Momentum and Energy Predict the Backwater Rise Generated by a Large Wood Jam

Follett, Elizabeth; Schalko, Isabella; Nepf, Heidi

doi:10.1029/2020gl089346

Cited by 36 publications

(85 citation statements)

References 53 publications

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“…Water approaching a jam with a lower gap partitions between the porous jam and the gap beneath the jam. Flow exiting the jam adopted an elevated height

h_{j} > a

(Figure 2) similar to previous observations of flow through channel‐spanning jams without a lower gap (Follett et al., 2020). Negligible exchange of flow between the jam and gap sections was visually observed from injections of rhodamine dye.…”

Section: Theorysupporting

confidence: 87%

“…Upstream water depth

h_{0}

was measured

L_{c v} = 1

m upstream of jam leading edge. Discharge through the jam

q_{j}

calculated for yellow control volume extending from

x = x_{a}

x_{j}

and

z = a

h_{0}, h_{j}

(Follett et al., 2020). Discharge through the gap

q_{a}

estimated for blue control volume

x = x_{0}

x_{a}

and

z = 0

h_{0}

, accounting for discharge through the jam.…”

Section: Methodsmentioning

confidence: 99%

“…Note that this neglects additional losses that occur along the length of the gap, an assumption which degrades as the jam length increases. Within the jam, conservation of momentum reduces to a balance of hydrostatic pressure and drag on jam elements, which provides a relation between the upstream water depth (

h_{0}

) and discharge through the jam (

q_{j}

) (Equation 6 in Follett et al., 2020),

h_{0} - a = \sqrt{3} {(\frac{C_{A} q_{j}^{2}}{2 g})}^{1 / 3} .

…”

Section: Theorymentioning

confidence: 99%

“…The drag within the jam is characterized by the jam accumulation factor

C_{A} = \frac{L_{j} C_{D} a_{f}}{{(1 - ϕ)}^{3}}

(Follett et al., 2020) with spatial average frontal area density

a_{f}

. By rearrangement of Equation , the discharge passing through the jam layer is

q_{j} = {[\frac{2 g {((), h_{0} - a)}^{3}}{3 \sqrt{3} C_{A}}]}^{1 / 2}

…”

Section: Theorymentioning

confidence: 99%

See 3 more Smart Citations

Logjams With a Lower Gap: Backwater Rise and Flow Distribution Beneath and Through Logjam Predicted by Two‐Box Momentum Balance

Follett

Schalko

Nepf

2021

Geophysical Research Letters

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“…Water approaching a jam with a lower gap partitions between the porous jam and the gap beneath the jam. Flow exiting the jam adopted an elevated height

h_{j} > a

Section: Theorysupporting

confidence: 87%

“…Upstream water depth

h_{0}

was measured

L_{c v} = 1

m upstream of jam leading edge. Discharge through the jam

q_{j}

calculated for yellow control volume extending from

x = x_{a}

x_{j}

and

z = a

h_{0}, h_{j}

(Follett et al., 2020). Discharge through the gap

q_{a}

estimated for blue control volume

x = x_{0}

x_{a}

and

z = 0

h_{0}

, accounting for discharge through the jam.…”

Section: Methodsmentioning

confidence: 99%

h_{0}

) and discharge through the jam (

q_{j}

) (Equation 6 in Follett et al., 2020),

h_{0} - a = \sqrt{3} {(\frac{C_{A} q_{j}^{2}}{2 g})}^{1 / 3} .

…”

Section: Theorymentioning

confidence: 99%

“…The drag within the jam is characterized by the jam accumulation factor

C_{A} = \frac{L_{j} C_{D} a_{f}}{{(1 - ϕ)}^{3}}

(Follett et al., 2020) with spatial average frontal area density

a_{f}

. By rearrangement of Equation , the discharge passing through the jam layer is

q_{j} = {[\frac{2 g {((), h_{0} - a)}^{3}}{3 \sqrt{3} C_{A}}]}^{1 / 2}

…”

Section: Theorymentioning

confidence: 99%

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Logjams With a Lower Gap: Backwater Rise and Flow Distribution Beneath and Through Logjam Predicted by Two‐Box Momentum Balance

