The measurement of suspended sediments from acoustic backscatter was originally developed in marine science for monitoring near‐bottom suspensions usually composed of sand particles. In the last ...decade, there has been a growing interest in adapting these techniques to rivers. The so‐called “solid particle theory” developed in oceanography mainly applies to suspensions of non‐cohesive solid particles producing incoherent backscatter signal. So far, this theory has been used for interpreting river backscatter even if it relies on assumptions that are not obviously met in rivers. This study uses a set of measurements made on the Rhône River in France to discuss the typical issues which challenge the interpretation of sound backscattering for monitoring suspended sediments in rivers. Large discrepancies between model outputs and measurements for frequencies lower than 2.5 MHz suggest that other scattering processes including flocculation and air micro‐bubbles may have a large impact on acoustic backscatter and attenuation. Deviations of the backscatter echo distribution from Rayleigh statistics were observed, suggesting that the assumption of incoherent backscattering is not always met. This work calls for the development of a more complete theory for interpreting river backscatter.
Key Points
Modeling the acoustic backscatter of suspended sediments in rivers often results in large errors
Various sources of error may arise from the diversity and complexity of scatterers in rivers
Specific experiments and theoretical developments are required to identify and reduce modeling errors
Video‐based hydrometry continues to develop for contactless discharge measurements, automated flood gauging stations and the use of crowd‐sourced flood videos for discharge reconstruction. ...Irrespective of the velocimetry algorithm used (LSPIV, STIV, PTV…), orthorectification of the images is necessary beforehand, so that each pixel has the same known physical size. Most times, the orthorectification transformation is a plane‐to‐plane projection from the water surface to the camera sensor. Two approaches are typically used to compute the coefficients of this transformation: their calibration from ground reference points (GRPs) with known image and real‐world coordinates (“implicit calibration”) or their calculation from the values of the intrinsic (focal length, sensor size) and extrinsic (position, angles) parameters of the camera (“explicit calibration”). In this paper, we develop a Bayesian method which makes it possible to combine the implicit and explicit approaches in a probabilistic framework. The Bayesian approach can be used from situations suitable for the implicit approach (plenty of GRPs) to situations propitious to the explicit approach (well‐known camera parameters). The method is illustrated using synthetic views of a typical streamgauging scene with known true values of the parameters and GRP coordinates. We show that combining observational and prior information is generally beneficial to get precise estimates. Further tests carried out with a real scene of the Arc River at Randens, France, in flood conditions illustrate the impact of the number, uncertainty and spatial distribution of GRPs on the final uncertainty of flow velocity and discharge.
A Bayesian camera calibration method is introduced to quantify the flow velocity and discharge uncertainties due to image orthorectification errors in large‐scale image velocimetry techniques.
•We introduce three independent citizen science projects to document floods.•Crowdsourced images were used for discharge estimation or flood mapping.•The projects provide consistent feedback on the ...key drivers for success.•Especially: the support of stakeholders and the public awareness of natural hazards.
New communication and digital image technologies have enabled the public to produce large quantities of flood observations and share them through social media. In addition to flood incident reports, valuable hydraulic data such as the extent and depths of inundated areas and flow rate estimates can be computed using messages, photos and videos produced by citizens. Such crowdsourced data help improve the understanding and modelling of flood hazard. Since little feedback on similar initiatives is available, we introduce three recent citizen science projects which have been launched independently by research organisations to quantitatively document flood flows in catchments and urban areas of Argentina, France, and New Zealand. Key drivers for success appear to be: a clear and simple procedure, suitable tools for data collecting and processing, an efficient communication plan, the support of local stakeholders, and the public awareness of natural hazards.
Streamflow data measured at hydrometric stations are affected by uncertainty due to water level (or stage) measurement errors. This uncertainty increases as the sensitivity of the stage‐discharge ...controls decreases. A recently proposed method is used to demonstrate the role of control sensitivity in propagating stage uncertainty to streamflow uncertainty among other error sources. The method is first applied to a fictitious hydrometric station with five alternative scenarios of controls with variable sensitivity. The fictitious controls are designed on a flat weir without or with triangular or rectangular notches. The method is also evaluated using a real hydrometric station where the initially flat weir was changed to a weir with a rectangular notch. Both applications confirm the importance of the sensitivity of the controls, showing that a narrow notch in a flat control substantially reduces the uncertainty of daily, monthly and yearly discharges as well as the uncertainty of a low flow index. Quantifying such uncertainty component is essential to optimize the design of hydrometric stations and to provide streamflow data with acceptable uncertainty, especially for low flows.
The presented study cases demonstrate that the stage‐induced uncertainty in streamflow series strongly increases when hydraulic controls become less sensitive. The applications include synthetic data derived for a flat weir without or with triangular or rectangular notches, and a real hydrometric station where the initially flat weir was changed to a weir with a rectangular notch.
The hydroacoustic monitoring of suspended sediment concentration (SSC) in rivers is based on the inversion of backscatter and attenuation models. To evaluate such models, acoustic backscatter and ...attenuation were measured from a homogeneous suspension of fine river sediments (clay) in a laboratory tank at various concentrations in the range 1–18 g/l. Agreement between the modeled and measured acoustic backscatter and attenuation values was found to be relatively poor. The results are highly sensitive to particle size and shape which come with large measurement uncertainties and they can be significantly improved by adjusting plausible particle parameters. Various inversion methods combining single or multiple frequencies, analysis of backscatter and/or attenuation, spherical or oblate shape hypothesis for particles and fixed or estimated lognormal grain size distribution are tested. The most promising inversion methods using both backscatter and attenuation information led to accurate SSC estimates.
