{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T16:17:40Z","timestamp":1781713060521,"version":"3.54.5"},"reference-count":52,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,11]],"date-time":"2023-07-11T00:00:00Z","timestamp":1689033600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"South East Water (Australia)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>We designed an out-of-water radar water velocity and depth sensor, which is unique due to its low cost and low power consumption. The sensor is a first at a cost of less than USD 50, which is well suited to previously cost-prohibited high-resolution monitoring schemes. This use case is further supported by its out-of-water operation, which provides low-effort installations and longer maintenance-free intervals when compared with in-water sensors. The inclusion of both velocity and depth measurement capabilities allows the sensor to also be used as an all-in-one solution for flowrate measurement. We discuss the design of the sensor, which has been made freely available under open-hardware and open-source licenses. The design uses commonly available electronic components, and a 3D-printed casing makes the design easy to replicate and modify. Not before seen on a hydrology sensor, we include a 3D-printed radar lens in the casing, which boosts radar sensitivity by 21 dB. The velocity and depth-sensing performance were characterised in laboratory and in-field tests. The depth is accurate to within \u00b16% and \u00b17 mm and the uncertainty in the velocity measurements ranges from less than 30% to 36% in both laboratory and field conditions. Our sensor is demonstrated to be a feasible low-cost design which nears the uncertainty of current, yet more expensive, velocity sensors, especially when field performance is considered.<\/jats:p>","DOI":"10.3390\/s23146314","type":"journal-article","created":{"date-parts":[[2023,7,12]],"date-time":"2023-07-12T01:05:01Z","timestamp":1689123901000},"page":"6314","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8967-5853","authenticated-orcid":false,"given":"Stephen","family":"Catsamas","sequence":"first","affiliation":[{"name":"BoSL Water Monitoring and Control, Department of Civil Engineering, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baiqian","family":"Shi","sequence":"additional","affiliation":[{"name":"BoSL Water Monitoring and Control, Department of Civil Engineering, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miao","family":"Wang","sequence":"additional","affiliation":[{"name":"BoSL Water Monitoring and Control, Department of Civil Engineering, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jieren","family":"Xiao","sequence":"additional","affiliation":[{"name":"BoSL Water Monitoring and Control, Department of Civil Engineering, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Kolotelo","sequence":"additional","affiliation":[{"name":"BoSL Water Monitoring and Control, Department of Civil Engineering, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"McCarthy","sequence":"additional","affiliation":[{"name":"BoSL Water Monitoring and Control, Department of Civil Engineering, Monash University, Melbourne, VIC 3800, Australia"},{"name":"School of Civil and Environmental Engineering, Faculty of Engineering, Queensland University of Technology, Brisbane, QLD 4001, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1016\/j.jenvman.2009.09.026","article-title":"Urban Water Infrastructure Optimization to Reduce Environmental Impacts and Costs","volume":"91","author":"Lim","year":"2010","journal-title":"J. Environ. Manag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"5297","DOI":"10.1007\/s11356-013-2370-x","article-title":"Road Traffic Impact on Urban Water Quality: A Step towards Integrated Traffic, Air and Stormwater Modelling","volume":"21","author":"Bonhomme","year":"2014","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.jhydrol.2010.04.005","article-title":"Predictive Models for Forecasting Hourly Urban Water Demand","volume":"387","author":"Herrera","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1007\/s10661-016-5461-6","article-title":"Assessment of Pollutant Load Emission from Combined Sewer Overflows Based on the Online Monitoring","volume":"188","author":"Zawilski","year":"2016","journal-title":"Environ. Monit. Assess."