Analysis of the accuracy and uncertainty of flow measurements taken by large-scale particle image velocimetry

Information on river flows is essential in water management for the calibration of hydrological models, the estimation of the annual exceedance probabilities and the calibration of the hydraulic models required to delimit flood-prone areas or maintain the safety of the population. Flow measurements are generally carried out using an acoustic Doppler current profiler (ADCP). However, it is sometimes difficult or even dangerous to take measurements using an ADCP, particularly during high flow, when objects (trees, ice) can drift in the river.

In addition, a certain water depth is required for taking measurements with an ADCP. Thus, extreme events are often poorly characterized. Extreme events will occur more frequently with climate change, making better characterization necessary. Large-scale particle image velocimetry (LSPIV) is a non-contact method for measuring river flow. It can be applied during low and high flow. However, the field of application, the acquisition method (drone, camera), and the method’s sources of error and uncertainty must be assessed.
 

• Evaluate the accuracy of LSPIV in the natural environment in a range of conditions, such as the river width, depth, roughness, the camera position (mounted on a bank, a bridge or by drone), and the number, geometry and position of the control points;

• Determine the effect of geometry in a controlled environment (a channel) on the estimation of the flow using LSPIV;

• Determine the optimal seeding, lighting and wind conditions for LSPTV and compare the results with the LSPIV method.

• Acquisition of data at fifteen sites representing different hydraulic and morphological conditions and processing of images using free LSPIV/LSPTV software;

• Experimental study in a controlled environment at the University of Sherbrooke’s experimental river in order to facilitate the achievement of objective 2 by varying the geometry of the river;

• Identification and estimation of error and uncertainty.

The project will analyze the performance (accuracy and uncertainty) of the LSPIV method for measuring river flows in Quebec. An accompanying guide on the use of the LSPIV method for gauging will be written and will list best practices for taking measurements in the field, the steps for image processing with the recommended software (user guide) and analysis of the result obtained. In addition, the project will acquire data on flows throughout the process for the rivers under study.