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Sediment transport is a key process that affects the morphology and ecological habitat diversity of rivers. As part of a gravel augmentation program to mitigate sediment deficit below a dam, gravel mobility in the Ain River in Eastern France was investigated by tracking of a large amount (n = 1,063) of PIT‐tagged gravels in the field, conducting a probabilistic approach based on published tracer studies, and performing two‐dimensional (2D) numerical modeling of flow and bedload transport. This comparative study highlights the strengths, weaknesses, and complementary aspects of the three approaches to the understanding of river gravel mobility. Thanks to recent technological improvements, PIT‐tagged gravels provide an increasingly reliable and accurate representation of bedload movement in the field, although it remains limited in spatio‐temporal resolution. Based on an exponential distribution, the probabilistic approach correctly reproduces the average trend in travel distances by the different classes of particles over hydrological periods, including one or several significant floods. Furthermore, the 2D numerical modeling accounts for the variability of local hydrodynamic conditions and can simulate realistic displacement distributions for the different classes of particles with high spatio‐temporal resolution. Numerical modeling is a very encouraging approach, which makes our study original because it is the first time that the estimation of mean travel distances, the application of an exponential distribution, and the comparison with a hydrodynamic model are combined. A more effective modeling strategy involves incorporating a probabilistic transport model in the 2D numerical model to reproduce the observed scatter of the individual particle trajectories. Key Points: PIT‐tagged gravels are used to track gravel mobility in the restored Ain RiverThe results of field tracer surveys are compared with probabilistic and two‐dimensional numerical modelingThe three approaches are found to be meaningful and complementary [ABSTRACT FROM AUTHOR]

Improving the quantification of the transverse mixing coefficient in rivers is essential for a better estimation of pollutant dispersion. This coefficient is evaluated from tracing experiments or from semi‐empirical equations assuming uniform flow conditions. This assumption, verified for laboratory experiments, is questionable for river studies. For example, piedmont rivers exhibit nonuniform flows due to their longitudinal morphological variations. This work aims at studying the longitudinal variability of the transverse mixing coefficient in a river with longitudinally varied morphology and the overlooked impact of the flow nonuniformity on the coefficient's values. Tracing experiments were conducted in the Durance River in France using slug injections and concentration measurements made at the cross‐sections delineating homogeneous sub‐reaches. Using the well‐known 1D transverse diffusion model, values of the transverse mixing coefficient are determined for all consecutive sub‐reaches. These values substantially vary along the studied river, with stronger mixing efficiency at pools and complex riffles and weaker mixing efficiency in straight sub‐reaches with emerging obstacles. The dimensionless transverse mixing coefficient is strongly related to a parameter quantifying the deviation from flow‐uniformity, i.e., indicating flow acceleration, deceleration or a succession of both within the sub‐reaches. While usual formulas from the literature fail to predict our empirical results, a new equation including the flow nonuniformity parameter fits our experimental data with high accuracy. After further validation, such equation may be used for predicting the transverse mixing coefficient in rivers with longitudinally varied morphology. Key Points: Tracing experiments in a shallow, gravel‐bedded river yield highly variable transverse mixing coefficientsUsual predictive formulas fail to predict reach‐averaged transverse mixing coefficients in a river with longitudinally varied morphologyAn equation based on a flow nonuniformity parameter is fitted to our experimental data [ABSTRACT FROM AUTHOR]

The stage‐discharge rating curve is subject at many hydrometric stations to sudden changes (shifts) typically caused by morphogenic floods. We propose an original method for estimating shift times using the stage‐discharge observations, also known as gaugings. This method is based on a recursive segmentation procedure that accounts for both gaugings and rating curve uncertainties through a Bayesian framework. It starts with the estimation of a baseline rating curve using all available gaugings. Then it computes the residuals between the gaugings and this rating curve with uncertainties. It proceeds with the segmentation of the time series of residuals through a multi‐change point Bayesian estimation accounting for residuals uncertainties. Once the first set of shift times is identified, the same procedure is recursively applied to each sub‐period through a "top‐down" approach searching for all effective shifts. The proposed method is illustrated using the Ardèche River at Meyras in France (a typical hydrometric site subject to river bed degradation) and evaluated using several synthetic data sets for which the true shift times are known. The applications confirm the added value of the recursive segmentation compared with a "single‐pass" approach and highlight the importance of properly accounting for uncertainties in the segmented data. The recursive procedure effectively disentangles rating changes from observational and rating curve uncertainties. Plain Language Summary: For many hydrological and hydraulic issues, such as flood forecasting, a reliable river discharge estimate is needed. In general, discharge is derived from the recorded water level (stage) through a stage‐discharge relation (rating curve). This relation is calibrated using direct observations (gaugings). Unfortunately, the rating curve is not only uncertain but it can also be subject to sudden changes or shifts due for example to intense floods that modify the river bed geometry. One solution to identify periods of rating curve stability is to apply a segmentation procedure to the gaugings. We propose in this paper an original recursive segmentation procedure that accounts for both gaugings and rating curve uncertainties. Key Points: We propose a method for detecting rating shifts through the segmentation of residuals between the gaugings and a reference rating curveThe method accounts for observational and rating curve uncertainties and expresses change points in terms of time (rather than position)The method recursively re‐estimates the reference rating curve to improve the detection of small shifts [ABSTRACT FROM AUTHOR]