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1016\/j.watres.2010.09.024","article-title":"Impact of an Intense Combined Sewer Overflow Event on the Microbiological Water Quality of the Seine River","volume":"45","author":"Passerat","year":"2011","journal-title":"Water Res."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Hauet, A.C. (2020). Uncertainty of Discharge Measurement Methods: A Literature Review, NVE\u2014Norges vassdrags- og energidirektorat.","DOI":"10.5194\/egusphere-egu2020-4661"},{"key":"ref_7","unstructured":"(2022, September 16). On the Derivation of Flow Rating Curves in Data-Scarce Environments|Elsevier Enhanced Reader. Available online: https:\/\/reader.elsevier.com\/reader\/sd\/pii\/S0022169418303111?token=E7BF89DB02F822C933091A38091751208C04D135804463AABDF46E53F598519B735CAC22AECF982A37CAD1857634B495&originRegion=us-east-1&originCreation=20220916025705."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"913","DOI":"10.5194\/hess-13-913-2009","article-title":"Uncertainty in River Discharge Observations: A Quantitative Analysis","volume":"13","author":"Baldassarre","year":"2009","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Moramarco, T., Barbetta, S., and Tarpanelli, A. (2017). From Surface Flow Velocity Measurements to Discharge Assessment by the Entropy Theory. Water, 9.","DOI":"10.3390\/w9020120"},{"key":"ref_10","first-page":"49","article-title":"Chapter 3\u2014Discharge Measurements and Streamflow Analysis","volume":"Volume 1","author":"Hauer","year":"2017","journal-title":"Methods in Stream Ecology"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Chen, Y.-C., Hsu, Y.-C., and Zai, E.O. (2022). Streamflow Measurement Using Mean Surface Velocity. Water, 14.","DOI":"10.3390\/w14152370"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Vyas, J.K., Perumal, M., and Moramarco, T. (2020). Discharge Estimation Using Tsallis and Shannon Entropy Theory in Natural Channels. Water, 12.","DOI":"10.3390\/w12061786"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1016\/j.watres.2016.11.027","article-title":"Should We Trust Build-up\/Wash-off Water Quality Models at the Scale of Urban Catchments?","volume":"108","author":"Bonhomme","year":"2017","journal-title":"Water Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.jenvman.2019.06.006","article-title":"Understanding Spatiotemporal Variability of In-Stream Water Quality in Urban Environments\u2014A Case Study of Melbourne, Australia","volume":"246","author":"Shi","year":"2019","journal-title":"J. Environ. Manag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"7267","DOI":"10.1021\/acs.est.5b05870","article-title":"Smarter Stormwater Systems","volume":"50","author":"Kerkez","year":"2016","journal-title":"Environ. Sci. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Fulton, J.W., Anderson, I.E., Chiu, C.-L., Sommer, W., Adams, J.D., Moramarco, T., Bjerklie, D.M., Fulford, J.M., Sloan, J.L., and Best, H.R. (2020). QCam: SUAS-Based Doppler Radar for Measuring River Discharge. Remote Sens., 12.","DOI":"10.3390\/rs12203317"},{"key":"ref_17","unstructured":"(2020, November 30). HACH Submerged Area\/Velocity Sensor and AV9000. Available online: https:\/\/au.hach.com\/asset-get.download.jsa?id=8289724802."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"28","DOI":"10.2166\/ws.2019.144","article-title":"Water Quality Monitoring: From Conventional to Emerging Technologies","volume":"20","author":"Ahmed","year":"2019","journal-title":"Water Supply"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Fulton, J.W., Mason, C.A., Eggleston, J.R., Nicotra, M.J., Chiu, C.-L., Henneberg, M.F., Best, H.R., Cederberg, J.R., Holnbeck, S.R., and Lotspeich, R.R. (2020). Near-Field Remote Sensing of Surface Velocity and River Discharge Using Radars and the Probability Concept at 10 U.S. Geological Survey Streamgages. Remote Sens., 12.","DOI":"10.3390\/rs12081296"},{"key":"ref_20","first-page":"2648","article-title":"End-User Perspective of Low-Cost Sensors for Urban Stormwater Monitoring: A Review","volume":"87","author":"Zhu","year":"2023","journal-title":"Water Sci. