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Abstract The rapid advancement of drone technology and digital twin systems has significantly transformed environmental monitoring, particularly in the field of water quality assessment. This paper systematically reviews the current state of research on the application of drones, digital twins, and their integration for water quality monitoring and management. It highlights key themes, insights, research trends, commonly used methodologies, and future directions from existing studies, aiming to provide a foundational reference for further research to harness the promising potential of these technologies for effective, scalable solutions in water resource management, addressing both immediate and long‐term environmental challenges. The systematic review followed PRISMA guidelines, rigorously analysing hundreds of relevant papers. Key findings emphasise the effectiveness of drones in capturing real‐time, high‐resolution spatial and temporal data, as well as the value of digital twins for predictive and simulation‐based analysis. Most importantly, the review demonstrates the potential of integrating these technologies to enhance sustainable water management practices. However, it also identifies a significant research gap in fully integrating drones with digital twins for comprehensive water quality management. In response, the review outlines future research directions, including improvements in data integration techniques, predictive models, and interdisciplinary collaboration.
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Integrating Inland and Coastal Water Quality Data for Actionable Knowledge
Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.
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- PAR ID:
- 10412988
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Date Published:
- Journal Name:
- Remote Sensing
- Volume:
- 13
- Issue:
- 15
- ISSN:
- 2072-4292
- Page Range / eLocation ID:
- 2899
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/rs13152899