Predicting mixing processes, especially transverse mixing, downstream of river confluences, is necessary for assessing and modeling the fate of pollutants transported in river networks, but it is still challenging. Typically, there is a lack of transverse mixing solutions implemented in 1‐D hydrodynamical models widely used in river engineering applications. To investigate the mixing processes developing downstream of a medium‐sized river confluence, three high‐resolution in situ surveys are conducted at the Rhône‐Saône confluence in France, based on geolocated specific conductivity and hydroacoustic measurements. Contrasting mixing situations are observed depending on hydrological conditions. In some cases, the two flows mix slowly due to turbulent shear at their vertical interface. This can be modeled by an analytical solution of the advection‐diffusion equation. In other cases, the waters from one of the two tributaries move under the waters of the other tributary. The induced local circulation enhances transverse mixing but not vertical mixing and the flow remains stratified vertically, which may be missed when surface or satellite images are analyzed qualitatively. Stratification may be predicted by comparing the time scales for shear and density‐driven adjustment. Shear‐dominated transverse mixing of depth‐averaged concentrations can be predicted analytically and implemented in 1‐D hydrodynamical models. However, the initiation of apparently rapid transverse mixing due to density‐driven circulation remains to be better understood and quantified. Plain Language Summary: Predicting how waters mix downstream of river confluences is necessary for assessing and modeling the fate of pollutants transported in river networks, but it is still challenging. Typically, there is a lack of transverse mixing solutions implemented in models widely used in river engineering applications. To investigate the mixing processes developing downstream of a medium‐sized river confluence, three high‐resolution in situ surveys are conducted at the Rhône‐Saône confluence in France. Contrasting slow or rapid mixing situations are observed depending on hydrological conditions. The transverse mixing of depth‐averaged concentrations can be predicted analytically and implemented in 1‐D hydrodynamical models. However, the initiation of rapid transverse mixing due to difference in fluid density remains to be better understood and quantified. Key Points: Three high‐resolution surveys of mixing are conducted downstream of a medium‐sized, symmetrical, low‐angle river confluenceShear‐dominated transverse mixing can be predicted analytically and implemented in 1‐D hydrodynamical modelsVarious criteria are tested to predict vertical stratification due to density effects, inducing apparently rapid mixing [ABSTRACT FROM AUTHOR]

Stage-fall-discharge (SFD) rating curves are traditionally used to compute streamflow records at sites where the energy slope of the flow is variable due to variable backwater effects. We introduce a model with hydraulically interpretable parameters for estimating SFD rating curves and their uncertainties. Conventional power functions for channel and section controls are used. The transition to a backwater-affected channel control is computed based on a continuity condition, solved either analytically or numerically. The practical use of the method is demonstrated with two real twin-gauge stations, the Rhône River at Valence, France, and the Guthusbekken stream at station 0003⋅0033, Norway. Those stations are typical of a channel control and a section control, respectively, when backwater-unaffected conditions apply. The performance of the method is investigated through sensitivity analysis to prior information on controls and to observations (i.e., available gaugings) for the station of Valence. These analyses suggest that precisely identifying SFD rating curves requires adapted gauging strategy and/or informative priors. The Madeira River, one of the largest tributaries of the Amazon, provides a challenging case typical of large, flat, tropical river networks where bed roughness can also be variable in addition to slope. In this case, the difference in staff gauge reference levels must be estimated as another uncertain parameter of the SFD model. The proposed Bayesian method is a valuable alternative solution to the graphical and empirical techniques still proposed in hydrometry guidance and standards. [ABSTRACT FROM AUTHOR]

