<p>Real-time and near real-time (RT/NRT) water-quality sensors have increasingly been recognised as important tools because they provide high-frequency, site-specific data that complement remote sensing and support timely decision-making. However, the availability, deployment, and operational challenges of these sensors remain largely unexamined. To address this gap, this study provides the first continental-scale empirical assessment of operational RT/NRT water-quality sensor networks by integrating large-scale deployment mapping, stakeholder survey data, and newly proposed quantitative performance metrics to synthesise key findings. In this regard, 585 monitoring sites were mapped and detailed survey responses were collected from 186 operational sites. Results demonstrate substantial disparities in monitoring capacity. Physical sensors were widely deployed (Sensor Coverage Ratio = 89.6%), whereas chemical (34.2%) and biological sensors (3.8%) were less prevalent. Sensor deployment exhibited a strong inland bias, and monitoring breadth remained limited (Parameter Diversity Score ≈ 0.30). Survey findings indicated relatively strong operational reliability (Operational Reliability Score ≈ 0.73) and moderate willingness for data sharing (Data Accessibility Index ≈ 0.66), but only partial integration into management workflows (Integration Index ≈ 0.53) and limited expansion planning (Expansion Plan Rate ≈ 0.15). Limited staff capacity (97%), technical constraints (55%), and data interpretation difficulties (48%) were identified as major barriers. Overall, the findings advance understanding of RT/NRT monitoring practices and offer practical recommendations to strengthen the consistency, scalability, and practical uptake of monitoring efforts.</p>

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Assessing real-time water quality monitoring in a continental scale: sensor availability, management, and gaps

  • Negar Taheriashtiani,
  • Tim J. Malthus,
  • Timothy Bolton,
  • Arash Zamyadi

摘要

Real-time and near real-time (RT/NRT) water-quality sensors have increasingly been recognised as important tools because they provide high-frequency, site-specific data that complement remote sensing and support timely decision-making. However, the availability, deployment, and operational challenges of these sensors remain largely unexamined. To address this gap, this study provides the first continental-scale empirical assessment of operational RT/NRT water-quality sensor networks by integrating large-scale deployment mapping, stakeholder survey data, and newly proposed quantitative performance metrics to synthesise key findings. In this regard, 585 monitoring sites were mapped and detailed survey responses were collected from 186 operational sites. Results demonstrate substantial disparities in monitoring capacity. Physical sensors were widely deployed (Sensor Coverage Ratio = 89.6%), whereas chemical (34.2%) and biological sensors (3.8%) were less prevalent. Sensor deployment exhibited a strong inland bias, and monitoring breadth remained limited (Parameter Diversity Score ≈ 0.30). Survey findings indicated relatively strong operational reliability (Operational Reliability Score ≈ 0.73) and moderate willingness for data sharing (Data Accessibility Index ≈ 0.66), but only partial integration into management workflows (Integration Index ≈ 0.53) and limited expansion planning (Expansion Plan Rate ≈ 0.15). Limited staff capacity (97%), technical constraints (55%), and data interpretation difficulties (48%) were identified as major barriers. Overall, the findings advance understanding of RT/NRT monitoring practices and offer practical recommendations to strengthen the consistency, scalability, and practical uptake of monitoring efforts.