (TON). The results showed that the lockdown had a significant impact on various WQ indicators, particularly pH, TEMP, TON, and BOD5. Over the study period, most indicators were within the permissible limit except for MRP, with the exception of during COVID-19. During the pandemic, TON and DIN decreased, while water transparency significantly improved. In contrast, after COVID-19, WQ at 7% of monitoring sites significantly deteriorated. Overall, WQ in Cork Harbour was categorized as "good," "fair," and "marginal" classes over the study period. Compared to temporal variation, WQ improved at 17% of monitoring sites during the lockdown period in Cork Harbour. However, no significant trend in WQ was observed. Furthermore, the study analyzed the advanced model's performance in assessing the impact of COVID-19 on WQ. The results indicate that the advanced WQ model could be an effective tool for monitoring and evaluating lockdowns' impact on surface water quality. The model can provide valuable information for decision-making and planning to protect aquatic ecosystems.

Community-funded behavioural change initiatives: Water quality in Ireland

Mitigating the deterioration in water quality is contingent on changing human behaviours. Community-based behavioural change initiatives are one approach to changing people's actions, which is distinct from many behavioural change programmes that target the actions of individuals. This paper examines a behavioural change initiative aiming to foster proactive community engagement in the management and protection of water catchments in Ireland. The initiative comprises a grant scheme for community groups to undertake a variety of activities to support improvements in water quality, ranging from education and awareness activities to physical interventions. The analysis finds that higher grant awards and a greater number of grant applications are positively associated with either a higher likelihood of engagement with public and private sector stakeholders or participation in the State's River Basin Management Plan process on improving water quality. While this demonstrates some success for the grant scheme, questions remain unanswered with respect to the efficacy of schemes like this. With limited quantitative data available both on the precise nature of interventions applied and measured target outcomes, it was not possible to discern what community group or project attributes are critical to the success of the grant scheme. This deficiency means that effectively replicating or scaling up successful projects like this will be practically challenging.

The Role of Volunteers and Citizen Scientists in Addressing Declining Water Quality in Irish River Catchments

Integrated Catchment Management (ICM) frames water management in Ireland to account for the complex hydrological, biophysical, and environmental interactions along with the political, socio-economic and cultural influences inherent in the management of river catchments. Despite a range of European Union (EU) Directives, national laws, policies, and incentives, the quality of water and biological diversity in Irish rivers is declining. In response, there has been an increased effort to involve local communities in ICM through a bottom-up, nature-based citizen science approach to activate local cooperation and environmental stewardship. This paper assembles 157 examples of citizen science water-based projects (48 in Ireland as of 2021) to appraise the position of community-led water monitoring in ICM. Notable differences found between the Irish and international programmes found a greater emphasis on habitat internationally, while a taxonomy focus was evident in Ireland despite a lower number of skilled volunteer activity-based citizen science projects. The continuing decline in water quality in Ireland, even with appropriate regulations, commendable governance changes, and expansion of citizen science, suggests more work is necessary before there will be successful ICM and improvements to river water quality.

Exploiting partially-labeled data in learning predictive clustering trees for multi-target regression: A case study of water quality assessment in Ireland

Many environmental problems give rise to predictive modeling tasks where several dependent variables need to be predicted simultaneousy from a given set of independent variables. When the target variables are numeric, the task at hand is called multi-target regression (MTR). An example task of this type is the assessment of quality of agricultural waters in Ireland according to three indicators: biological water quality, nitrogen concentration and phosphorus concentration.Multi-target regression models are typically learnt from labeled training examples, where the values of both the dependent variables (labels) and the independent variables are provided, in a setting known as supervised learning. Many different approaches to supervised multi-target regression have been developed, among which predictive clustering trees and ensembles thereof stand out due to their effectiveness and efficiency. Recently, these approaches have been extended to exploit not only labeled examples, but also unlabeled examples, where only the values of the independent variables are provided, a setting known as semi-supervised learning.In practice, training data can also contain partially labeled examples, where the values of some of the dependent variables are provided and others are missing (in addition to fully labeled examples where all target values are provided and completely unlabeled examples where no target values are provided). For the task of water quality assessment in Ireland, we encounter this kind of partially labeled data. Existing supervised and semi-supervised MTR approaches typically ignore partially labeled data.In this paper, we propose the use of semi-supervised predictive clustering trees for MTR that can handle partially labeled examples. We apply these to the task of assessment of water quality in Ireland, showing that better performance can be achieved if partially labeled examples are exploited, rather than discarded. We build both local models (collections of single-target models predicting each target separately) and global models (multi-target models simultaneously predicting all targets), showing that global models are both smaller and easier to interpret, and also overfit less (and have better performance) as compared to local models.

