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

  • J. Rozemeijer
  • , P. Jordan
  • , A. Hooijboer
  • , B. Kronvang
  • , M. Glendell
  • , R. Hensley
  • , K. Rinke
  • , M. Stutter
  • , M. Bieroza
  • , R. Turner
  • , P.E. Mellander
  • , P. Thorburn
  • , R. Cassidy
  • , J. Appels
  • , K. Ouwerkerk
  • , M. Rode
  • Deltares
  • Ulster University
  • National Institute for Public Health and the Environment (Netherlands)
  • Aarhus University
  • National Ecological Observatory Network (USA)
  • Helmholtz Centre for Environmental Research
  • Swedish University of Agricultural Sciences
  • University of Queensland
  • Teagasc - Irish Agriculture and Food Development Authority
  • CSIRO
  • Agri-Food and Biosciences Institute (Northern Ireland)
  • microLAN BV

Research output: Contribution to journalArticlepeer-review

Abstract

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. Low-frequency hydrochemical data are still routinely used to review environmental policies but are prone to missing important event-driven processes. With a changing climate where such event-driven processes are more likely to occur and have a greater impact, the adoption of high-frequency water quality monitoring is becoming more pressing. To prepare regulators and environmental and hydrological agencies for these new challenges, this paper reviews international best practice in high-frequency data provision. As a result, we summarise the added value of high-frequency water quality monitoring, describe international best practices for sensors and analysers in the field, and evaluate the experience with high-frequency data cleaning. We propose a decision workflow that includes considerations of monitoring data needs, sensor choice, maintenance and calibration, and structured data processing. The workflow fills an important knowledge-exchange gap between research and statutory surveillance for future high-frequency water quality sensor uptake by practitioners and agencies.
Original languageEnglish
Article number353
JournalEnvironmental Monitoring and Assessment
Volume197
DOIs
Publication statusPublished - 4 Mar 2025

Keywords

  • Decision workflow
  • High-frequency data
  • Monitoring
  • Sensors
  • Water quality

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