SURGE-DEPENDENT VEGETATION

EFFECTS ON HURRICANE-

GENERATED WAVES

Q. Jim Chen and Haihong Zhao

Department of Civil and Environmental Engineering

Louisiana State University

Baton Rouge, LA 70803

qchen@lsu.edu

[09-NGI-08] Understanding Coastal

Resiliency from Hurricane Impacts Using

Integrated Modeling and Observations

Participants:

Q. Jim Chen (LSU), Pat Fitzpatrick (MSU),

Robert Twilley (ULL), Jaye Cable (UNC),

Hendrick Tolman (NOAA/NCEP)

Haihong Zhao (LSU), Kelin Hu (LSU), Ranjit

Jadhav (LSU), Kim Marsh (LSU), Arun Chawla

(NOAA)

[09-NGI-08] Presentations (2011)

Directional Spectra of Hurricane Waves

in the Gulf of Mexico (Kelin Hu and Q.

Jim Chen) Poster

Wetland erosion issues near the

Caernarvon freshwater diversion (Pat

Fitzpatrick, Y. Lau, J. Chen, V. Anantharaj

and S. Shean)

Effects of Vegetation Properties on

Coastal Wetland Hydrodynamics in

Southern Louisiana [Student Poster]

(Kimberly Marsh)

[NG-CHC] Poster Presentations (2011)

Numerical Experiments on Ecosystem

Restoration and Flood Risks Reduction

in the Northern Gulf Coast – a need for

integrated cyberinfrastructure

(Hu et al. LSU)

Cyber-Enabled Coastal Data Factory for

the Northern Gulf (Jiang et al. LSU )

ADVANCED SURGE GUIDANCE

SYSTEM (ASGS) A Multi-State

Hurricane Forecast Effort for the NG

Region (Kaiser et al. LSU/ULL)

Outline

Study Area

Objectives

Field observations

Numerical modeling

Application to Hurricane Katrina

Conclusions

Study Area

Caernarvon Marsh

Biloxi Marsh

Chandeleur Island

Lake Pontchartrain

Objectives

Conduct field measurements of

vegetation and soil propoerties.

Couple a spectral wind-wave model with

a 3D circulation/surge model.

Incorporate energy (and momentum)

dissipation by salt marshes into the wave

and surge models.

Apply the coupled vegetation-wave-surge

models to Hurricanes Katrina and Gustav.

Vegetation Coverage (NLCD)

È

Legend

11

21

22

23

24

31

41

42

43

52

71

81

82

90

95

127

NLCD

Class #

NLCD Class Name

11 Open Water

21 Developed - Open Space

22 Developed – Low Intensity

23 Developed – Medium Intensity

24 Developed – Medium Intensity

31 Barren Land (Rock/Sand/Clay)

41 Deciduous Forest

42 Evergreen Forest

43 Mixed Forest

52 Shrub/Scrub

71 Grassland/Herbaceous

81 Pasture/Hay

82 Cultivated Crops

90 Woody Wetlands

95 Emergent Herbaceous Wetlands

In Louisiana GAP analysis project, #95 is classified as Brackish marsh with

Manning’s coefficient of 0.045 and at the seaward edge saline marsh is

distributed but not indicated in NLCD database.

Marshes

Marsh Properties Sampling Site Plant Density

(number/m2)

Stem Height

(m) / (Stem

Diameter

(mm))

Bending

Stiffness EI

(N m2)

Breton Sound

(August, 2009) 258 0.22/7.65 0.0272

Terrebonne Bay

(December, 2009) 285 0.52/5.87 0.0253

Terrebonne Bay Breton Sound

Dimensions of Marsh

Diameter (Bv)

Height of Stem (Hv)

Height of Plant (Hp)

Vegetation Heights before

and after Bending/Deflection

7.07 ”

5”

5”

45° Force (F)

hs Hv

Method: Vegetation Effects

Hydrodynamic Model

(Modified ECOM3D)

tv: shear stress due to vegetation HV: vegetation height N: stem density r : water density h: total water depth C1, C0: coefficients V*: shear velocity MEI: vegetation flexibility : depth-averaged velocity hs: vegetation wetted (defected) height

Flexible plants: Rigid plants:

Derived from Stone and Shen (2002) Kouwen and Li (1981)& Kouwen & Li (1980)

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

0.5

1

1.5

2

Friction F

acto

r

Submergence (h/Hv)

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

0.05

0.1

0.15

0.2

0.25

Submergence (h/Hv)