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"12398","DOI":"10.1109\/JSEN.2019.2937954","article-title":"Continuous, Near-Bed Current Velocity Estimation Using Pressure and Inertial Sensing","volume":"19","author":"Ristolainen","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Catsamas, S., Shi, B., Deletic, B., Wang, M., and McCarthy, D.T. (2022). A Low-Cost, Low-Power Water Velocity Sensor Utilizing Acoustic Doppler Measurement. Sensors, 22.","DOI":"10.3390\/s22197451"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Huang, Y., Chen, H., Liu, B., Huang, K., Wu, Z., and Yan, K. (2023). Radar Technology for River Flow Monitoring: Assessment of the Current Status and Future Challenges. Water, 15.","DOI":"10.3390\/w15101904"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1372","DOI":"10.2166\/wst.2022.034","article-title":"Illicit Discharge Detection in Stormwater Drains Using an Arduino-Based Low-Cost Sensor Network","volume":"85","author":"Shi","year":"2022","journal-title":"Water Sci. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Prafanto, A., and Budiman, E. (2018, January 6\u20137). A Water Level Detection: IoT Platform Based on Wireless Sensor Network. Proceedings of the 2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT), Makassar, Indonesia.","DOI":"10.1109\/EIConCIT.2018.8878559"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"042025","DOI":"10.1088\/1757-899X\/518\/4\/042025","article-title":"Highly Accurate Water Level Measurement System Using a Microcontroller and an Ultrasonic Sensor","volume":"518","author":"Mohammed","year":"2019","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Wang, G., Gu, C., Rice, J., Inoue, T., and Li, C. (2013, January 20\u201323). Highly Accurate Noncontact Water Level Monitoring Using Continuous-Wave Doppler Radar. Proceedings of the 2013 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet), Austin, TX, USA.","DOI":"10.1109\/WiSNet.2013.6488620"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Bandini, F., Fr\u00edas, M.C., Liu, J., Simkus, K., Karagkiolidou, S., and Bauer-Gottwein, P. (2022). Challenges with Regard to Unmanned Aerial Systems (UASs) Measurement of River Surface Velocity Using Doppler Radar. Remote Sens., 14.","DOI":"10.20944\/preprints202109.0521.v2"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1108","DOI":"10.1002\/2015WR017906","article-title":"Field Assessment of Noncontact Stream Gauging Using Portable Surface Velocity Radars (SVR)","volume":"52","author":"Welber","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2439","DOI":"10.1002\/esp.4199","article-title":"RAPTOR-UAV: Real-Time Particle Tracking in Rivers Using an Unmanned Aerial Vehicle","volume":"42","author":"Thumser","year":"2017","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Pearce, S., Ljubi\u010di\u0107, R., Pe\u00f1a-Haro, S., Perks, M., Tauro, F., Pizarro, A., Dal Sasso, S.F., Strelnikova, D., Grimaldi, S., and Maddock, I. (2020). An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems. Remote Sens., 12.","DOI":"10.5194\/egusphere-egu2020-324"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Koutalakis, P., Tzoraki, O., and Zaimes, G. (2019). UAVs for Hydrologic Scopes: Application of a Low-Cost UAV to Estimate Surface Water Velocity by Using Three Different Image-Based Methods. Drones, 3.","DOI":"10.3390\/drones3010014"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Watanabe, K., Fujita, I., Iguchi, M., and Hasegawa, M. (2021). Improving Accuracy and Robustness of Space-Time Image Velocimetry (STIV) with Deep Learning. Water, 13.","DOI":"10.3390\/w13152079"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"5195","DOI":"10.1109\/TGRS.2020.2974185","article-title":"Noncontact Measurement of River Surface Velocity and Discharge Estimation with a Low-Cost Doppler Radar Sensor","volume":"58","author":"Alimenti","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3463","DOI":"10.1002\/mop.32479","article-title":"A 24 GHz Hydrology Radar System Capable of Wide-Range Surface Velocity Detection for Water Resource Management Applications","volume":"62","author":"Lin","year":"2020","journal-title":"Microw. Opt. Technol. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"16008","DOI":"10.1109\/JSEN.2022.3191443","article-title":"Self-Temperature Compensated Water Level and Velocity Sensor Based on Fiber Bragg Gratings","volume":"22","author":"Fernandes","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4578","DOI":"10.3390\/s120404578","article-title":"Long-Period Fiber Grating Sensors for the Measurement of Liquid Level and Fluid-Flow Velocity","volume":"12","author":"Wang","year":"2012","journal-title":"Sensors"},{"key":"ref_38","unstructured":"(2023, April 29). Acconeer XM132 Datasheet. Available online: https:\/\/developer.acconeer.com\/download\/xm132-datasheet-pdf\/."