Johnson 2

The application of a two-dimensional sediment transport

model in a Cumberland Plateau mountainous stream reach

with complex morphology and coarse substrate

Those who thoughtlessly make use of the miracles of science and

technology, without understanding more about them than a cow eating

plants understands about botany, should be ashamed of themselves.

(Einstein).

Daniel Johnson and Dr. John Schwartz

SRI conference

November, 5th 2008

Coastal Science & Engineering

Background

USACOE

• A calibrated computational model canfacilitate the design process.

• A computational model can be a powerfultool for investigating sediment transportand in-stream hydrodynamic processes(Chen et al., 2007; Duan et al., 2007; Jiaet al., 1999; Jia et al., 2006; Langendoen,2001; Papanicolaou et al., 2008; Scott etal., 2005; White, 2008; Wu, 2008).

Two-dimensional sediment transport modeling

• If the vertical variations of flow and sediment quantities in a water body are sufficiently small orcan be determined analytically, their variations in the horizontal plane can be approximatelydescribed by a depth-averaged 2D model (Wu, 2008).

CCHE2D Output

• Abbreviated (2D)

• Simulate the transverse and longitudinal

velocity component

• Structured grids

• Increased complexity necessitates

significantly more data input

• Does not require the computational

capacity of a 3D model

• 2D depth averaged models assume the

vertical variations of flow and sediment

quantities are sufficiently small.

• Incorporates turbulence through depth

averaged eddy viscosity coefficients

• Examples: CCHE2D, DELFT2D,

FLUVIAL 12, and MIKE 21

Study background

• Study Objective

– Determine the sensitivity of model output (at various scales) to the Manning’s n variable and

upstream sediment rating curves.

– Scales of interest:

• Reach scale > 100 m

• Local scale ~ 10 m

• Point scale ~ 1 m

– Ligias Creek (study site)

– CCHE2D (model)

Study site (Ligias Creek)

2

1

2

1

2

CCHE2D

• Two-dimensional, depth averaged, with unsteady flow and sediment transport capabilities.

• Developed at the National Center for Computational Hydroscience and Engineering (NCCHE)

• includes a Graphical Users Interface (CCHE-GUI) and a structured mesh generator (CCHE2D MeshGenerator).

• Simulates both suspended load and bedload transport

• Solves the Navier-Stokes equations

Input data requirements

• What is required to perform a sediment transport simulation?

– Channel geometry (physical domain described by a structured mesh)

– Upstream and downstream hydraulic boundary conditions

– Calculated Manning’s n value

• Discharge or velocity measurements

• Measured cross sectional area

• Measured wetted perimeter

• Measured Energy slope

– Upstream sediment boundary conditions

• Bedload rating curve

• Suspended load rating curve

2/13/2 SRn

kV n

Manning’s equation

(Langendoen, 2000)

Channel geometry & monitoring points

Developed mesh (3D view) [looking upstream from downstream

modeling boundary]

In-stream velocity & energy slope measurements

Marsh-McBirney™ Flo-mate Model

2000 Flowmeter.

Ligias Fork

Stage-Discharge Plot

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

2.25

2.50

2.75

0 10 20 30 40 50 60 70 80 90 100

Stream Discharge (m3/sec)

Str

eam

Sta

ge

Rea

din

g (

met

ers)

Measured

Simulated

Global Water™ Stage Recorders

(Model No. WL-16)

Energy Slope vs. Time

0.0038

0.0042

0.0046

0.0050

0.0054

0.0058

0.0062

0.0066

03/23 03/28 04/02 04/07 04/12 04/17 04/22 04/27 05/02 05/07 05/12

Time (mm/dd)

En

erg

y S

lop

e (

ft/f

t)

92.750

93.250

93.750

94.250

94.750

95.250

95.750

96.250

96.750

97.250

97.750

98.250

98.750

99.250

ENERGY SLOPE DS WSEL US WSEL

Measured water surface and calculated energy slope

Stream stage (m) versus discharge (cms)

Suspended load sampling & rating curve

H-48 Depth Integrated Sediment

Sampler (Model 5200)

Suspended sediment rating curve

Bedload trap (net-frame sampler)

1. Allow for the collection of a physical sample for sieve analysis

2. Can be utilized for a long sampling duration

3. Portable

4. Require minimal stream excavation

•Bunte K., Abt S.R., Potyondy J.P., and S.E. Ryan. (2004). “Measurement of Coarse Gravel and

Cobble Transport Using Portable Bedload Traps.” Journal of Hydraulic Engineering, Vol. 130,

No.9, pp. 879-893

Net-frame sampler Base

Aluminum trapTrailing net

Bedload sample Bedload sample

Net-frame sampler in action

Calculated bedload rating curve

• Meyer-Peter and Muller

– Energy slope

– Critical diameter

– Water depth

– Shields parameter

– Critical value of shields parameter (0.047)

– Hiding coefficient, equal to a value of 0.7, was implemented to account for the bimodal bed

gradation and the influence of hiding and exposure effects on sediment transport.

