Earthquake-Generated Landslides and Tsunamis

Jonas Eliasson

### Abstract

Large earthquakes generate tsunamis, but when it also triggers a landslide, the tsunami may become enormous. Slide scars on the continental shelf of the North Atlantic Ocean show this. For estimating the tsunami, a translatory wave theory has been suggested. Slide data are used to estimate the amplitude of the displacement wave. The amplitudes are used to obtain wave heights at a reference point outside the breaker zone. Energy transmission formulas are used to find the wave height transfer coefficients from the source area to a reference point. Tsunami risk from several sources at a reference point is quantified using stochastic processes, and estimations of a hazard curve for the probability of landslide occurrence are carried out. The sensitivity of the hazard curve to uncertainties in determining the wave height from the individual sources turns can be evaluated. In two case studies, the Tohoku tsunami and earthquake in 2011 in Japan is found to be caused by a coseismic slip and a landslide in combination, and a hazard curve for a reference point south of Iceland is found for tsunamis in the North Atlantic Ocean.

Keywords: earthquake, tsunami, landslide, hazard

#### 1. Introduction

The main difficulty in tsunami hazard assessment is to estimate the generation of wave energy at the source. In many cases, this is simply solved by running a CFD model and estimating the ocean surface amplitude at the source [1] from it. This estimate of the amplitudes involves many problems and can be very uncertain, when the measured amplitudes are small, but a better method is still to be found.

Sometimes it is better to estimate the initial wave itself, and when that is done, the energy transmission from the source to the point of impact can be quite accurately modeled in CFD models [2–4], if the shallow water wave equations are in the numerically stable domain.

Strong earthquakes cause large deformations of the surface of the earth, so tsunamis are more often than not strengthened by landslides triggered by the earthquake. Often the triggering earthquake does not contribute any significant amount of energy to the tsunami wave, and this seems to be the general case in the North Atlantic, where few dangerous tsunamis are reported.

There have also been speculations in the scientific community about the danger of tsunamis in the North Atlantic from gigantic glacial flood waves of volcanic origin, (jökulhlaups), emerging on the south coast of Iceland. In this case, there is a well-defined probability of occurrence [5] and clear geological evidence of the

volcanic events [6] but practically no historical evidence of tsunamis. For the landslide tsunamis, we introduce a translatory wave model to estimate the initial disturbance [7]. Block slide models are popular for this purpose [8]; in them the blocks must reach very high velocities to create a serious tsunami. The translatory wave model assumes that sliding blocks break up and become debris flows when the velocity is high enough.

When the wave crest of the tsunami approaches a beach, instability of the wave fronts, wave breaking, and reflection set in. There may be little reflection on a flat beach but large energy dissipation due to wave breaking.

Few authors discuss how this problem is to be handled in practical hazard assessment, and most often this is simply done by making all coasts completely reflecting. This is on the safe side in run-up estimation. But how the correct boundary conditions should be formulated in terms of reflection and energy dissipation in the various models reported is an open question.

The following treatment on tsunamis has the emphasis on the estimation of initial disturbance and energy formation in the tsunami. The underlying theories are formulated in [8, 9] and the case studies in Chapter 7. The theory of CFD modeling of a tsunami and the associated procedures of preparing tsunami warnings are left out, as they can be found in various internet resources of the government institutions that make them.

How the final inundation height is affected is unclear. Energy is lost in the jump as the bore moves inland, but with water behind has not, so it keeps moving. Then there is the role of the bathymetry; it has an influence on the dispersion and reflection of the

In short, the mathematics and numerical schemes are well developed in tsunami modeling, but there are pitfalls that can be difficult to avoid. Even models that have been through a scrutineer's process of calibration and validation can fail. Still, the initial conditions in the source area are the biggest uncertainty. It has therefore been concluded that verification and validation are necessary for each case, even for

There are several numerical methods available to treat such waves using, for example, the well-known St. Venant's equations, see [11], to take an example. But the names used here, St. Venant's equations and translatory waves, are usually not mentioned. Analytical solutions are possible for stationary flows using a wave progressing with constant velocity down an inclined plane, or in a funnel, as the translatory wave in [7]. In there it is also demonstrated that numerical solutions of the St. Venant's equations can produce exactly this kind of flow without presuming

However, when a wave runs upwards a mild slope with constant celerity c, as a translatory wave, c will inevitably reach the shallow water wave celerity, c = √gD (g acceleration of gravity and D the water depth) somewhere, and then the surface profile may become unstable, which can result in a breaking wave (bore) or a series of braking waves if the wave is very long. Figure 2 shows a nearshore breakup of this kind. The successive waves, resulting from the breakup, ride upon each other making the ultimate tsunami run-up very difficult to predict, even when the deepwater wave is well known. This difficulty is discussed further in Sections 5 and 7.

