Acta Geographica Sinica ›› 2019, Vol. 74 ›› Issue (7): 1392-1408.doi: 10.11821/dlxb201907009

• Climate Change and Surface Processes • Previous Articles     Next Articles

Measuring streamflow with low-altitude UAV imagery

ZHAO Changsen1,2,PAN Xu1,3,YANG Shengtian1,2(),LIU Changming1,CHEN Xin4,ZHANG Hanming5,PAN Tianli2   

  1. 1.College of Water Sciences, Beijing Normal University, Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China
    2.School of Geography, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    3.College of Water Conservancy and Civil Engineering, Shandong Agricultural University, Tai'an 271018, Shandong, China
    4.Jinan Survey Bureau of Hydrology and Water Resources, Jinan 250013, China
    5.Dongying Bureau of Hydrology and Water Resources, Dongying 257000, Shandong, China
  • Received:2018-05-17 Revised:2019-03-10 Online:2019-07-25 Published:2019-07-23
  • Contact: YANG Shengtian
  • Supported by:
    National Key Project for R&D(2016YFC0402403);National Key Project for R&D(2016YFC0402409)


Stream flows are of great importance in maintaining a stable hydrosphere and assessing available water resources of a nation. However, previous satellite-methods are difficult to retrieve stream flows for middle- or small-scale rivers due to the satellite course spatial resolution whereas near-ground measuring methods have too complex procedure, requirement of expensive apparatus, or low-efficiency. These shortcomings hindered them to be used widely in non-gauged areas and situations needing non-contact measurement, e.g., accidental pollution events. This paper presented a novel, non-contact, fast method to calculate streamflow using UAV images which can be easily applied to rivers with different scales of width. Using this method, stream flows can be calculated with or without ground-measured cross-section data. With UAV images it produced point-cloud and DSM (digital surface model) which were then used to calculate values of river-width, roughness, longitudinal water-surface slope and cross-section above water surface. With all these values, the hydraulic method was finally adopted to calculate stream flows. Results show that the method has a satisfactory performance with modelled streamflow values slightly higher than observed ones at high-flow periods (R 2= 0.997, RMSE = 4.55 m 3/s) with ground-observed cross-section data. When the cross-section data were absent, the cross-section under water can be generalized with the UAV measured above-water cross-section data. Errors in estimating stream flows induced by cross-section generalization decreased with increment of water-level and water-width. The maximum accumulated errors accounted for 8.28% of the bankfull streamflow. The errors were resulted from the generalization of river bottom with un-regular cross-sections. All the results and methodologies could be of great help in streamflow measurement in accidental pollution events and in ungauged areas across the globe.

Key words: streamflow, UAV, hydraulics, Jinan