Follett

Schalko

Nepf

2021

Geophysical Research Letters

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“…The random variation in β i between mixtures, repetitions, volume of LW and water discharge is higher than the eventual effect of fine material. Follett et al (2020) recently demonstrated that head losses were related to the projected area of the material (coarse and fine) constituting the jam. Our fine material was not fine enough to percolate through the accumulation to densify it and to increase the projected area as leaves and fine organic matter would.…”

Section: First Step Toward Generalizationmentioning

confidence: 99%

Open check dams and large wood: head losses and release conditions

Piton¹,

Horiguchi²,

Marchal³

et al. 2020

Nat. Hazards Earth Syst. Sci.

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Abstract. Open check dams are strategic structures to control sediment and large-wood transport during extreme flood events in steep streams and piedmont rivers. Large wood (LW) tends to accumulate at such structures, obstruct their openings and increase energy head losses, thus increasing flow levels. The extent and variability to which the stage–discharge relationship of a check dam is modified by LW presence has so far not been clear. In addition, sufficiently high flows may trigger a sudden release of the trapped LW with eventual dramatic consequences downstream. This paper provides experimental quantification of LW-related energy head loss and simple ways to compute the related increase in water depth at dams of various shapes: trapezoidal, slit, slot and sabo (i.e. made of piles), with consideration of the flow capacity through their open bodies and atop their spillways. In addition, it was observed that LW is often released over the structure when the overflowing depth, i.e. total depth minus spillway elevation, is about 3–5 times the mean log diameter. Two regimes of LW accumulations were observed. Dams with low permeability generate low velocity upstream, and LW then accumulates as floating carpets, i.e. as a single floating layer. Conversely, dams with high permeability maintain high velocities immediately upstream of the dams and LW tends to accumulate in dense complex 3D patterns. This is because the drag forces are stronger than the buoyancy, allowing the logs to be sucked below the flow surface. In such cases, LW releases occur for higher overflowing depth and the LW-related head losses are higher. A new dimensionless number, namely the buoyancy-to-drag-force ratio, can be used to compute whether (or not) flows stay in the floating-carpet domain where buoyancy prevails over drag force.

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Physical modelling of large wood (LW) processes relevant for river management: Perspectives from New Zealand and Switzerland

Friedrich

Ravazzolo

Ruíz-Villanueva

et al. 2021

Earth Surf Processes Landf

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In the last 30 years, work on large wood (LW) has expanded and matured considerably, and river scientists, managers and practitioners now have a better appreciation of the role of LW in maintaining ecosystems, forming or stabilizing riverine landforms, and interacting with river morphodynamics. We have gained a better understanding of the hazards posed by the recruitment and transport of LW in the river channel and associated infrastructure. While LW dynamics have traditionally been studied in the natural river environment, innovations in laboratory techniques have enabled important advances in understanding LW process dynamics, using physical scale models, new sensors, scanners and sophisticated model boundary conditions. Current trends in LW laboratory research focus on (1) mobilization and transport of logs, (2) trapping and deposition of sediment in the presence of LW and(3) LW contribution to hydraulic flow resistance. Ultimately, a combined process understanding is needed to assess impacts upon infrastructure with erodible boundaries, such as bridge piers and LW retention racks. In this review, we present a critical analysis of emerging experimental work on LW obtained through physical modelling studies. We put recent experimental work in context with global LW management challenges. In particular, we set our work in context with the present environmental and engineering issues that confront catchment and natural resource managers in Switzerland and New Zealand. We show how improved physical models incorporating LW transport, accumulation and scouring processes are needed to contribute to more reliable hazard and risk assessment and improved river management in LW-prone systems.

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Momentum and Energy Predict the Backwater Rise Generated by a Large Wood Jam

Cited by 36 publications

References 53 publications

Logjams With a Lower Gap: Backwater Rise and Flow Distribution Beneath and Through Logjam Predicted by Two‐Box Momentum Balance

Logjams With a Lower Gap: Backwater Rise and Flow Distribution Beneath and Through Logjam Predicted by Two‐Box Momentum Balance

Open check dams and large wood: head losses and release conditions

Physical modelling of large wood (LW) processes relevant for river management: Perspectives from New Zealand and Switzerland

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