It sounds like a misconception, but in deep waters outside the continental shelfs,

tsunamis propagate as shallow water waves. The mathematics of shallow water

wave fronts that is sometimes significant and sometimes not.

Nearshore breakup of a tsunami wave in Phi Phi Island 2004.

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

models that have been through this process before [10].

a constant velocity wave.

Figure 2.

3. Propagation of tsunami waves

3.1 Deep water

205

## 2. Properties of a tsunami wave

Tsunamis are ocean waves that are considerably different from the best known types of ocean waves, storm waves, and ocean tides. There is much less periodicity in tsunamis, and they can run over dry land in a more or less unpredictable way. On dry land, large tsunami waves have a devastating power that resembles flood waves of the type "translatory waves" [6], such waves knock down most everything in their way. Out in the oceans (deep water), it is normally like a long wave and can be modeled using the shallow water wave theory. In this, it resembles the tidal wave.

However, there are several snags in the numerical modeling of tsunamis. Ordinary storm waves create steep wave crests that break in the shore line, but tsunamis are more like a bore, or a moving hydraulic jump; Figure 1 illustrates this difference.

Figure 1. Difference between storm waves (a) and tsunamis (b) [9].

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

#### Figure 2.

volcanic events [6] but practically no historical evidence of tsunamis. For the landslide tsunamis, we introduce a translatory wave model to estimate the initial disturbance [7]. Block slide models are popular for this purpose [8]; in them the blocks must reach very high velocities to create a serious tsunami. The translatory wave model assumes that sliding blocks break up and become debris flows when the

beach but large energy dissipation due to wave breaking.

Earthquakes - Impact, Community Vulnerability and Resilience

the various models reported is an open question.

ment institutions that make them.

2. Properties of a tsunami wave

Figure 1.

204

Difference between storm waves (a) and tsunamis (b) [9].

When the wave crest of the tsunami approaches a beach, instability of the wave fronts, wave breaking, and reflection set in. There may be little reflection on a flat

Few authors discuss how this problem is to be handled in practical hazard assessment, and most often this is simply done by making all coasts completely reflecting. This is on the safe side in run-up estimation. But how the correct boundary conditions should be formulated in terms of reflection and energy dissipation in

The following treatment on tsunamis has the emphasis on the estimation of initial disturbance and energy formation in the tsunami. The underlying theories are formulated in [8, 9] and the case studies in Chapter 7. The theory of CFD modeling of a tsunami and the associated procedures of preparing tsunami warnings are left out, as they can be found in various internet resources of the govern-

Tsunamis are ocean waves that are considerably different from the best known types of ocean waves, storm waves, and ocean tides. There is much less periodicity in tsunamis, and they can run over dry land in a more or less unpredictable way. On dry land, large tsunami waves have a devastating power that resembles flood waves of the type "translatory waves" [6], such waves knock down most everything in their way. Out in the oceans (deep water), it is normally like a long wave and can be modeled using the shallow water wave theory. In this, it resembles the tidal wave. However, there are several snags in the numerical modeling of tsunamis. Ordinary storm waves create steep wave crests that break in the shore line, but tsunamis are more like a bore, or a moving hydraulic jump; Figure 1 illustrates this difference.

velocity is high enough.

Nearshore breakup of a tsunami wave in Phi Phi Island 2004.

How the final inundation height is affected is unclear. Energy is lost in the jump as the bore moves inland, but with water behind has not, so it keeps moving. Then there is the role of the bathymetry; it has an influence on the dispersion and reflection of the wave fronts that is sometimes significant and sometimes not.

In short, the mathematics and numerical schemes are well developed in tsunami modeling, but there are pitfalls that can be difficult to avoid. Even models that have been through a scrutineer's process of calibration and validation can fail. Still, the initial conditions in the source area are the biggest uncertainty. It has therefore been concluded that verification and validation are necessary for each case, even for models that have been through this process before [10].

