River flow monitoring: LS-PIV technique, an image-based method to assess discharge

The measurement of the river discharge within a natural ort artificial channel is still one of the most challenging tasks for hydrologists and the scientific community. Although discharge is a physical quantity that theoretically can be measured with very high accuracy, since the volume of water flows in a well-defined domain, there are numerous critical issues in obtaining a reliable value. Discharge cannot be measured directly, so its value is obtained by coupling a measurement of a quantity related to the volume of flowing water and the area of a channel cross-section. Direct measurements of current velocity are made, traditionally with instruments such as current meters. Although measurements with current meters are sufficiently accurate and even if there are universally recognized standards for the current application of such instruments, they are often unusable under specific flow conditions. In flood conditions, for example, due to the need for personnel to dive into the watercourse, it is impossible to ensure adequate safety conditions to operators for carrying out flow measures. Critical issue arising from the use of current meters has been partially addressed thanks to technological development and the adoption of acoustic sensors. In particular, with the advent of Acoustic Doppler Current Profilers (ADCPs), flow measurements can take place without personnel having direct contact with the flow, performing measurements either from the bridge or from the banks. This made it possible to extend the available range of discharge measurements. However, the flood conditions of a watercourse also limit the technology of ADCPs. The introduction of the instrument into the current with high velocities and turbulence would put the instrument itself at serious risk, making it vulnerable and exposed to damage. In the most critical case, the instrument could be torn away by the turbulent current. On the other hand, considering smaller discharges, both current meters and ADCPs are technologically limited in their measurement as there are no adequate water levels for the use of the devices. The difficulty in obtaining information on the lowest and highest values of discharge has important implications on how to define the relationships linking flows to water levels. The stage-discharge relationship is one of the tools through which it is possible to monitor the flow in a specific section of a watercourse. Through this curve, a discharge value can be obtained from knowing the water stage. Curves are site-specific and must be continuously updated to account for changes in geometry that the sections for which they are defined may experience over time. They are determined by making simultaneous discharge and stage measurements. Since instruments such as current meters and ADCPs are traditionally used, stage-discharge curves suffer from instrumental limitations. So, rating curves are usually obtained by interpolation of field-measured data and by extrapolate them for the highest and the lowest discharge values, with a consequent reduction in accuracy. This thesis aims to identify a valid alternative to traditional flow measurements and to show the advantages of using new methods of monitoring to support traditional techniques, or to replace them. Optical techniques represent the best solution for overcoming the difficulties arising from the adoption of a traditional approach to flow measurement. Among these, the most widely used techniques are the Large-Scale Particle Image Velocimetry (LS-PIV) and the Large-Scale Particle Tracking Velocimetry. They are able to estimate the surface velocity fields by processing images representing a moving tracer, suitably dispersed on the liquid surface. By coupling velocity data obtained from optical techniques with geometry of a cross-section, a discharge value can easily be calculated. In this thesis, the study of the LS-PIV technique was deepened, analysing the performance of the technique, and studying the physical and environmental parameters and factors on which the optical results depend. As the LS-PIV technique is relatively new, there are no recognized standards available for the proper application of the technique. A preliminary numerical analysis was conducted to identify the factors on which the technique is significantly dependent. The results of these analyses enabled the development of specific guidelines through which the LS-PIV technique could subsequently be applied in open field during flow measurement campaigns in Sicily. In this way it was possible to observe experimentally the criticalities involved in applying the technique on real cases. These measurement campaigns provided the opportunity to carry out analyses on field case studies and structure an automatic procedure for optimising the LS-PIV technique. In all case studies it was possible to observe how the turbulence phenomenon is a worsening factor in the output results of the LS-PIV technique. A final numerical analysis was therefore performed to understand the influence of turbulence factor on the performance of the technique. The results obtained represent an important step for future development of the topic

A Comparison of Methods for Streamflow Uncertainty Estimation

International audienceStreamflow time series are commonly derived from stage-discharge rating curves, but the uncertainty of the rating curve and resulting streamflow series are poorly understood. While different methods to quantify uncertainty in the stage-discharge relationship exist, there is limited understanding of how uncertainty estimates differ between methods due to different assumptions and methodological choices. We compared uncertainty estimates and stage-discharge rating curves from seven methods at three river locations of varying hydraulic complexity. Comparison of the estimated uncertainties revealed a wide range of estimates, particularly for high and low flows. At the simplest site on the Isère River (France), full width 95% uncertainties for the different methods ranged from 3 to 17% for median flows. In contrast, uncertainties were much higher and ranged from 41 to 200% for high flows in an extrapolated section of the rating curve at the Mahurangi River (New Zealand) and 28 to 101% for low flows at the Taf River (United Kingdom), where the hydraulic control is unstable at low flows. Differences between methods result from differences in the sources of uncertainty considered, differences in the handling of the time-varying nature of rating curves, differences in the extent of hydraulic knowledge assumed, and differences in assumptions when extrapolating rating curves above or below the observed gaugings. Ultimately, the selection of an uncertainty method requires a match between user requirements and the assumptions made by the uncertainty method. Given the significant differences in uncertainty estimates between methods, we suggest that a clear statement of uncertainty assumptions be presented alongside streamflow uncertainty estimates