Suchergebnisse

Decreased funding and shifting governmental priorities have resulted in a contraction of hydrometric measurement in many regions over the past two decades. Moreover, concerns exist with respect to appropriate data usage and (transboundary) exchange, in addition to the compatibility and extent of existing hydrometric datasets. These issues are undoubtedly magnified due to enhanced data demands and increased financial pressures on network managers, thus requiring new approaches to optimising the societal benefits and overall efficacy of hydrometric information for future socio-hydrological resilience. The current study employed a quantitative cross-sectional expert elicitation of 203 respondents to collate, analyse and assess hydrometric network users' opinions, knowledge and experience. Current usage patterns, perceived network strengths, requirements, and limitations have been identified and discussed within the context of hydrometric resilience in a changing social, economic and natural environment. Findings indicate that small (<30 km2) catchment data are most frequently employed in the Republic of Ireland, particularly with respect to extreme event prediction and flood management. Similarly, small catchments and areas characterised by previous/recent flooding were prioritised for resilience management via network amendment. Over half of those surveyed (50.5%) reported the current network as inadequate for their professional requirements. Conversely, respondents indicated network efficacy has improved (53.2%) or remained stable (26.6%) over the course of their professional career, however, improvements (as defined by individual respondents i.e. network density, data quality, data availability) have not occurred at a sufficient rate. User-defined efficacy (adequacy, resilience) was found to be a somewhat vague, multivariate concept, with no individual predictor identified, however, general data quality, network density, and urban catchment data were the most significant issues among respondents. A significant majority (85.4%) of respondents indicate that future resilience would be best achieved via network density amendment, with over 60% favouring geographically and/or categorically focused network increases, as opposed to more general national increases.

AbstractComplex, multihazard risks such as private groundwater contamination necessitate multiannual risk reduction actions including seasonal, weather‐based hazard evaluations. In the Republic of Ireland (ROI), high rural reliance on unregulated private wells renders behavior promotion a vital instrument toward safeguarding household health from waterborne infection. However, to date, pathways between behavioral predictors remain unknown while latent constructs such as extreme weather event (EWE) risk perception and self‐efficacy (perceived behavioral competency) have yet to be sufficiently explored. Accordingly, a nationwide survey of 560 Irish private well owners was conducted, with structural equation modeling (SEM) employed to identify underlying relationships determining key supply management behaviors. The pathway analysis (SEM) approach was used to model three binary outcomes: information seeking, post‐EWE action, and well testing behavior. Upon development of optimal models, perceived self‐efficacy emerged as a significant direct and/or indirect driver of all three behavior types—demonstrating the greatest indirect effect (β = −0.057) on adoption of post‐EWE actions and greatest direct (β = 0.222) and total effect (β = 0.245) on supply testing. Perceived self‐efficacy inversely influenced EWE risk perception in all three models but positively influenced supply awareness (where present). Notably, the presence of a vulnerable (infant and/or elderly) household member negatively influenced adoption of post‐EWE actions (β = −0.131, p = 0.016). Results suggest that residential and age‐related factors constitute key demographic variables influencing risk mitigation and are strongly mediated by cognitive variables—particularly self‐efficacy. Study findings may help contextualize predictors of private water supply management, providing a basis for future risk‐based water interventions.

Environmentally associated infectious diseases, including those driven by extreme weather events, represent a critical challenge for public health as their source and transmission are frequently sporadic and associated mechanisms often not well understood. Over the past decade, the Republic of Ireland (ROI) has persistently reported the highest incidence of confirmed verotoxigenic E. coli (VTEC) and cryptosporidiosis infection in the European Union. Moreover, recent climate projections indicate that the incidence, severity and timing of extreme rainfall events and flooding will increase dramatically over the next century, with Ireland forecast to be the second most affected European country with respect to the mean proportion of the population residing in flood-prone areas by 2100. This study aimed to assess the association(s) between potential flood risk exposure and the spatial occurrence of confirmed VTEC and cryptosporidiosis infection in Ireland over a 10-year period (2008-2017). In 2012, the Irish Office of Public Works (OPW) initiated the National Catchment Flood Risk Assessment and Management (CFRAM) Programme within the framework of the Flood Directive (2007/60/CE), with high-resolution flood maps produced for coastal and fluvial risks and three risk scenarios based on calculated return periods (low, medium and high probability). Small area identifiers (national census area centroids) were used to attach anonymised spatially referenced case data to CFRAM polygons using Geographical Information Systems (GIS) to produce an anonymised dataframe of confirmed infection events linked to geographically explicit flood risk attributes. Generalised linear modelling with binary link functions (infection presence/absence) were used to calculate probabilistic odds ratios (OR) between flood risk (presence/absence and scenarios) and confirmed human infection. Preliminary results indicate a clear relationship between both infections and hydrological risk. Over one third of all infection cases were reported within areas exposed to flood risk (VTEC 948/2755 cases; cryptosporidiosis 1548/4509 cases). Census areas categorised by a high (10-year Return Period) fluvial flood risk probability exhibited significantly higher incidence rates for both VTEC (OR: 1.83, P = 0.0003) and cryptosporidiosis (OR: 1.80, P = 0.0015). Similarly, areas characterised by low (1000-year Return Period) coastal flood risk probability were over twice as likely to report ≥1 confirmed case of cryptosporidiosis during the study period (OR: 2.2, P= 0.003). Space-time scan statistics (temporally-specific spatial autocorrelation) indicate an unseasonal peak of cryptosporidiosis cases occurring during April 2016, a majority of which took place within or adjacent to high flood risk areas (56% of total cases), revealing a potential relationship with the exceptional flooding events experienced during winter 2015-2016 (November-January). Further work will seek to identify the individual/combined flood risk (CFRAM) elements most significantly associated with the incidence of infections. Flood risk assessment mapping may represent an innovative approach to assessing the human health impacts of flood risk exposure and climate change. The outcomes of this study will contribute to predictive modelling of VTEC and cryptosporidiosis in Ireland, thus aiding surveillance and control of these diseases in the future, and the causative nature of regional hydrology and climate.