There are several numerical methods available to treat such waves using, for example, the well-known St. Venant's equations, see [11], to take an example. But the names used here, St. Venant's equations and translatory waves, are usually not mentioned. Analytical solutions are possible for stationary flows using a wave progressing with constant velocity down an inclined plane, or in a funnel, as the translatory wave in [7]. In there it is also demonstrated that numerical solutions of the St. Venant's equations can produce exactly this kind of flow without presuming a constant velocity wave.

However, when a wave runs upwards a mild slope with constant celerity c, as a translatory wave, c will inevitably reach the shallow water wave celerity, c = √gD (g acceleration of gravity and D the water depth) somewhere, and then the surface profile may become unstable, which can result in a breaking wave (bore) or a series of braking waves if the wave is very long. Figure 2 shows a nearshore breakup of this kind. The successive waves, resulting from the breakup, ride upon each other making the ultimate tsunami run-up very difficult to predict, even when the deepwater wave is well known. This difficulty is discussed further in Sections 5 and 7.

#### 3. Propagation of tsunami waves

#### 3.1 Deep water

It sounds like a misconception, but in deep waters outside the continental shelfs, tsunamis propagate as shallow water waves. The mathematics of shallow water

waves has been investigated by many; the analytical description is well known from [12] and similar works. The equations are a system of partial differential equations of the hyperbolic type, and the solution propagates along the characteristics.

manmade landscape; and are very difficult to model. The run-up wave height must be estimated for each place individually. Several mathematical solutions exist for the shoaling process, both analytical and numerical from CFD. The analytical methods mostly utilize conservation of momentum or transported energy, but they are for two-dimensional waves only. Run-up heights and attenuation are very difficult to control in numerical calculation, because of difficulties in modeling the breaking of water waves, influence of obstacles on the beach, and the amount of

In finding some expressions for shoaling and run-up of two-dimensional waves,

two kinds of waves will be considered: Firstly, a displacement wave, which is translatory in nature. Secondly, an oscillatory wave is considered; it has different properties than the displacement wave. When we have big tsunamis, it will be the displacement wave that hits the nearby coasts but may become an oscillatory wave

A bore, H meters high above still water level, will be formed as the water particles cannot overtake the wave front. A bore that inundates the land travels ashore as a breaking wave. Bore is formed when the water velocity u = c. According to first-order wave theory, this leads to H = D (D is the breaking depth of the wave), but from higher-order theories and practical experience, H = 0.7 D is closer to the true value for long waves breaking on a beach. If the beach slope is only slight (e.g., river estuaries), traditional long wave mild slope equations in [13] are valid. We will have an inundation, or run-up, to a level of R = H above still water level. If the slope is steep, full or partial reflection sets in, but for steep and mild slopes, R will

> H2 ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi <sup>g</sup>ðH=0:<sup>7</sup> � � <sup>p</sup> <sup>2</sup> ð Þ <sup>H</sup>=0:<sup>7</sup> <sup>2</sup>

The shoaling process is assumed to be near linear for tsunami waves of a very small steepness. Linear theory for shoaling means keeping the energy flux constant

<sup>H</sup> <sup>¼</sup> <sup>a</sup> <sup>¼</sup> <sup>0</sup>:7 D

H � �<sup>1</sup>=<sup>5</sup>

The amplification factor due to shoaling of the radial wave is denoted as a. Hb(r) is the breaker height of the incoming radial wave. For waves of around 1 m coming in from the deep regions of the ocean, it can become a = 2–5. For waves of a few centimeters, it can become a = 5–10. When Hb(r) is found, the run-up will be the same as in the case of the displacement wave, 1.0–1.35 times the breaking

This investigation shows that the run-up process depends very heavily on the far field wave height. But if a reference point is selected in water that is deep enough to exclude the effect of breaking on the wave height estimation, then we will have a quasi-linear transfer process from the source area to the reference point. This means that a fixed coefficient, independent of source area wave height, can be used as a

2g <sup>¼</sup> <sup>1</sup>:35H (1)

(2)

energy dissipated in this process [13].

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

R ¼ H þ

until the point of breaking. Then we find:

u2 2g <sup>¼</sup> <sup>H</sup> <sup>þ</sup>

Hb ð Þr

farther away from the source.

3.2.1 Displacement wave

not exceed:

wave height.

