A Contactless Rapid Rating Curve Assessment Based On Drone-borne Measurement

Rating curve relationship is vital to hydrological studies, such as flood control and other water-related decision-making processes. Traditionally, rating curve are estimated by using single- or multiple-gauging observations, which is time-consuming, costly, and lacks spatial resolution. Hydraulic models are usually a reliable method to quickly derive the stage-discharge relation for discharge estimation, especially for assessing more reliable high-flow rating relations in extrapolation beyond gauge observation. To establish such models, hydraulic parameters such as water surface elevation, bathymetry, and bed roughness are needed, but they are mostly not available in remote and inaccessible regions. Drone-borne hydrometric monitoring technologies can be deployed to address this problem. As one of the primary objectives of the Horizon Europe UAWOS project, which is dedicated to developing an Unmanned Airborne Water Observing System for providing key hydrometric variables at high spatial resolution/coverage, and data-based products/services to enhance management and decision-making, this work centers on integrating hydraulic modeling with the unmanned airborne water observing system to establish the rating curve relationship. Water surface elevation data is derived by radar altimetry, bathymetry data by water penetrating radar and sonar, and Doppler radar for surface velocity. By utilizing the surface velocity and water surface elevation data, in conjunction with shallow-water equations, a bathymetry estimation algorithm is used to interpolate the bathymetry from the observed cross-section to the whole simulated river channel. We also come up with a method to directly retrieve the river roughness parameter from the UAV drone observation data. As a whole, these methods collectively establish a framework that is easily to use to estimate the rating curve in remote regions. The study shows how information from high spatial resolution and coverage hydrometric variables derived by drone-borne hydrometric monitoring technologies can improve rating curve estimates from models.