Livestock exclusion from watercourses: Policy effectiveness and implications

The deterioration of water quality in Ireland over the past thirty years and the nutrient losses from agriculture are of particular concern to policy makers. Agri-environmental schemes (AES) are designed to improve the environment and water quality. One of the more common AES measures is the exclusion of cattle from watercourses. Cattle exclusion provides a number of benefits such as reduction in nitrogen, phosphorus and sediment run-off, riverbank stability and improved vegetation cover and biodiversity. Using GIS methods a new national farm boundary spatial database SLIDE (Spatial Land Identification Database for Éire) is created utilising national administrative data and a spatial data storage model. This is the first examination of cattle exclusion and its cost effectiveness at the individual farm level across a national population of farms. Benefits are measured in the form of reduced in-stream faecal deposits. The spatial distribution of cost-effectiveness at the sub-catchment level highlights the differences between areas in terms of costs, benefits and extent. A cluster analysis is used to aggregate results. This information is utilised to undertake an ex-ante examination of the implications of a national policy to restrict cattle access to waterbodies for specific categories of farmers, under the EU Nitrates Directive. The analysis of the clusters show that due to the reduction of faecal deposition in watercourses, fencing on medium and high intensity farms is ∼20 % more cost effective relative to farms with lower livestock densities. This study makes an important contribution to the literature in broadening our understanding of the impacts of policy decision making at the individual farm level and also the costs and scale of AES measures at a national level.

Longitudinal evaluation of the impact of traditional rainbow trout farming on receiving water quality in Ireland.

In the context of future aquaculture intensification, a longitudinal ten-year evaluation of the current traditional rainbow trout production in Ireland was performed. Publically available and independent data obtained from local authorities were gathered and analysed. Inlet and outlet concentrations of parameters such as BOD5, ammonium, nitrite, dissolved oxygen and pH for four consecutive flow-through fish farms covering the four seasons over a ten-year period (2005–2015) were analysed. The objectives of the study were (i) to characterize the impact of each fish farm on water quality in function of their respective production and identify any seasonal variability, (ii) to quantify the cumulative impact of the four farms on the river quality and to check if the self-purification capacity of the river was enough to allow the river to reach back its background levels for the analysed parameters, (iii) to build a baseline study for Ireland in order to extrapolate as a dataset for expected climate change and production intensification. For most of the parameter analysed, no significant impact of the fish farming activity on water quality/river quality was observed. These results, the first ones generated in Ireland so far, will have to be completed by a survey on biodiversity and ecotoxicology and compared after production intensification and the likely future introduction of water treatment systems on the different sites.