207

3.2.2 Oscillatory wave

Tsunamis originate in a source area, unlike the tidal wave that propagates in the same manner in deep water but originates from a gravity potential created by the moon and the sun (astronomical tide). In a point, well away from the source area, a tsunami wave front propagates along the line drawn from the source area through the point with the phase velocity c = √gD, called the wave orthogonal. The actual water velocity is much lower than c. How much lower depends on the wave amplitude H in the point and the usual shallow water formulae for local energy, E = ⅛ρgH2 , and transported energy, Etr = E c, applied for a wave train, if there is one.

The full set of the partial differential equation system for tsunami propagation is nonlinear and includes terms for Coriolis forces and shear stress at the bottom and wind stress at the surface of the ocean. However out on deep water, the shear stress terms are not dominating so the equation system is only weakly nonlinear. This means that the nonlinear interaction with the local astronomical tide will be small, so its amplitude and velocity can be added without damaging errors, while the wave stays in deep water. This is not the case in shallow water.

The wave celerity c of a tsunami is the velocity of propagation of both the surface disturbance and the transported energy. This velocity is very high when the water depth is counted in kilometers, comparable to the travel speed of a passenger jet. This has a great impact on the danger of the tsunami. The tsunami attack comes swiftly, few hours after the onset of the wave from the source area.

Prediction of tsunamis is very important in disaster prevention, and a large warning system is maintained all over the world, see, for example, https://www. tsunami.gov/. A simulation model that solves the partial differential system numerically is the heart of every warning system. The model usually simulates the real wave quite well in deep water, so the estimate for the arriving time of the attacking wave may be quite accurate even when the amplitude of it is less accurately predicted. Waves that originate from the continental shelf and run over deep water regions to their place of attack are a special problem. They usually start out as displacement waves, i.e., waves without characteristic periodicity, but change to an oscillatory wave train in deep water, and the periodicity of the wave train may be difficult to model.

Numerical simulations of tsunami waves are an invaluable part of the tsunami warning system, but the uncertainty about initial wave heights and total wave energy generation is a problem.

#### 3.2 Shallow water

Shortly after the tsunami wave hits the continental shelf, it reaches shallow water where the processes of wave refraction and diffraction take over the propagation. The wave becomes highly nonlinear as these processes, called the shoaling, set in. The wave fronts turn toward the coast, so the angle of attack is different from the deep-water direction. An example of wave fronts curved by shoaling may be seen in Figure 2.

When the wave hits the shoreline, the shoaling process is finished and is followed by the run-up. Approaching the coast from a reference point, the tsunami wave runs into a new near-field process of breaking and run-up of the tsunami wave and inundation of the land. In the run-up, large tsunami waves travel ashore as spilling breakers; this is a nonlinear process. The methods to predict such processes are extremely complex; depend on the incoming wave height and natural and

#### Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

manmade landscape; and are very difficult to model. The run-up wave height must be estimated for each place individually. Several mathematical solutions exist for the shoaling process, both analytical and numerical from CFD. The analytical methods mostly utilize conservation of momentum or transported energy, but they are for two-dimensional waves only. Run-up heights and attenuation are very difficult to control in numerical calculation, because of difficulties in modeling the breaking of water waves, influence of obstacles on the beach, and the amount of energy dissipated in this process [13].

In finding some expressions for shoaling and run-up of two-dimensional waves, two kinds of waves will be considered: Firstly, a displacement wave, which is translatory in nature. Secondly, an oscillatory wave is considered; it has different properties than the displacement wave. When we have big tsunamis, it will be the displacement wave that hits the nearby coasts but may become an oscillatory wave farther away from the source.

#### 3.2.1 Displacement wave

waves has been investigated by many; the analytical description is well known from [12] and similar works. The equations are a system of partial differential equations of the hyperbolic type, and the solution propagates along the characteristics.