Mannin

g's

nVegetation induced friction

Dotted black: rigid plants Solid black: flexible plants (flexibility is considered) Solid blue: results from Manning’s n Hv=22cm; Bv=1cm; n=0.11

Bending Data Plants at a field site are sampled randomly and the following

parameters are collected:

◦ Total plant height

◦ Stem height

◦ Stem Diameter 5cm from the base

◦ Horizontal pull force needed to bend a plant 45°

Each data set consists of 15 plants

Data is analyzed to get plant stiffness and physical plant parameter ratios

y = 895775x1.3961 R² = 0.8408

1.00E+06

1.00E+07

1.00E+08

1.00E+09

1.00E+10

1.00E+11

0 100 200 300 400 500

Stif

fne

ss M

od

ulu

s E S

(N

/m²)

Stem Height/Stem Diameter

Plant Stiffness

BS 8-13-09

TB 12-22-09

MS Juntus 5-12-10

TB Dead 4-8-10

TB Live 4-8-10

Trendline

0 0.1 0.2 0.3 0.4 0.5 0.6 0.70

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Shera Velocity (V*)

Deflecte

d V

egeta

tion H

eig

ht

(hs)

Equation (2)

Equation (3)

Method: Vegetation Effect

---due to flexible plants

tv : Vegetation-induced shear stress r : Water density V*: Shear velocity : Depth-averaged velocity h : Total water depth

HV : Erect Vegetation height hs : Bended vegetation height MEI: Vegetation rigidity C1=3.08; C0=0.28 for prone configuration

---------------------------(1)

---------(2)

Kouwen & Li (1980)

------------(3)

Kouwen and Li (1981)

2*Vv rt

59.125.0

14.0

v

v

v

s

H

MEI

H

h t

0s

1*

Chhlog

C

V

V

V

=1.00m/s Hv =0.22m EI =0.0272Nm2

M =258

V

Numerical Modeling System

Wind Forcing

(H*Wind)

River Discharge

(USGS)

Wind Waves

(SWAN)

Suspended Sediment

Concentration

(SSC) and Morphology

SED

Hydrodynamic Model

(Modified ECOM3D)

Cohesive and

Non-cohesive

Sediments properties

Sediment Load

from River

Offshore

Boundary

Conditions

Implementation

Wind Waves

(Modified

SWAN)

Hydrodynamic Model

(Modified ECOM3D)

Water levels & currents

Wave heights, periods, & direction

Vegetation coverage

Shear stress at the

top of canopy

Deflected vegetation

height

•Extension of Dalrymple et al.’s (1984) vegetation effect to random waves

•Currently implemented in SWAN (v40.81)

•sm, km are used in SWAN (peak frequency and corresponding wave number

were introduced in Mendez & Losada (2004)

•Rayleigh distribution was assumed in the derivation (Mendez & Losada 2004)

Method: Vegetation Effect on Waves

<SV>: Vegetation-induced wave energy dissipation (m2/s) s: Wave radian frequency (Hz) k: Wave number (1/m) sr : Representative wave frequency kr: Representative wave number h: Total water depth; g: Gravity m0: zero moment of spectrum E(σ,θ) :wave energy density (m2/Hz)

a: a=1 for emergent a<1 for submerged case (hs/h <1) CD: Vegetation drag coefficient BV: Vegetation element diameter N: Number of stems per m2

h

heightn vegetatioEffective

33

33

sinh3sinh3sinh

21

rms

rr

rrr

VDv H

hkk

hkhk

g

NBCS

aas

ss ,,

0, E

m

SS

v

vds

T (dimensionless)

A (

dim

ensio

nle

ss)

Probability Density

P=1.0

1 2 30

1

2

3

1

2

3

4

0 1 2 30

0.5

1

A (dimensionless)

Pro

babili

ty D

ensity

=0.4

=0.0

T (dimensionless)

A (

dim

ensio

nle

ss)

Probability Density

P=1.0

1 2 30

1

2

3

1

2

3

4

0 1 2 30

0.5

1

A (dimensionless)

Pro

babili

ty D

ensity

=0.1

=0.0

Joint Distribution Based Approach (Chen and Zhao 2011)

s

sss

aa

s p

khk

hkhk

g

NBCmS VD

vds

23

2

33

330

,11

sinh3sinh3sinh

3)22(

23

211

2)(

ss

s

s

Lp

•Based on joint distribution function

(Longuet-Higgins, M. S., 1983).