The objective of this paper is to characterize some of the sperm motility parameters in European hake ( Merluccius merluccius), which is considered to be a species with aquaculture potential. The total ATP, ADP and AMP concentrations were determined using high-performance liquid chromatography on hake sperm samples collected during the winter-early spring in the Bay of Biscay (France) (n = 22) and on hake sperm samples collected during the summer-early autumn in waters off Western Norway (n = 5). The Adenylate Energy Charge (AEC) was deduced from these data. Computer Assisted Sperm Analysis (CASA) was used to measure a series of parameters characterizing the motility and the sperm swimming performances. Changes in salinity of the swimming medium affected all the measured motility parameters. The sperm velocity and the straightness of the movement were at maximum when sperm was activated with 100% filtrated sea water (100 SW) but decreased sharply later. When sperm was activated in filtrated sea water (50% diluted with distilled water: 50 SW) the values of these parameters increased (with a lower percentage of active cells) during the first 2.5 min and thereafter decreased slowly. In 50 SW, the initial velocity was lowered but the swimming period lasting 4.5 times longer than in 100 SW (but with a lower percentage of actively swimming cells). Initial sperm motility (percentage of swimming cells) in 100 SW was affected by sperm storage duration. Undiluted sperm could be stored at 4°C for 5 days and still show 13 ± 7% motility; the velocity and straightness of the movement were at maximum at the earliest period of measurement (0.5–1 day of storage) and then decreased gradually to reach their minima after 4 days of storage. Further, both the AEC and ATP content decreased with storage time, with the AEC decreasing from 0.78 ± 0.07 (mean ± SD) at stripping time to 0.20 ± 0.09 after 2 days of storage. Over the same period ATP content decreased from 85 ± 80 to 5 ± 4 nanomoles 10−9 spermatozoa, these data presenting a high variability. [ABSTRACT FROM AUTHOR]

• The method aims to detect stage-discharge hysteresis at gauging stations. • The method can be applied easily to a large set of gauging stations. • The hysteresis is quantified based on simple hydraulic concepts (Jones equation). • The use of bed slopes indicative of hydraulic controls is a key for good diagnosis. A generic framework is proposed to evaluate the relative discharge error made when ignoring stage-discharge hysteresis due to transient flow over large gauging station networks. The diagnosis is conducted using the Jones equation, a simple hydraulic concept relating discharge to stage and its time-gradient. The input data used for the method are the flow resistance coefficients, the temporal stage gradients, and the bed slopes. The hysteresis effect is quantified for each gauging station and mapped using the relative discharge error. The method was applied to 2618 gauging stations of France's national hydrometry network using data extracted from the national hydrological archive and from Digital Terrain Models. The diagnostic results highly depend on slope estimates used as inputs. Substantial hysteresis effects were found at stations with low bed slope combined with a fast flood regime. The application to France shows the difficulty of drawing a firm conclusion about stations prone to hysteresis due to the slope data uncertainty. This issue is not specific to France; slope estimates over a network of hydrometric stations are difficult to obtain in many countries. The use of local bed slope estimates is recommended to approach the slopes of the reaches controlling the station stage-discharge relation. [ABSTRACT FROM AUTHOR]

The Rhône River (France) has been used for energy production for decades and 21 dams have been built. To avoid problems due to sediment storage, dam flushing operations are periodically organized. The impacts of such operations on suspended particulate matter (SPM) dynamics (resuspension and fluxes) and quality (physico-chemical characteristics and contamination), were investigated during a flushing operation performed in June 2012 on 3 major dams from the Upper Rhône River. The concentrations of major hydrophobic organic contaminants (polychlorinated biphenyls, polycyclic aromatic hydrocarbons - PAHs, bis(2-ethylhexyl)phthalate [DEHP] and 4-n-nonylphenol), trace metal elements, particulate organic carbon (POC) and particle size distribution were measured on SPM samples collected during this event as well as on those obtained from 2011 to 2016 at a permanent monitoring station (150 km downstream). This allows to compare the SPM and contaminant concentrations and fluxes during the 2012 dam flushing operations with those during flood events and baseflow regime. At equal water discharge, mean SPM concentrations during flushing were on average 6-8 times higher than during flood events recorded from 2011 to 2016. While of short duration (19 days), the flushing operations led to the resuspension of SPM and contributed to a third of the mean annual SPM flux. The SPM contamination was generally lower during flushing than during baseflow or flood, probably due to the fact that flushing transports SPM only issued from resuspended sediment, with no autochtonous particles nor eroded soil. The only exception are PAHs and DEHP with higher concentrations during flushing, which must be issued from the resuspension of legacy-contaminated sediments stored behind the dams before the implementation of emission regulations. During flushing, the variations of POC and contaminant concentrations are also mostly driven by particle size. Finally, we propose a list of recommendations for the design of an adequate monitoring network to evaluate the impact of dam flushing operations on large river systems., (Copyright © 2019 Elsevier Ltd. All rights reserved.)