Part C | 25.2
556 Part C Coastal Design
ciently slowly to be considered constant over about
1530 min.
In summary, storm winds in and of themselves pose
a wind load threat to the built environment at the coast,
for example critical infrastructure, such as roadways
and utilities, as well as residential and commercial
buildings. The above equations may be used to get
a general sense of wind strength as it depends on storm
meteorological parameters, but it is recommended that
numerical simulation and assimilation techniques be
employed for the rigorous assessment of winds and
wind forcing. Lastly, these storm winds induce large
storm waves and surges that are often the design condition of interest in coastal design, as discussed in the
following sections.
Example 25.1
At landfall near the Louisiana-Mississippi border, US,
Hurricane Katrina was observed to have a forward
speed and central pressure of V f D 7 m s
1 [25.76] and
p c D 920 mb [25.77]. Hurricane Katrina’s maximum
relative wind speed at landfall may be approximated
using (25.3) or Fig. 25.4, where we assume p far D
1013 mb (standard atmospheric pressure), B D 1:0 (typical value), and a D 1:23 kg m
3 . The relative maximum wind speed is then U max D 53 m s
1 . The actual
maximum wind speed is estimated by summing the
relative maximum speed and the tropical cyclone’s forward speed, giving U a-max D 60 m s
1 . Observed actual
maximum 15-min wind speed for Hurricane Katrina at
landfall was U a-max D 44 m s
1 [25.77]; thus, for this
storm, (25.3) provides a maximum wind speed estimate
that is about 35% larger than the observed value. This
example illustrates the errors that can be introduced
by using a simplified wind model close to the coastline, where the wind field is significantly altered by the
storm’s interaction with land.
25.2.2 Wind-Generated Waves
Large wind-generated waves often govern coastal engineering design. Understanding the magnitude and
frequency of large waves is essential for quantifying
impact loading on and overtopping of coastal structures
and for quantifying storm erosion. These waves develop
during far-field and near-field storm events. The reader
is referred to Chap. 4 for a discussion of nearshore
wave evolution and processes and Chap. 27 for a discussion of numerical modeling of coastal waves. While
a thorough analysis of the design wave climate involves
analysis of wave-field observations and computational
modeling (Chap. 27), in this section we discuss simple methods for identifying general storm wave climate
characteristics by considering tropical cyclone waves at
the coast.
Wind-wave generation is governed by the strength,
extent, and duration of the winds, as well as topographic conditions that limit energy transfer and growth
by reducing fetch distance and depth, respectively. The
empirical model developed by [25.78] from the interpretation of numerical simulations has been used
extensively [25.79, 80] for approximating a tropical cyclone’s maximum nonbreaking significant wave height
(H s-max )
gH s-max
U 2
a-max
D a
s
gX
U 2
a-max
;
(25.4)
where U a-max is taken at a 10-m elevation, a is an empirical fit coefficient, and X is an equivalent fetch distance.
The empirical coefficient is a D 0:0016, and is based on
the earlier work of Hasselmann et al. [25.81] on fetchlimited spectral wave growth. Taylor [25.82] found that
the formulation of Alves et al. [25.83] for X provides
less scatter and bias for nearshore wave estimation, with
respect to the original formulation of Young [25.78].
The Alves et al. [25.83] definition is
X D b
Ä
R max
Â
1 C d
V f
c g-max
ÃÃ m
;
(25.5)
where c g-max is the dominant wave’s group speed at the
location of interest (Part A, Chap. 4) and b, d, and m
are empirical fit coefficients. Alves et al. [25.83] found
b D 1:11, d D 2:3, and m D 0:38, based on numerical
simulations with WAVEWATCH III, where R max is in
meters and V f and c g-max are in m s
1 . In shallower
depths, depth-limited breaking should be considered
and the wave-height prediction by (25.4) and (25.5) reduced accordingly. Alves et al. [25.83] suggested the
following approximation for the peak wave period (T p )
T p D
0:123U a-max
g
:
(25.6)
Representative calculations using (25.4) through (25.6)
to estimate H s-max are presented in Fig. 25.5.
In summary, while it is recommended that computational simulations be used when possible to accurately
quantify wave design conditions, the above empirical
formulae provide a means for initially assessing extreme wave conditions at the coast.
Example 25.2
Continuing with the information provided in Example 25.1, where the 15-min maximum wind speed and
the radius to maximum wind for Hurricane Katrina at
556 Part C Coastal Design
ciently slowly to be considered constant over about
1530 min.