Tsunamis originate in a source area, unlike the tidal wave that propagates in the same manner in deep water but originates from a gravity potential created by the moon and the sun (astronomical tide). In a point, well away from the source area, a tsunami wave front propagates along the line drawn from the source area through the point with the phase velocity c = √gD, called the wave orthogonal. The actual water velocity is much lower than c. How much lower depends on the wave amplitude H in the point and the usual shallow water formulae for local energy,

, and transported energy, Etr = E c, applied for a wave train, if there

The full set of the partial differential equation system for tsunami propagation is nonlinear and includes terms for Coriolis forces and shear stress at the bottom and wind stress at the surface of the ocean. However out on deep water, the shear stress terms are not dominating so the equation system is only weakly nonlinear. This means that the nonlinear interaction with the local astronomical tide will be small, so its amplitude and velocity can be added without damaging errors, while the wave

The wave celerity c of a tsunami is the velocity of propagation of both the surface disturbance and the transported energy. This velocity is very high when the water depth is counted in kilometers, comparable to the travel speed of a passenger jet. This has a great impact on the danger of the tsunami. The tsunami attack comes

Prediction of tsunamis is very important in disaster prevention, and a large warning system is maintained all over the world, see, for example, https://www. tsunami.gov/. A simulation model that solves the partial differential system numerically is the heart of every warning system. The model usually simulates the real wave quite well in deep water, so the estimate for the arriving time of the attacking

predicted. Waves that originate from the continental shelf and run over deep water regions to their place of attack are a special problem. They usually start out as displacement waves, i.e., waves without characteristic periodicity, but change to an oscillatory wave train in deep water, and the periodicity of the wave train may be

Numerical simulations of tsunami waves are an invaluable part of the tsunami warning system, but the uncertainty about initial wave heights and total wave

Shortly after the tsunami wave hits the continental shelf, it reaches shallow water where the processes of wave refraction and diffraction take over the propagation. The wave becomes highly nonlinear as these processes, called the shoaling, set in. The wave fronts turn toward the coast, so the angle of attack is different from the deep-water direction. An example of wave fronts curved by shoaling may be

When the wave hits the shoreline, the shoaling process is finished and is followed by the run-up. Approaching the coast from a reference point, the tsunami wave runs into a new near-field process of breaking and run-up of the tsunami wave and inundation of the land. In the run-up, large tsunami waves travel ashore as spilling breakers; this is a nonlinear process. The methods to predict such processes are extremely complex; depend on the incoming wave height and natural and

wave may be quite accurate even when the amplitude of it is less accurately

stays in deep water. This is not the case in shallow water.

Earthquakes - Impact, Community Vulnerability and Resilience

swiftly, few hours after the onset of the wave from the source area.

E = ⅛ρgH2

difficult to model.

3.2 Shallow water

seen in Figure 2.

206

energy generation is a problem.

is one.

A bore, H meters high above still water level, will be formed as the water particles cannot overtake the wave front. A bore that inundates the land travels ashore as a breaking wave. Bore is formed when the water velocity u = c. According to first-order wave theory, this leads to H = D (D is the breaking depth of the wave), but from higher-order theories and practical experience, H = 0.7 D is closer to the true value for long waves breaking on a beach. If the beach slope is only slight (e.g., river estuaries), traditional long wave mild slope equations in [13] are valid. We will have an inundation, or run-up, to a level of R = H above still water level. If the slope is steep, full or partial reflection sets in, but for steep and mild slopes, R will not exceed:

$$\text{IR} = \text{H} + \frac{\text{u}^2}{2\text{g}} = \text{H} + \frac{\text{H}^2 \left(\sqrt{\text{g}(\text{H}/\text{0.7})}\right)^2}{\left(\text{H}/\text{0.7}\right)^2 2\text{g}} \quad = \text{1.35H} \tag{1}$$

#### 3.2.2 Oscillatory wave

The shoaling process is assumed to be near linear for tsunami waves of a very small steepness. Linear theory for shoaling means keeping the energy flux constant until the point of breaking. Then we find:

$$\frac{\mathbf{H}\_{\rm b}(\mathbf{r})}{\mathbf{H}} = \mathbf{a} = \left(\frac{\mathbf{0}.7\mathbf{D}}{\mathbf{H}}\right)^{1/5} \tag{2}$$

The amplification factor due to shoaling of the radial wave is denoted as a. Hb(r) is the breaker height of the incoming radial wave. For waves of around 1 m coming in from the deep regions of the ocean, it can become a = 2–5. For waves of a few centimeters, it can become a = 5–10. When Hb(r) is found, the run-up will be the same as in the case of the displacement wave, 1.0–1.35 times the breaking wave height.

