University of Worcester Worcester Research and Publications

Advancing river monitoring using image-based techniques: Challenges and opportunities

Manfreda, S., Miglino, D., Khim, C., Jomaa, S., Eltner, A., Perks, M., Pena-Haro, S., Bogaard, T., van Emmerik, T., Mariani, S., Maddock, Ian ORCID:, Tauro, F., Grimaldi, S., Zeng, Y., Goncalves, G., Strelnikova, D., Bussettini, M., Marchetti, G., Lastoria, B., Su, Z. and Rode, M. (2024) Advancing river monitoring using image-based techniques: Challenges and opportunities. Hydrological Science Journal, Latest (AAM). pp. 1-52. ISSN Print: 0262-6667 Electronic: 2150-3435

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Enhanced and effective hydrological monitoring plays a crucial role in understanding water-related processes in a rapidly changing world. Within this context, image-based river monitoring has shown to significantly enhance data collection, improve analysis and accuracy, and support effective and timely decision-making. The integration of remote and proximal sensing technologies, with citizen science, and artificial intelligence may revolutionize monitoring practices. Therefore, it is crucial to quantify the quality of current research and ongoing initiatives to envision the potential trajectories for research activities within this specific field. The evolution of monitoring strategies is progressing in multiple directions that should converge to build critical mass around relevant challenges to meet the need for innovative solutions to overcome limitations of traditional approaches. The present study reviews showcases and good practices of enhanced hydrological monitoring in different applications, reflecting the strengths and limitations of new approaches.

Item Type: Article
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The version available on this repository was published with the following disclaimer:
'As a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also.'

Uncontrolled Discrete Keywords: river monitoring, image-based techniques, remote sensing, water quality, artificial intelligence, citizen science
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
G Geography. Anthropology. Recreation > GB Physical geography
G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > Q Science (General)
T Technology > T Technology (General)
Divisions: College of Health, Life and Environmental Sciences > School of Science and the Environment
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Copyright Info: Open access, © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Depositing User: Ian Maddock
Date Deposited: 27 Mar 2024 15:27
Last Modified: 27 Mar 2024 15:27

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