Optical sensing for stream flow observations: A review

  • Flavia Tauro Department for Innovation in Biological, Agro-food and Forest Systems, University of Tuscia, Viterbo, Italy.
  • Andrea Petroselli Department of Economics, Engineering, Society and Business Organisation, University of Tuscia, Viterbo, Italy.
  • Salvatore Grimaldi | salvatore.grimaldi@unitus.it Department for Innovation in Biological, Agro-food and Forest Systems, University of Tuscia, Viterbo, Italy; Department of Mechanical and Aerospace Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, United States.


Images are revolutionising the way we sense and characterise the environment by offering higher spatial and temporal coverage in ungauged environments at competitive costs. In this review, we illustrate major image-based approaches that have been lately adopted within the hydrological research community. Although many among such methodologies have been developed some decades ago, recent efforts have been devoted to their transition from laboratories to operational outdoor settings. Sample applications of image-based techniques include flow discharge estimation in riverine environments, clogging dynamics in irrigation systems, and flow diagnostics in engineering infrastructures. The potential of such image-based approaches towards fully remote observations is also illustrated through a simple experiment with an unmanned aerial vehicle.


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Review Articles
Ungauged catchments, experimental monitoring, images, optical sensing, large scale particle image velocimetry, particle tracking velocimetry.
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How to Cite
Tauro, F., Petroselli, A., & Grimaldi, S. (2018). Optical sensing for stream flow observations: A review. Journal of Agricultural Engineering, 49(4), 199-206. https://doi.org/10.4081/jae.2018.836

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