Key Points
Acoustic backscatter and attenuation of a homogeneous suspension of fine river sediment were measured in a laboratory tank
The results of existing models are highly sensitive to particle size distribution uncertainty
Inversion using both backscatter and attenuation yielded accurate concentration estimates
Flood frequency analysis (FFA), a widely used method to estimate flood hazard, is affected by several sources of uncertainty. Extending flood samples by reanalyzing historical systematic stage ...records has the potential to reduce sampling uncertainty, but the historical flood discharges derived from this reanalysis are generally affected by large uncertainties. This paper explores whether historical stage records improve design flood estimates through a chain of uncertainty estimation methods for FFA. Uncertainties are estimated and propagated from stage and rating curves to design flood estimates using Monte Carlo procedures. The role of both streamflow and sampling uncertainties in design flood estimation is examined. This procedure is applied to the 205-year long stage series of the Rhône River at Beaucaire, France (95 590 km2). The estimated streamflow 95% uncertainty varies from 30% (XIXth Century) to 5% (1967–2020). The total uncertainty of design flood is significantly reduced when the length of the series increases from 20 to 100 years due to sampling uncertainty reduction. However, the total uncertainty remains stable beyond this sample size: this is because large uncertainties affecting the XIXth Century flood discharges compensate for the reduction in sampling uncertainty. Enlarging the sample size to two centuries leads to including the two largest known floods in 1840 and 1856. In turn, this induces a 15% increase of the 1000-year flood estimates.
•Stage and rating curve uncertainties are propagated to design flood estimates.•XIXth Century floods uncertainty contribution on design flood uncertainty is large.•Sampling uncertainty decrease is offset by streamflow uncertainty increase.•Design flood uncertainty is not reduced beyond 100 years sample size.
In the last decade, much progress has been made in continuously measuring suspended sediment concentration (SSC) in rivers using horizontal side‐looking Acoustic Doppler Current Profilers. However, ...these techniques do not provide information on the spatial variability of the suspension. In this study, we explore some new possibilities offered by the down‐looking deployment of a multifrequency acoustic backscatter system (ABS) in order to obtain information on the suspension throughout an entire river cross section. Two sites, with low and high levels of SSC, were investigated. The acoustic signal was processed using multifrequency inversion methods. Both water sample calibration data and modeling were used for retrieving the acoustic properties of the suspended particles. At the low SSC site (
∼30 mg/L), we successfully inverted the acoustic signal, except in some areas of high acoustic backscatter close to the surface that were probably generated by air microbubbles. At the high SSC site (
∼10 g/L), estimates of both fine and sand SSCs throughout the river cross section were successfully obtained, except in some areas close to the bottom where the acoustic signal was totally attenuated due to distance and high concentration of fine sediments. This work confirms the capacity of hydroacoustic technology for providing spatial information on river suspensions.
Key Points
Multi‐frequency inversion methods were applied to down‐looking multi‐frequency ABS
Inversion of bimodal river suspension was successful for high fine and sand concentrations
Acoustic response was not always dominated by solid suspended particles for low concentration
Streamflow 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.
Plain Language Summary
Knowledge of the uncertainty in streamflow discharge measured at gauging stations is important for water management applications and scientific analysis. This paper shows that uncertainty estimates vary widely (typically up to a factor of 4) when comparing seven recently introduced estimation methods. A clear understanding of the assumptions underpinning different uncertainty estimation methods and the sources of uncertainty included in their calculations is needed when selecting a method and using and presenting its uncertainty estimates.
Key Points
Methods for estimating the stage‐discharge rating curve and its uncertainty were compared for stream gauges with varying hydraulic complexity
Uncertainty estimates varied widely at high and low flows for the different methods
Careful description of the assumptions behind uncertainty methods is needed
Steep streams with massive sediment supply are among the most complex systems to study, even in the laboratory. Their shallow sediment‐laden flows create self‐adjusting bed geometries that evolve ...rapidly. Often, morphological changes and flow processes cannot be dissociated. Because these very shallow and unstable flows cannot be equipped with measurement sensors, image analysis techniques, such as photogrammetry (e.g., structure‐from‐motion, SfM) and large‐scale particle image velocimetry (LSPIV), are interesting options for capturing the characteristics of these systems. The present work describes a complete procedure using both techniques to measure spatially distributed surface velocity and bed properties (deposit patterns, channel slope, and local roughness). The velocity data are used to assess the local flow directions along which the channel slope and roughness are extracted from the SfM digital elevation models. Fergusons “variable power equation” friction law, having been previously validated by comparison with approximately 100 local flow depth measurements, was used in a second step with the collected data to reconstruct a complete mapping of the depth‐averaged flows, thereby enabling a comprehensive analysis of the hydrogeomorphic system where shallow water equations apply. The assumptions, details, use of the friction law with roughness standard deviation rather than diameter as parameter and limitations of the procedure as well as possible sources of errors are discussed here, along with possibilities for improvements. This affordable and simple‐to‐implement procedure can provide a large amount of data, allowing for a more comprehensive analysis of complex hydraulic systems.
Plain Language Summary
Steep‐slope stream hydraulics are complicated and insufficiently known because fast, active, mobile, and profoundly correlated with massive sediment transport processes. Capturing data on such flows is complicated, although necessary to develop and validate models. Here we propose a combination of two image analysis methods (SfM and LSPIV) and an inverse procedure using a friction law to acquire thousands of flow observations. This affordable and simple to use method gives promising perspectives for other application in the still widely used flume experiments.
Key Points
Bedload laden flows on steep slopes are complex and poorly known processes with highly mobile boundaries
The paper proposes a complete procedure to reconstruct depth‐averaged flow spatial distribution
The method combines large‐scale PIV and structure‐from‐motion photogrammetry in a friction law
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