Will recent improvements in estuarine water quality in Ireland be compromised by plans for increased agricultural production? A case study of the Blackwater estuary in southern Ireland

The environmental status of many European estuaries has improved in recent years as a result of the implementation of a range of different legislative measures. Better municipal waste water treatment and a reduction in the application of inorganic and organic fertiliser to agricultural lands are the main reasons for these improvements. It is anticipated, however, that the ending of the EU milk quota in 2015, and the proposed enlargement of the European dairy sector will lead to a market-driven increase in milk production through an increase in animal numbers and higher productivity. This new production is likely to lead to an increase in pressures with the potential to impact on the quality of surface waters, including estuarine waters. In this paper we focus on the Blackwater estuary in southern Ireland which has seen a marked improvement in water quality due to a reduction in riverine nutrient inputs of phosphorus and nitrogen. A bio-physical model is used to test nutrient-input scenarios likely to represent the range of nutrient loadings that may arise as a result of increased agricultural production. The outputs from these different scenarios are used to assess if recent improvements in estuarine water quality will be undermined or even negated by the proposed expansion of the Irish dairy sector. Appropriate management options to address these potential impacts are discussed.

A systematic map protocol: What evidence exists to link agricultural practices with ecological impacts for Irish waterbodies?

Increasing world population, changing consumption patterns, and the agri-food industry ambition for expansion will drive an increase in outputs from future Irish agriculture. This must be achieved within the context of the targets established within E.U. environmental directives, such as the Nitrates (91/676/EEC) and Water Framework Directives (2000/60/EC). How and if sustainable intensification can be achieved is unclear, with climate change and competition for land (e.g. bioenergy crops) increasing pressures on agriculture and the environment. The Environmental Protection Agency’s report, Ireland’s Environment, investigated the status of water quality and concluded agricultural diffuse and small point sources of pollution were the main cause of 50 % and 13 % of river and groundwater pollution, respectively (EPA, 2012). As a result of significant investment in research, there is now an understanding of the factors controlling the impact of agriculture on water quality in Ireland. However, in facing the challenges of sustainable intensification, climate change, and increasing demand for delivery of ecosystem services from rural environments, there is a need to determine to what extent existing research can provide answers to these challenges and what further research is required to balance water quality protection and agricultural production in the future. The objective of this systematic map protocol is to plan development of an evidence-base to inform recommendations for further research on mitigating the impact of agriculture on water quality in Ireland under future climate change and sustainable intensification. The primary question for this systematic map is: What evidence exists to link agricultural practices with ecological impacts in Irish waterbodies? This involves coding studies based on variables such as scale, methodology, chemical and ecological impacts, and location. Following an extensive search for relevant research documents, documents selected for inclusion in the systematic map will be implemented on a hierarchical basis, with documents first screened at title and abstract level and subsequently at full text level using predetermined selection criteria. Coding will include elements of critical appraisal (e.g. study length, study scale, and experimental design). A geographical map indicating where each study occurred will be linked to the database describing all studies included in the systematic map.

The effect of forest windrowing on physico-chemical water quality in Ireland

Windrowing is widely practised, across Europe and North America, in bole-only harvested coniferous forest plantations before replanting. Forest harvesting has been shown to significantly increase sediment and nutrient losses to watercourses in other studies but windrowing effects, which are as bad, have not been investigated in detail. To determine physico-chemical impacts on water quality and to help inform forest managers, the effects of windrowing were investigated in a headwater catchment. Water samples were collected from storm events pre- (PWR), during (DWR) and after windrowing (AWR). Total suspended solids (TSS), total phosphorus (TP), soluble reactive phosphorus (SRP), total ammonia, nitrate, stream discharge, water level and velocity were measured. Results showed that peak and flow weighted mean concentrations (FWMC) of TSS concentrations increased significantly during windrowing when compared to pre-windrowing concentrations. Peak TSS increased from 88mg/l (PWR) to 502mg/l (DWR) and decreased to 163mg/l (one year AWR) and 225mg/l (two years AWR). Peak and FWMC of TP also increased during windrowing when compared to pre-windrowing concentrations. Peak TP concentrations increased from 0.1mg/l (PWR) to 0.4mg/l (DWR) and decreased to 0.1mg/l (AWR). SRP and nitrate concentrations increased during windrowing when compared to pre-windrowing but remained low overall. TSS and TP concentrations were highest when flows greater than 0.3m3/s (exceeded 6.3% of time) were recorded in the channel. It was highlighted that high-resolution sampling of storm events is important, where precise measurements of windrowing-sourced outputs are required. Windrowing was shown to generate very high concentrations of TSS and TP, comparable to those recorded during harvesting. This research helps to identify potential impacts on physico-chemical water quality that arise during windrowing and demonstrates the need for measures to minimize impacts on surface waters as required by the EU Water Framework Directive and similar legislation elsewhere.

