Best practice in high-frequency water quality monitoring for improved management and assessment; a novel decision workflow.

The use of high-frequency water quality monitoring has increased over several decades. This has mostly been motivated by curiosity-driven research and has significantly improved our understanding of hydrochemical processes. Despite these scientific successes and the growth in sensor technology, the large-scale uptake of high-frequency water quality monitoring by water managers is hampered by a lack of comprehensive practical guidelines.

Cost-effectiveness of targeted riparian management for sediment and total phosphorus considering convergent surface flow pathways: an Irish case study.

Unlabelled: Diffuse pollution, globally affecting water quality by delivery of sediment, nutrients, pathogens and agro-chemicals from farmland, often has dominant flowpaths connecting to discrete channel delivery points, where field-edge mitigation can be optimally targeted. Accurate representation of field convergent flow paths (CFPs) can inform decisions on riparian mitigation planning. For three fields in Wexford, Ireland, we combined literature, catchment data, field-survey and spatial data methods to derive sediment and P exports (7.

Far-future hydrology will differentially change the phosphorus transfer continuum.

Climate change is likely to exacerbate land to water phosphorus (P) transfers, causing a degradation of water quality in freshwater bodies in Northwestern Europe. Planning for mitigation measures requires an understanding of P loss processes under such conditions. This study assesses how climate induced changes to hydrology will likely influence the P transfer continuum in six contrasting river catchments using Irish national observatories as exemplars.

Stochastic modelling of pesticide transport to drinking water sources via runoff and resulting human health risk assessment.

A modelling framework was developed to facilitate a probabilistic assessment of health risks posed by pesticide exposure via drinking water due to runoff, with the inclusion of influential site conditions and in-stream processes. A Monte-Carlo based approach was utilised to account for the inherent variability in pesticide and population properties, as well as site and climatic conditions. The framework presented in this study was developed with an ability to integrate different data sources and adapt the model for various scenarios and locations to meet the users' needs.