This investigation shows that the run-up process depends very heavily on the far field wave height. But if a reference point is selected in water that is deep enough to exclude the effect of breaking on the wave height estimation, then we will have a quasi-linear transfer process from the source area to the reference point. This means that a fixed coefficient, independent of source area wave height, can be used as a

wave height transfer coefficient from the source area to the reference point. This method is utilized in Chapter 6.

B: The width of the submarine landslide V: Velocity of the front y0: The frontal height of the landslide Lh: The length under water xv: Distance from the shoreline to c = V xw: Distance to slide front Cm: Average wave celerity in xw � xv Lhb = Ls + (xw � xv)Cm/V Ls: Effective length of a submerged slide ρ: Density of water

For further discussion and estimation of slide dimensions, see Section 7 and

In this case the surface disturbance, or the water wave, cannot run away from the translatory wave, i.e., the submarine landslide that causes it because c < V. The water volume above the still water level will therefore simply be equal to the displacing volume, of the submerged part of the slide. The estimates for the energy of the initial wave are for the two sub-cases: Case 1a, a slide that originates from

The displaced water volume will be equal to the total submerged volume of the slide. The slide will hit the water with a great splash and run on the bottom until it stops. The water will be lifted the distance y0 from the bottom, and this will be the resulting height of the water wave when the slide suddenly stops. In that situation,

2

B Lh (3)

B Ls (4)

/g, and the

EW1a ¼ ½y0ρ gy0B Lh ¼ ½ρgy0

The wave progresses in the x direction with the shallow water velocity c. In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area where h = y0 in an area of size B Lh.

Now the slide will leave a scar, or a hole Ls long, in the seabed of volume LsB y0. An equal part of the slide will be outside the scar and leave a heap at the slide front.

In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area where h = �y0 in the hole area of size

<sup>2</sup> <sup>¼</sup> <sup>ρ</sup>gy0

2

land, and Case 1b, a slide that originates at the sea bottom.

The hole and the heap have the same volume. We will find.

EW1b ¼ ½ y0ρg LsB y0

In this case, the slide passes the point where V = c, or the depth D = V2

water wave will run away from the front of the translatory slide wave. When the slide front stops, the water wave front will be at a distance Lha = xv + (xw � xv)Cm/V

the energy added to the water will be.

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

B Ls and h = +y0 in the heap area.

[6, 9, 15].

5.1 Case 1

5.1.1 Case 1a

5.1.2 Case 1b

5.2 Case 2

209

## 4. Causes of tsunamis

Large earthquakes usually start a tsunami. The earthquake deforms the bottom landscape and creates a surface disturbance in the source area and the associated transfer of energy to the water mass. This energy is transmitted from the source area by the tsunami wave.

An earthquake of magnitude 7 or larger on the Richter scale usually starts a tsunami. However, this is a rule of thumb only; smaller earthquakes can trigger a tsunami by starting a submarine landslide on bottom slopes. If it does, the magnitude of the tsunami depends on the size of the landslide, so the tsunami can be enormous even though the earthquake is small. Some years ago, it was discovered that huge submarine landslides on the continental shelf of the North Atlantic Ocean have caused large tsunamis. In Table 7.1 in [14], 11 submarine landslides with slide volumes 20–20,000 km<sup>3</sup> are listed. Submarine landslides of that magnitude run as translatory waves. The deadliest tsunami attacks in the recent years have struck Indonesia and the Indian Ocean coasts; the most recent one is the Anak Krakatau volcano, where a submarine landslide of type Case 1a (see Section 5.1) caused a tsunami December 22, 2018.

If a landslide is triggered or not, it can be stated that a movement on the sea bottom creates a surface disturbance with a certain potential energy, deduced by the common methods of wave mechanics. Some kinetic energy will also be created in the boundary layer around the moving object; this is mechanical energy and can thus be converted in wave energy in the tsunami wave. But as a rule, the kinetic energy will be converted to turbulent energy that cannot be converted into wave energy and is dissipated. Thus, the total potential energy of a mass that flows from land and into the sea is not converted into wave energy; only the potential energy of the initial disturbance it causes on the sea surface contributes to the tsunami.

