Evaluation of long-term bedload virtual velocity in gravel-bed rivers (Ardenne, Belgium)

Houbrechts, Geoffrey; Levecq, Yannick; Peeters, Alexandre; Hallot, Éric; Campenhout, Jean Van; Denis, Anne-Cécile; Petit, François

doi:10.1016/j.geomorph.2015.05.012

Cited by 34 publications

(52 citation statements)

References 81 publications

(131 reference statements)

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“…For both the control and the restored reaches, the mobility appears to decrease with subsequent floods, as pm is significantly lower in the third flood as compared to the first flood, despite the higher peak magnitude of the flooding in the third period. Reduced mobility of tracers is expected from previous studies [50,66], particularly where the initial particles are seeded loosely on the bed of the channel as they were in this case. Table 2.…”

Section: Basic Particle Tracking Statisticssupporting

confidence: 50%

“…Table 2. Particle tracking statistics for the three flooding periods in both the control and restoration reaches, where nt is the total number of particles present in the reach, nl is the number located in the survey, ninf is the number of inferred particles, nf is the number of found particles, pf is the percentage of found particles, nfb is the number of particles found in both the beginning and end surveys for each period, pfb is the percentage of particles found in both surveys, nm is the number of particles that moved, pm is the percentage of moved particles, CIpm is the confidence interval for pm, 50 …”

Section: Basic Particle Tracking Statisticsmentioning

confidence: 99%

“…In the third flood, travel distance confidence intervals overlap with those in the second flood and slightly overlap between the reaches. The relatively small overlap (~1 m, or <5% of 50 …”

Section: Lmentioning

confidence: 99%

“…For instance, a number of studies in mixed-gravel beds have demonstrated the prevalence of partial mobility [37][38][39][40], and characterized the relation between particle size and travel distance [41][42][43]. Tracking methods using Radio Frequency Identification (RFID) transponders have become common in the research community due to their advantages over other tracking technologies in terms of individualized particle displacement information, low cost, battery-free nature and robust design [44][45][46][47][48][49][50][51]. Sediment tracking has been used to assess some restoration projects [52][53][54] but its potential for testable hypotheses to assess restoration outcomes has yet to be fully realized.…”

Section: Introductionmentioning

confidence: 99%

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Assessing the Performance of In-Stream Restoration Projects Using Radio Frequency Identification (RFID) Transponders

MacVicar

Chapuis

Buckrell

et al. 2015

Water

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Abstract:Instream channel restoration is a common practice in river engineering that presents a challenge for research. One research gap is the development of monitoring techniques that allow for testable predictions of sediment transport and supply. Here we use Radio Frequency Identification (RFID) transponders to compare the short-term (1-year) sediment transport response to flood events in a restored and a control reach. The field site is Wilket Creek, an enlarged creek in a fully urbanized catchment without stormwater management control in Toronto, Ontario. The responses to three flooding periods, each of which are at or above the design bankfull discharge, are described. Key results are that (i) particle mobility is lower in the restored reach for all three periods; (ii) full mobility occurs in the control reach during the first two floods while partial mobility occurs in the restored reach; and (iii) the constructed morphology exerted a controlling influence on particle entrainment, with higher mobility in the pools. Log-transformed travel distances exhibit normal distributions when grouped by particle size class, which allows a statistical comparison with power law and other predictive travel-distance relations. Results show that three bedload transport conditions can occur, with partial mobility associated with a OPEN ACCESSWater 2015, 7 5567 mild relation between particle size and travel distance and full mobility associated with either a flat or steep relation depending on the degree of integration of particles in the bed. Recommendations on seeding strategy and sample sizes are made to improve the precision of the results by minimizing confidence intervals for mobility and travel distances. Even in a short term study, the RFID sediment tracking technique allows a process-based assessment of stream restoration outcomes that can be used to justify the instream intervention and plan future attempts to stabilize and enhance the system.

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Section: Basic Particle Tracking Statisticssupporting

confidence: 50%

Section: Basic Particle Tracking Statisticsmentioning

confidence: 99%

“…In the third flood, travel distance confidence intervals overlap with those in the second flood and slightly overlap between the reaches. The relatively small overlap (~1 m, or <5% of 50 …”

Section: Lmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessing the Performance of In-Stream Restoration Projects Using Radio Frequency Identification (RFID) Transponders

MacVicar

Chapuis

Buckrell

et al. 2015

Water

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“…Entrainment of the marked grain seeds method is widely used to analyze flow competence (e.g., Petit et al, 2005;Houbrechts et al, 2015). However, in this study, it was not practical because of the fact that (i) particle recovery is almost impossible (Ryan and Troendle, 1997) and (ii) in places like our study area where streams are a source of water for livestock and for domestic uses, painted grains catch the attention of children and hence they are subject to disturbance.…”

Section: Class Definitionmentioning

confidence: 99%

Sediment flux dynamics as fingerprints of catchment rehabilitation: The case of western Rift Valley escarpment of northern Ethiopia

et al. 2015

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Particle transport in gravel‐bed rivers: Revisiting passive tracer data

Vázquez‐Tarrío

Recking

Liébault

et al. 2018

Earth Surf Processes Landf

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Data from tracer experiments were compiled and analysed in order to explore the role of geomorphological, hydrological and sedimentological constraints on fluvial gravel transport in gravel‐bed rivers. A large data set from 217 transport episodes of tagged stones were compiled from 33 scientific papers. Our analyses showed that while magnitude of peak discharge is a major control on gravel transport and mobility, tracer travel distances show some scale dependence on the morphological configuration of the channel. Our results also highlight differences in the way tracers are displaced between step–pool and riffle and pool channels. The riffle–pool sequence seems to be a more efficient trap for travelling gravels than the step–pool pair. In addition, in step–pool channels there are clear differences in tracer transport between observations of first displacements after tracer seeding (unconstrained‐stone conditions), and second and subsequent observations of tracer displacements (constrained‐stone conditions). The comparison between tracer experiments under constrained conditions and those under unconstrained conditions also highlights the importance of bed state and structures in gravel mobility. The results of this study confirm that sediment transport in gravel‐bed rivers is a complex process, whereby sedimentological and geomorphological controls are superimposed on the hydraulic forcing. © 2018 John Wiley & Sons, Ltd.

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Evaluation of long-term bedload virtual velocity in gravel-bed rivers (Ardenne, Belgium)

Cited by 34 publications

References 81 publications

Assessing the Performance of In-Stream Restoration Projects Using Radio Frequency Identification (RFID) Transponders

Assessing the Performance of In-Stream Restoration Projects Using Radio Frequency Identification (RFID) Transponders

Sediment flux dynamics as fingerprints of catchment rehabilitation: The case of western Rift Valley escarpment of northern Ethiopia

Particle transport in gravel‐bed rivers: Revisiting passive tracer data

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