A Drone Borne Method to Jointly Estimate Discharge and Manning's Roughness of Natural Streams

Image cross-correlation techniques, such as Particl e Image Velocimetry (PIV), can estimate water surface velocity (v surf) of streams. However, discharge estimation require s water depth and the depthaveraged vertical velocity (U m). The variability of the ratio Um/vsurf introduces large errors in discharge estimates. We demonstrate a method to es timate vsurf from Unmanned Aerial Systems (UASs) with PIV technique. This method does not req uire any Ground Control Point (GCP): the conversion of velocities from pixels per frame into meters per time is performed by informing a camera pinhole model; the range from the pinhole to the water surface is measured by the droneboard radar. For approximately uniform flow, U m is a function of the Gauckler-Manning-Strickler coefficient (Ks) and vsurf. We implement an approach that can be used to join tly estimate Ks and discharge by informing a system of 2 unknowns (Ks a nd discharge) and 2 non-linear equations: i) Manning’s equation ii) mean-section method for comp uting discharge from U m. This approach relies on bathymetry, acquired in-situ a-priori, and on UA S-borne vsurf and water surface slope measurements. Our joint (discharge and Ks) estimati on pproach is an alternative to the widely used approach than relies on estimating U m as 0.85·vsurf. It was extensively investigated in 27 case studi es, A cc ep te d A rt ic le This article has b en acc p ed for publication and undergone full peer rev ew but h s not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1029/2020WR028266. This article is protected by copyright. All rights reserved. A cc ep te d A rt ic le This article is protected by copyright. All rights reserved. in different streams with different hydraulic condi tions. Discharge estimated with the joint estimatio n approach showed a mean absolute error in discharge of 19.1% compared to in-situ discharge measurements. Ks estimates showed a mean absolute e rror of 3.2 m/s compared to in-situ measurements.