Long term evolution of a dam reservoir subjected to regular flushing events

Guertault, Lucie; Camenen, B.; Peteuil, Christophe; Paquier, André

doi:10.5194/adgeo-39-89-2014

Cited by 14 publications

(14 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Finally, we calculated net change in sediment volume as:

normalΔ V_{j} = D_{j} normalΔ A_{j}

where Δ A j is the cross‐sectional area difference between S i 1 and S i 2 for the j th CS and

D_{j} = ((),, \frac{1}{2} L_{j - 1} + \frac{1}{2} L_{j})

, with L j the longitudinal distance between the j th and ( j + 1)th CSs (Guertault et al , ). In cases where L j − 1 or L j were not defined, we considered

D_{j} = \frac{1}{2} L_{j}

D_{j} = \frac{1}{2} L_{j - 1}

respectively.The uncertainty in sediment volumes due to transversal interpolation, smoothing and systematic bias is:

u_{t, j} = D_{j} E_{t, j}

Following Guertault et al (), we calculated the uncertainty in sediment volume due to the longitudinal interpolation between CSs. When the channel geometry is very different between consecutive CSs, the hypothesis of a constant evolution of sediment volume can be questioned.…”

Section: Methodsmentioning

confidence: 99%

Monitoring gravel augmentation in a large regulated river and implications for process‐based restoration

Arnaud

Piégay

Béal

et al. 2017

Earth Surf Processes Landf

View full text Add to dashboard Cite

International audienceThe artificial gravel augmentation of river channels is increasingly being used to mitigate the adverse effects of river regulation and sediment starvation. A systematic framework for designing and assessing such gravel augmentations is still lacking, notably on large rivers. Monitoring is required to quantify the movement of augmented gravel, measure bedform changes, assess potential habitat enhancement, and reduce the uncertainty in sediment management. Here we present the results of an experiment conducted in the Rhine River (French and German border). In 2010, 23 000 m3 of sediments (approximately the mean annual bedload transport capacity) were supplied in a by-passed reach downstream of the Kembs dam to test the feasibility of enhancing sediment transport and bedform changes. A 620-m-long and 12-m-wide gravel deposit was created 8 km downstream from the dam. Monitoring included topo-bathymetric surveys, radio-frequency particle tracking using passive integrated transponder (PIT) tags, bed grain size measurement, and airborne imagery. Six surveys performed since 2009 have been described (before and after gravel augmentation, and after Q2 and Q15 floods). The key findings are that (i) the augmented gravel was partially dispersed by the first flood event of December 2010 (Q1); (ii) PIT tags were found up to 3200 m downstream of the gravel augmentation site after four years, but the effects of gravel augmentation could not be clearly distinguished from the effects of floods and internal remobilization on more than 3500 m downstream; (iii) linear and log-linear relationships linking bedload transport, particle mobility, and grain size were established; and (iv) combined bathymetry and PIT tag surveys were useful for evaluating potential environmental risks and the first morpho-ecological responses. This confirmed the complementary nature of such techniques in the monitoring of gravel augmentation in large rivers

show abstract

“…Finally, we calculated net change in sediment volume as:

normalΔ V_{j} = D_{j} normalΔ A_{j}

where Δ A j is the cross‐sectional area difference between S i 1 and S i 2 for the j th CS and

D_{j} = ((),, \frac{1}{2} L_{j - 1} + \frac{1}{2} L_{j})

, with L j the longitudinal distance between the j th and ( j + 1)th CSs (Guertault et al , ). In cases where L j − 1 or L j were not defined, we considered

D_{j} = \frac{1}{2} L_{j}

D_{j} = \frac{1}{2} L_{j - 1}

respectively.The uncertainty in sediment volumes due to transversal interpolation, smoothing and systematic bias is:

u_{t, j} = D_{j} E_{t, j}

Section: Methodsmentioning

confidence: 99%

Monitoring gravel augmentation in a large regulated river and implications for process‐based restoration

Arnaud

Piégay

Béal

et al. 2017

Earth Surf Processes Landf

View full text Add to dashboard Cite

show abstract

“…Large sedimentation occurred in the reservoir, and the storage loss by 2012 was estimated to be 36% of the initial storage capacity (Guertault et al. ). Comparison between the 1954 and 2011 longitudinal profiles showed that the upstream portion of the reservoir has been affected by bed incision, caused by the reduction of sediment transport due to upstream dams, and gravel mining activities performed from the 1970s to the 1990s (Figure a).…”

Section: The Génissiat Dam Reservoirmentioning

confidence: 99%

“…However, this last objective has not always been met, as the long‐term sediment budget of the Génissiat Reservoir showed that half of the sediment accumulation occurred during flushing operations of upstream dams (Guertault et al. ).…”