Assessment of the impact of traditional septic tank soakaway systems on water quality in Ireland.

One of the key threats to groundwater and surface water quality in Ireland is the impact of poorly designed, constructed or maintained on-site wastewater treatment systems. An extensive study was carried out to quantify the impact of existing sites on water quality. Six existing sites, consisting of a traditional septic tank and soakaway system, located in various ranges of subsoil permeabilities were identified and monitored to determine how well they function under varying subsoil and weather conditions. The preliminary results of the chemical and microbiological pollutant attenuation in the subsoil of the systems have been assessed and treatment performance evaluated, as well as impact on local surface water and groundwater quality. The source of any faecal contamination detected in groundwater, nearby surface water and effluent samples was confirmed by microbial source tracking. From this, it can be seen that the transport and treatment of percolate vary greatly depending on the permeability and composition of the subsoil.

Pathogen Sources Estimation and Scenario Analysis Using the Soil and Water Assessment Tool (SWAT)

ABSTRACT Concerns over water quality in Ireland have increased in recent years, in part due to the more frequent contamination of drinking water by pathogens such as Escherichia coli and Cryptosporidium. The objective of this study was to assess the use of SWAT for pathogen source estimation and to analyze the effects of various source scenarios on pathogen outputs in Irish catchments. Two agricultural catchments in Ireland susceptible to pathogen contamination of source water were the center of the SWAT model development with the primary focus on levels of E. coli in surface water. Model simulations used site and source specific information which was analyzed considering the total E. coli count for the simulation period (Fergus: January 2005–October 2006; Kilshanvey: January 2006–July 2007). Pathogen source estimation identified point sources as the most significant contributors to E. coli output with direct deposition the primary contributor (95%) in Kilshanvey and wastewater treatment plant outflow (89%) the main contributor in the Fergus catchment. A scenario analysis evaluated possible situations that may occur in study locations. The analysis indicated that restriction of livestock access to water sources and improved wastewater treatment would represent effective methods of improving water quality in both catchments.

AN EVALUATION OF THE ROLE OF EPA RESEARCH IN THE WATER FRAMEWORK DIRECTIVE IMPLEMENTATION IN IRELAND

AN EVALUATION OF THE ROLE OF EPA RESEARCH IN THE WATER FRAMEWORK DIRECTIVE IMPLEMENTATION IN IRELAND

Agriculture, Meteorology and Water Quality in Ireland: a Regional Evaluation of Pressures and Pathways of Nutrient Loss to Water

The main environmental impact of Irish agriculture on surface and ground water quality is the potential transfer of nutrients to water. Soil water dynamics mediate the transport of nutrients to water, and these dynamics in turn depend on agro-meteorological conditions, which show large variations between regions, seasons and years. In this paper we quantify and map the spatio-temporal variability of agro-meteorological factors that control nutrient pressures and pathways of nutrient loss. Subsequently, we evaluate their impact on the water quality of Irish rivers. For nitrogen, pressure and pathways factors coincide in eastern and southern areas, which is reflected in higher nitrate levels of the rivers in these regions. For phosphorus, pathway factors are most pronounced in north-western parts of the country. In south-eastern parts, high pressure factors result in reduced biological water quality. These regional differences require that farm practices be customised to reflect the local risk of nutrient loss to water. Where pathways for phosphorus loss are present almost year-round * as is the case in most of the north-western part of the country * build-up of pressures should be prevented, or ameliorated where already high. In south-eastern areas, spatio-temporal coincidence of nutrient pressures and pathways should be prevented, which poses challenges to grassland management.