SURGE-DEPENDENT VEGETATION EFFECT ON HURRICANE-GENERATED WAVES
Transcript of SURGE-DEPENDENT VEGETATION EFFECT ON HURRICANE-GENERATED WAVES
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
[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.