In summary, storm winds in and of themselves pose
a wind load threat to the built environment at the coast,
for example critical infrastructure, such as roadways
and utilities, as well as residential and commercial
buildings. The above equations may be used to get
a general sense of wind strength as it depends on storm
meteorological parameters, but it is recommended that
numerical simulation and assimilation techniques be
employed for the rigorous assessment of winds and
wind forcing. Lastly, these storm winds induce large
storm waves and surges that are often the design condition of interest in coastal design, as discussed in the
following sections.
Example 25.1
At landfall near the Louisiana-Mississippi border, US,
Hurricane Katrina was observed to have a forward
speed and central pressure of V f D 7 m s
1 [25.76] and
p c D 920 mb [25.77]. Hurricane Katrina’s maximum
relative wind speed at landfall may be approximated
using (25.3) or Fig. 25.4, where we assume p far D
1013 mb (standard atmospheric pressure), B D 1:0 (typical value), and a D 1:23 kg m
3 . The relative maximum wind speed is then U max D 53 m s
1 . The actual
maximum wind speed is estimated by summing the
relative maximum speed and the tropical cyclone’s forward speed, giving U a-max D 60 m s
1 . Observed actual
maximum 15-min wind speed for Hurricane Katrina at
landfall was U a-max D 44 m s
1 [25.77]; thus, for this
storm, (25.3) provides a maximum wind speed estimate
that is about 35% larger than the observed value. This
example illustrates the errors that can be introduced
by using a simplified wind model close to the coastline, where the wind field is significantly altered by the
storm’s interaction with land.
25.2.2 Wind-Generated Waves
Large wind-generated waves often govern coastal engineering design. Understanding the magnitude and
frequency of large waves is essential for quantifying
impact loading on and overtopping of coastal structures
and for quantifying storm erosion. These waves develop
during far-field and near-field storm events. The reader
is referred to Chap. 4 for a discussion of nearshore
wave evolution and processes and Chap. 27 for a discussion of numerical modeling of coastal waves. While
a thorough analysis of the design wave climate involves
analysis of wave-field observations and computational
modeling (Chap. 27), in this section we discuss simple methods for identifying general storm wave climate
characteristics by considering tropical cyclone waves at
the coast.
Wind-wave generation is governed by the strength,
extent, and duration of the winds, as well as topographic conditions that limit energy transfer and growth
by reducing fetch distance and depth, respectively. The
empirical model developed by [25.78] from the interpretation of numerical simulations has been used
extensively [25.79, 80] for approximating a tropical cyclone’s maximum nonbreaking significant wave height
(H s-max )
gH s-max
U 2
a-max
D a
s
gX
U 2
a-max
;
(25.4)
where U a-max is taken at a 10-m elevation, a is an empirical fit coefficient, and X is an equivalent fetch distance.
The empirical coefficient is a D 0:0016, and is based on
the earlier work of Hasselmann et al. [25.81] on fetchlimited spectral wave growth. Taylor [25.82] found that
the formulation of Alves et al. [25.83] for X provides
less scatter and bias for nearshore wave estimation, with
respect to the original formulation of Young [25.78].
The Alves et al. [25.83] definition is
X D b
Ä
R max
Â
1 C d
V f
c g-max
ÃÃ m
;
(25.5)
where c g-max is the dominant wave’s group speed at the
location of interest (Part A, Chap. 4) and b, d, and m
are empirical fit coefficients. Alves et al. [25.83] found
b D 1:11, d D 2:3, and m D 0:38, based on numerical
simulations with WAVEWATCH III, where R max is in
meters and V f and c g-max are in m s
1 . In shallower
depths, depth-limited breaking should be considered
and the wave-height prediction by (25.4) and (25.5) reduced accordingly. Alves et al. [25.83] suggested the
following approximation for the peak wave period (T p )
T p D
0:123U a-max
g
:
(25.6)
Representative calculations using (25.4) through (25.6)
to estimate H s-max are presented in Fig. 25.5.
In summary, while it is recommended that computational simulations be used when possible to accurately
quantify wave design conditions, the above empirical
formulae provide a means for initially assessing extreme wave conditions at the coast.
Example 25.2
Continuing with the information provided in Example 25.1, where the 15-min maximum wind speed and
the radius to maximum wind for Hurricane Katrina at