2

3

*3

)047.0(0.8)1( s

bb

gdSG

q

sdSG

Sy

1

0*

Meyer-Peter and Muller empirical formula

(Sturm, 2001)

Shields parameter

(Sturm, 2001)

Summary of methods

• Bed elevation change was measured at multiplemonitoring points after a significant storm event.

• A bedload rating curve was calculated (Meyer-Peter& Muller equation) and applied at the upstreamboundary

• A suspended load rating curve was developedbased on measured suspended sediment samples

• A manning’s n value was calculated based onavailable energy slope data

• Initial simulations began with a Manning’s n valueequal to 0.025 (value calculated based onmeasured energy slope data) and calculatedsediment rating curves (100% bedload, 100%suspended load).

• Additional model simulations were performed byvarying the Manning’s n variable and upstreamsediment rating curves.

• Simulated and measured bed elevation changeresults were compared at the reach, local, and pointscales.

• Multivariate statistical methods were implementedto determine the correlation and sensitivity of modeloutput (bed elevation change) to the variousindependent variables (Manning’s n variable,suspended sediment rating curve, bedload ratingcurve)

Description

Manning's n

value Description

Manning's n

value

0% suspended, 0% Bedload 0.01 10% suspended, 0% Bedload 0.025

0% suspended, 0% Bedload 0.015












0% suspended, 0% Bedload 0.055 25% Suspended, 5% Bedload 0.050

0% Suspended, 1% Bedload 0.025 30% suspended, 0% bedload 0.025

0% Suspended, 1% Bedload 0.035

40% suspended, 0% bedload 0.025



0% Suspended, 20% Bedload 0.025 5% suspended, 5% Bedload 0.035









Manning's n value Bedload Suspended load

0.01 - 0.065 0% - 50% 0% - 100%

Successful model simulations (variable range)

Modeling resultsBed elevation change as a function of channel roughness

0% Suspended load, 5% Bedload, 0.025 Manning’s n value

0% Suspended load, 5% Bedload, 0.055 Manning’s n value 0% Suspended load, 0% Bedload, 0.05 Manning’s n value


Modeling resultsBed elevation change as a function of sediment inflows




Study findings

• Extensive effort and time are required to obtainreasonable model input data

– bedload sampling is particularly problematic

– Critical field measurements include:

• time varying bedload transport rates as afunction of discharge

• energy slope as a function of discharge(Manning’s n calculation)

• and discharge as a function of time

• It is critical to obtain sufficient measurementsduring peak discharges or seasonally highdischarge rates

• The model appears most sensitive to the bedloadsediment rating curve at the upstream boundary.

– If the bedload rating curve is not reasonable,sediment mass builds at the entrance to thefinite element cells producing increased bedelevations, a hydraulic backwater at theupstream boundary, and ultimately numericalinstability.

• The model appears most sensitive to theManning’s n value at the downstream modelingboundary.

– When the roughness value is small, depthaveraged local velocities increase and erosionaccelerates near the downstream boundary.

Sediment mass accumulating at the upstream boundary, hydraulic

backwater and instability

Erosion accelerating near the downstream

boundary

2D modeling & stream restoration design

• Reliance on 2D sediment models without adequatedata collection and model calibration may lead topoorly designed stream restoration projects, andultimate project failure.

• In complex channels, 2D model performance at the

local, reach, or point scales is likely not possible with

current technology. However, in less complex

channels others have found existing 2D models work

reasonably well.

• It appears the current state-of-practice for stream

restoration must rely on 1D reach-scale sediment

transport models, with a general goal to determine

whether a reach is sediment-supply or capacity

limited.

• 2D models may be best implemented to analyze local

scale hydrodynamic processes.

– sediment transport can then be analyzed

analytically based on the hydraulic results

produced by the 2D model.

• In summary, it is very hard for a computational model

to precisely mimic the chaos and complex sediment

transport processes which occur in a natural channel.

Two-dimensional simulation results

The application of a two-dimensional sediment transport

model in a Cumberland Plateau mountainous stream reach

with complex morphology and coarse substrate

Those who thoughtlessly make use of the miracles of science and

technology, without understanding more about them than a cow eating

plants understands about botany, should be ashamed of themselves.

(Einstein).

Daniel Johnson and Dr. John Schwartz

SRI conference

November, 5th 2008

Coastal Science & Engineering

Johnson 2

Documents

Transcript of Johnson 2