Section: The Génissiat Dam Reservoirmentioning

confidence: 99%

“…Unlike natural rivers, a wide range of flow conditions can impact the morphodynamics of reservoirs, from high water‐level flows promoting sediment deposition to flushing flows designed to erode sediment deposits (Guertault et al. ). Accordingly, three flow conditions differentiating between normal operation flows and flushing flows were simulated to derive flow variables for the Génissiat reservoir: a normal operation scenario S1 with a reservoir inflow Q =600 m 3 s −1 and dam level Z =330 m; an intermediate‐level flushing scenario S2 with Q =300 m 3 s −1 and Z =315 m; a low‐level flushing scenario S3 with Q =300 m 3 s −1 and Z =305 m. …”

Section: Observed Sediment Dynamics In the Reservoirmentioning

confidence: 99%

See 1 more Smart Citation

A one‐dimensional process‐based approach to study reservoir sediment dynamics during management operations

Guertault

Camenen²,

Paquier³

et al. 2017

Earth Surf Processes Landf

View full text Add to dashboard Cite

A comprehensive understanding of the dynamics of erosion and sedimentation in reservoirs under different management conditions is required to anticipate sedimentation issues and implement effective sediment management strategies. This paper describes a unique approach combining fluvial geomorphology tools and morphodynamic modeling for analyzing the sediment dynamics of an elongated hydropower reservoir subjected to management operations: the Génissiat Reservoir on the Rhône River. Functional sub‐reaches representative of the reservoir morphodynamics were delineated by adapting natural river segmentation methods to elongated reservoirs. The segmentation revealed the link between the spatial and temporal reservoir changes and the variability of longitudinal flow conditions during reservoir management operations. An innovative modeling strategy, incorporating the reservoir segmentation into two sediment transport codes, was implemented to simulate the dynamics of erosion and sedimentation at the reach scale during historic events. One code used a bedload approach, based on the Exner equation with a transport capacity formula, and the other used a suspended load approach based on the advection–dispersion equation. This strategy provided a fair quantification of the dynamics of erosion and sedimentation at the reach scale during different management operations. This study showed that the reservoir morphodynamics is controlled by bedload transport in upper reaches, graded suspended load transport of sand in middle reaches and suspended load transport of fine sediments in lower reaches. Eventually, it allowed a better understanding of the impact of dam management on sediment dynamics. Copyright © 2017 John Wiley & Sons, Ltd.

show abstract

“…Although they have been successfully used to understand and reproduce to some extent complex physical processes that occur in nature, and have contributed significantly in hydraulic construction designs, they are relatively costly and time consuming [12]. More recently photogrammetry-based surveys using unmanned aerial systems have been used to evaluate flushed sediments [13][14][15]. Moreover, such techniques can only compute the amount of flushed sediments only when the reservoir is dry (i.e., empty), and subsequent images are necessary to compute the Digital Elevation Models (DEMs) of difference, from which the flushing efficiencies may be computed.…”

Section: Introductionmentioning

confidence: 99%

Estimating Sediment Flushing Efficiency of a Shaft Spillway Pipe and Bed Evolution in a Reservoir

Chen

Tsai

2017

Water

View full text Add to dashboard Cite

Abstract:Control of reservoir sedimentation in order to ensure their sustainable use has drawn attention among water engineers and water resource managers. Several methods have been proposed, but most of the developed methodologies are incapable of modelling bed evolutions, while at the same time, compute sediment flushing efficiency. In this study a two-dimensional bed evolution model is proposed to estimate sediment distribution, bed evolution and sediment flushing efficiency of reservoirs. A-Gong-Dian reservoir, in southern Taiwan, is used as an illustrative example. Typhoon events were used to verify the proposed model. Simulations were conducted for one and two-day storm events under return periods, 2, 5, 10, 25, 50, 100, and 200-year. The results indicated that the average sediment flushing efficiency of the shaft spillway under one and two-day storms were close, 58.50% and 59.39%, respectively. These results were similar to observed laboratory tests experiments, where an efficiency of 65.34% was obtained. This study suggests that the applied model could be adopted to ensure the sustainable use of reservoirs, and also to find an optimal area for the location of a shaft spillway pipe. Therefore, the proposed model could serve as a reference to the reservoir management personnel.

show abstract

Long term evolution of a dam reservoir subjected to regular flushing events

Cited by 14 publications

References 1 publication

Monitoring gravel augmentation in a large regulated river and implications for process‐based restoration

Monitoring gravel augmentation in a large regulated river and implications for process‐based restoration

A one‐dimensional process‐based approach to study reservoir sediment dynamics during management operations

Estimating Sediment Flushing Efficiency of a Shaft Spillway Pipe and Bed Evolution in a Reservoir

Contact Info

Product

Resources

About