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1242","DOI":"10.1109\/TGRS.2005.845641","article-title":"Measurement of River Surface Currents with Coherent Microwave Systems","volume":"43","author":"Plant","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"W07422","DOI":"10.1029\/2005WR004430","article-title":"Use of Radars to Monitor Stream Discharge by Noncontact Methods","volume":"42","author":"Costa","year":"2006","journal-title":"Water Resour. Res."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"214832","DOI":"10.1109\/ACCESS.2020.3041373","article-title":"Optimising SD Saving Events to Maximise Battery Lifetime for ArduinoTM\/Atmega328P Data Loggers","volume":"8","author":"Bradley","year":"2020","journal-title":"IEEE Access"},{"key":"ref_42","unstructured":"(2023, July 02). A111 Datasheet.Pdf\u2014Onehub. Available online: https:\/\/developer.acconeer.com\/download\/a111-datasheet-pdf\/."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Abedi, H., and Shaker, G. (2020, January 5\u201310). Low-Cost 3D Printed Dielectric Hyperbolic Lens Antenna for Beam Focusing and Steering of a 79GHz MIMO Radar. Proceedings of the 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, Montreal, QC, Canada.","DOI":"10.1109\/IEEECONF35879.2020.9329969"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Friel, R.J., Gerling-Gerdin, M., Nilsson, E., and Andreasson, B.P. (2019). 3D Printed Radar Lenses with Anti-Reflective Structures. Designs, 3.","DOI":"10.3390\/designs3020028"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"8790","DOI":"10.1109\/ACCESS.2023.3239782","article-title":"A Review of 3D Printed Gradient Refractive Index Lens Antennas","volume":"11","author":"Munina","year":"2023","journal-title":"IEEE Access"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Hagstr\u00f6m, A.L., Vass, L.A.M., Liu, F., Gerling, M., Karlsson, P.-O., Nilsson, E., and Andreasson, B.P. (2018, January 12\u201313). An Iterative Approach to Determine the Refractive Index of 3D Printed 60GHz PLA Lenses. Proceedings of the Loughborough Antennas & Propagation Conference (LAPC 2018), Loughborough, UK.","DOI":"10.1049\/cp.2018.1480"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1109\/LMWC.2018.2823005","article-title":"3-D Printed Millimeter-Wave Lens Systems at 39 GHz","volume":"28","author":"Paolella","year":"2018","journal-title":"IEEE Microw. Wirel. Compon. Lett."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Chen, Z.N., Liu, D., Nakano, H., Qing, X., and Zwick, T. (2016). Handbook of Antenna Technologies, Springer.","DOI":"10.1007\/978-981-4560-44-3"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Shi, B., Catsamas, S., Kolotelo, P., Wang, M., Lintern, A., Jovanovic, D., Bach, P.M., Deletic, A., and McCarthy, D.T. (2021). A Low-Cost Water Depth and Electrical Conductivity Sensor for Detecting Inputs into Urban Stormwater Networks. Sensors, 21.","DOI":"10.3390\/s21093056"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1812","DOI":"10.1016\/j.watres.2007.11.009","article-title":"Uncertainties in Stormwater E. coli Levels","volume":"42","author":"McCarthy","year":"2008","journal-title":"Water Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.flowmeasinst.2005.07.001","article-title":"A Simple Model for Estimation of Dimensionless Isovel Contours in Open Channels","volume":"16","author":"Maghrebi","year":"2005","journal-title":"Flow Meas. Instrum."},{"key":"ref_52","unstructured":"(2023, June 25). Decatur Europe\u2014Surface Velocity Radar|Hand-Held SVR Radar for Water Flow Measurement. Available online: https:\/\/www.decatureurope.com\/en\/products\/surface-velocity-flow."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/14\/6314\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:10:52Z","timestamp":1760127052000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/14\/6314"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,11]]},"references-count":52,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2023,7]]}},"alternative-id":["s23146314"],"URL":"https:\/\/doi.org\/10.3390\/s23146314","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,11]]}}}