Flow monitoring with a camera: a case study on a flood event in the Tiber River
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Monitoring surface water velocity during flood events is a challenging task. Techniques based on deploying instruments in the flow are often unfeasible due to high velocity and abundant sediment transport. A low-cost and versatile technology that provides continuous and automatic observations is still not available. Among remote methods, large-scale particle image velocimetry (LSPIV) is an optical method that computes surface water velocity maps from videos recorded with a camera. Here, we implement and critically analyze findings obtained from a recently introduced LSPIV experimental configuration during a flood event in the Tiber River at a cross section located in the center of Rome, Italy. We discuss the potential of LSPIV observations in challenging environmental conditions by presenting results from three tests performed during the hydrograph flood peak and recession limb of the event for different illumination and weather conditions. The obtained surface velocity maps are compared to the rating curve velocity and to benchmark velocity values. Experimental findings show that optical methods should be preferred in extreme conditions. However, their practical implementation may be associated with further hurdles and uncertainties.
KeywordsFlow monitoring Surface flow Flow measurement Flow velocity Large-scale particle image velocimetry Camera observations
This work was supported by the American Geophysical Union Horton (Hydrology) Research Grant for Ph.D. students, by the Ministero degli Affari Esteri project 2015 Italy-USA PGR00175, by the UNESCO Chair in Water Resources Management and Culture, and by the National Science Foundation under grant number BCS-1124795. The authors thank Roberto Rapiti and Giuliano Cipollari for help with the experiments and Francesco Mele, Domenico Spina, and Luigi D’Aquino from UIM for providing water level measurements and rating curves.
- Buchanan, T. J., and W. P. Somers (1969), Discharge measurements at gaging stations: U.S. geological survey techniques of water-resources investigations, Tech. rep., U.S. Geological Survey.Google Scholar
- Chow, V. T. (1959). Open-Channel Hydraulics. New York: McGraw-Hill.Google Scholar
- Gui, L. (2014), EDPIV—evaluation software for digital particle image velocimetry, http://lcgui.net.
- Hauet, A., Kruger, A., Krajewski, W. F., Bradley, A., Muste, M., Creutin, J.-D., & Wilson, M. (2008a). Experimental system for real-time discharge estimation using an image-based method. Journal of Hydrologic Engineering, 13(2), 105–110.Google Scholar
- Hauet, A., Creutin, J. D., & Belleudy, P. (2008b). Sensitivity study of large-scale particle image velocimetry measurement of river discharge using numerical simulation. Journal of Hydrology, 349(1-2), 178–190.Google Scholar
- Hrachowitz, M., Savenije, H. H. G., Bogaard, T., Tetzlaff, D., & Soulsby, C. (2013a). What can flux tracking teach us about water age distribution patterns and their temporal dynamics? Hydrology and Earth System Sciences, 17, 533–564.Google Scholar
- Hrachowitz, M., Savenije, H. H. G., Blöschl, G., McDonnell, J. J., Sivapalan, M., Pomeroy, J. W., Arheimer, B., Blume, T., Clark, M. P., Ehret, U., Fenicia, F., Freer, J. E., Gelfan, A., Gupta, H. V., Hughes, D. A., Hut, R. W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P. A., Uhlenbrook, S., Wagener, T., Winsemius, H. C., Woods, R. A., Zehe, E., & Cudennec, C. (2013b). A decade of predictions in ungauged basins (PUB)—a review. Hydrological Sciences Journal, 58(6), 1198–1255.Google Scholar
- Kim, Y. (2006), Uncertainty analysis for non-intrusive measurement of river discharge using image velocimetry, Ph.D. thesis, Graduate College of the University of Iowa.Google Scholar
- McMillan, H., Freer, J., Pappenberger, F., Krueger, T., & Clark, M. (2010). Impacts of uncertain river flow data on rainfall-runoff model calibration and discharge predictions. Hydrological Processes, 24(10), 1270–1284.Google Scholar
- Montanari, A., Young, G., Savenije, H. H. G., Hughes, D., Wagener, T., Ren, L. L., Koutsoyiannis, D., Cudennec, C., Toth, E., Grimaldi, S., Blöschl, G., Sivapalan, M., Beven, K., Gupta, H., Hipsey, M., Schaefli, B., Arheimer, B., Boegh, E., Schymanski, S. J., Di Baldassarre, G., Yu, B., Hubert, P., Huang, Y., Schumann, A., Post, D. A., Srinivasan, V., Harman, C., Thompson, S., Rogger, M., Viglione, A., McMillan, H., Characklis, G., Pang, Z., & Belyaev, V. (2013). Panta Rhei—everything flows: change in hydrology and society—The IAHS scientific decade 2013-2022. Hydrological Sciences Journal, 58(6), 1256–1275.CrossRefGoogle Scholar
- Raffel, M., Willert, C. E., Wereley, S. T., & Kompenhans, J. (2007). Particle image velocimetry. A practical guide. New York: Springer.Google Scholar
- Centro Funzionale Regionale – Regione Lazio (2015), http://www.idrografico.roma.it.
- Sassi, M. G., Hoitink, A. J. F., Vermeulen, B., and Hidayat (2011), Discharge estimation from H-ADCP measurements in a tidal river subject to sidewall effects and a mobile bed, Water Resources Research, 47(6), W06504.Google Scholar
- Tauro, F., Porfiri, M., & Grimaldi, S. (2013a). Fluorescent eco-particles for surface flow physics analysis. AIP Advances, 3(3), 032108.Google Scholar
- Tauro, F., Rapiti, E., Al-Sharab, J. F., Ubertini, L., Grimaldi, P., & Porfiri, M. (2013b). Characterization of eco-friendly fluorescent nanoparticle doped-tracers for environmental sensing. Journal of Nanoparticle Research, 15(9), 1884.Google Scholar
- Tauro, F., Porfiri, M., & Grimaldi, S. (2014a). Orienting the camera and firing lasers to enhance large scale particle image velocimetry for stream flow monitoring. Water Resources Research, 50(9), 7470–7483.Google Scholar
- Tauro, F., Porfiri, M., & Grimaldi, S. (2014b). Unraveling flow patterns through nonlinear manifold learning. PLoS One, 9(3), e91131.Google Scholar
- Tauro, F., A. Petroselli, and E. Arcangeletti (2015a), Assessment of drone-based surface flow observations, Hydrological Processes, 10.1002/hyp.10698
- Tauro, F., Pagano, C., Phamduy, P., Grimaldi, S., & Porfiri, M. (2015b). Large-scale particle image velocimetry from an unmanned aerial vehicle. IEEE/ASME Transactions on Mechatronics, 20(6), 3269–3275.Google Scholar
- Tazioli, A. (2011). Experimental methods for river discharge measurements: comparison among tracers and current meter [Méthodes expérimentales pour mesurer le débit des cours d’eau: Comparaison entre les traceurs artificiels et le courantomètre]. Hydrol Sci J, 56(7), 1314–1324.CrossRefGoogle Scholar