•p(s) is frequency probability density

from Longuet-Higgins joint distribution

function

•Currently implemented in SWAN (by

H. Zhao)

Model Testing

0 2 4 6 8 10 12 14 16 18 20

0

0.2

0.4

0.6

0.8

Wate

r D

epth

(m

)

x (m)

0 2 4 6 8 10 12 14 16 18 200

0.05

0.1

0.15

0.2

0.25

Hm

o (

m)

x (m)

0 2 4 6 8 10 12 14 16 18 200

0.05

0.1

0.15

0.2

0.25

Hm

o (

m)

x (m)

0 2 4 6 8 10 12 14 16 18 200

0.04

0.08

0.12

0.16

Hm

o (

m)

x (m)

0 2 4 6 8 100

0.02

0.04

0.06

0.08

0.1

x(m)

Hrm

s(m

)

IR12WD44.dat

0 2 4 6 8 100

0.04

0.08

0.12

0.16

0.2

x(m)H

rms(m

)

IR8WD57.dat

0 2 4 6 8 100

0.04

0.08

0.12

0.16

x(m)

Hrm

s(m

)

IR5WD63.dat

0 2 4 6 8 100

0.04

0.08

0.12

0.16

x(m)

Hrm

s(m

)IR7WD68.dat

0 2 4 6 8 100

0.04

0.08

0.12

0.16

0.2

x(m)

Hrm

s(m

)

IR6WD75.dat

0 2 4 6 8 100

0.05

0.1

0.15

0.2

0.25

x(m)

Hrm

s(m

)

IR8WD104.dat

Measurement

Orig

HC

JDR

Dubi and Torum 1994

Data: Mendez and Losada 2004; Lovas 2000

Case Study: Hurricane Katrina

-100 -95 -90 -85 -80 -75

16

18

20

22

24

26

28

30

32

34

36

42001

42002

42003

42007

42019

42020

42036

42038

4203942040

42055

Longitude (degrees)

Latitu

de (

degre

es)

Hurricane Katrina 2005 coastline

track

tropical storm

hurricane

Impact of Hurricane Katrina Basin Mississippi

River Delta Breton Sound Pontchartrain Pearl River

Period Class Mi2 Km2 Mi2 Km2 Mi2 Km2 Mi2 Km2

Fall

2004

~

Fall

2006

Net Land Area Change -18 -46.62 -41 -106.19 -19 -49.21 -4 -10.36

Flooded Burned Marsh 0 0.00 0 0.00 0 0.00 0 0.00

Flooded Ag/Pasture Impoundment 0 0.00 0 0.00 0 0.00 0 0.00

Adjusted Net Land Area Change -18 -46.62 -41 -106.19 -19 -49.21 -4 -10.36

Land Area Change in Coastal Louisiana After the 2005 Hurricanes: Overview (Barras, 2006)

Model Setup

35581 Water

points

Cell size along the

Chandeleur Island is ~150m(dx) by ~260m(dy) Cell size in the marsh area is 200m~300m

Boundary conditions are provided by ADCIRC

Modeled Maximum Surge Height

-90.5 -90 -89.5 -89 -88.5 -88

29

29.2

29.4

29.6

29.8

30

30.2

30.4

30.6

30.8

31

Longitude (degrees)

La

titu

de

(d

eg

ree

s)

Maximum Surge

Surface Elevation (m)

0 2 4 6

Comparison with Measured HWM

0 5 10 150

5

10

15

Measured (m, NAVD)

Modele

d (

m,

NA

VD

)

r2=0.874, RMSE=0.79

Effects of Rigid Plants

Without Vegetation Rigid Plants

-91.0 -90.5 -90.0 -89.5 -89.0 -88.5 -88.0

29.0

29.5

30.0

30.5

31.0

Longitude (degrees)

La

titu

de

(d

eg

ree

s)

(Hs, veg

-Hs, nonveg

)/Hs, nonveg

100

Relative Difference(%)-100 -80 -60 -40 -20 0 20 40

Differences in Waves

Conclusions

Surge-dependent effects of vegetation on surge and waves have been developed and implemented into the models.

The coupled models produced promising results, including vegetation-induced flow resistance, vegetation damage, and wave attenuation under field conditions.

Joint-distribution-based wave energy dissipation formula produces rational results especially in the case of broad-banded random waves.

Ongoing and Future Work

The coupled vegetation-surge-wave

models are being further tested against

lab/field data.

Future simulations will be focused on

Wax Lake Delta with different type of

landscape and vegetation.