#### 5. Initial disturbance and the tsunami wave energy

In estimating the mechanical wave energy generated in the source area of a tsunami, three types must be considered and separate estimates devised for each one. The different types are landslides down mountain slopes and in the water where V > c (Case 1). Totally submerged submarine landslides where V < c at least in for a part of the slide (Case 2) and bottom landscape features are moving vertically and horizontally (Case 3). The initial tsunami wave height is estimated. The energy transmitted to the water by the movement of the landslide is estimated from the moving mass. The total wave energy is estimated as the potential energy in the water mass the slide displaces from the still water surface, using the assumption that turbulent energy transmitted to the water cannot be regenerated as mechanical energy in the tsunami wave.

The wave energy transmission away from the source area can be translatory or by a solitary group of oscillatory waves. The wave transmission can be estimated in numerical models, and the shoaling also until either the point of breaking or where the numerical stability is lost in the model. In the following we will therefore estimate the wave energy generation in the source area and the corresponding wave amplitudes. In the following, the expressions for the wave energy and amplitude h depend on the variables listed here.

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807


For further discussion and estimation of slide dimensions, see Section 7 and [6, 9, 15].

#### 5.1 Case 1

wave height transfer coefficient from the source area to the reference point. This

Large earthquakes usually start a tsunami. The earthquake deforms the bottom landscape and creates a surface disturbance in the source area and the associated transfer of energy to the water mass. This energy is transmitted from the source

An earthquake of magnitude 7 or larger on the Richter scale usually starts a tsunami. However, this is a rule of thumb only; smaller earthquakes can trigger a tsunami by starting a submarine landslide on bottom slopes. If it does, the magnitude of the tsunami depends on the size of the landslide, so the tsunami can be enormous even though the earthquake is small. Some years ago, it was discovered that huge submarine landslides on the continental shelf of the North Atlantic Ocean have caused large tsunamis. In Table 7.1 in [14], 11 submarine landslides with slide volumes 20–20,000 km<sup>3</sup> are listed. Submarine landslides of that magnitude run as translatory waves. The deadliest tsunami attacks in the recent years have struck Indonesia and the Indian Ocean coasts; the most recent one is the Anak Krakatau volcano, where a submarine landslide of type Case 1a (see Section 5.1) caused a

If a landslide is triggered or not, it can be stated that a movement on the sea bottom creates a surface disturbance with a certain potential energy, deduced by the common methods of wave mechanics. Some kinetic energy will also be created in the boundary layer around the moving object; this is mechanical energy and can thus be converted in wave energy in the tsunami wave. But as a rule, the kinetic energy will be converted to turbulent energy that cannot be converted into wave energy and is dissipated. Thus, the total potential energy of a mass that flows from land and into the sea is not converted into wave energy; only the potential energy of the initial disturbance it causes on the sea surface contributes to the tsunami.

In estimating the mechanical wave energy generated in the source area of a tsunami, three types must be considered and separate estimates devised for each one. The different types are landslides down mountain slopes and in the water where V > c (Case 1). Totally submerged submarine landslides where V < c at least

The wave energy transmission away from the source area can be translatory or by a solitary group of oscillatory waves. The wave transmission can be estimated in numerical models, and the shoaling also until either the point of breaking or where the numerical stability is lost in the model. In the following we will therefore estimate the wave energy generation in the source area and the corresponding wave amplitudes. In the following, the expressions for the wave energy and amplitude h

in for a part of the slide (Case 2) and bottom landscape features are moving vertically and horizontally (Case 3). The initial tsunami wave height is estimated. The energy transmitted to the water by the movement of the landslide is estimated from the moving mass. The total wave energy is estimated as the potential energy in the water mass the slide displaces from the still water surface, using the assumption that turbulent energy transmitted to the water cannot be regenerated as mechanical

5. Initial disturbance and the tsunami wave energy

method is utilized in Chapter 6.

Earthquakes - Impact, Community Vulnerability and Resilience

4. Causes of tsunamis

area by the tsunami wave.

tsunami December 22, 2018.

energy in the tsunami wave.

depend on the variables listed here.

208

In this case the surface disturbance, or the water wave, cannot run away from the translatory wave, i.e., the submarine landslide that causes it because c < V. The water volume above the still water level will therefore simply be equal to the displacing volume, of the submerged part of the slide. The estimates for the energy of the initial wave are for the two sub-cases: Case 1a, a slide that originates from land, and Case 1b, a slide that originates at the sea bottom.

#### 5.1.1 Case 1a

The displaced water volume will be equal to the total submerged volume of the slide. The slide will hit the water with a great splash and run on the bottom until it stops. The water will be lifted the distance y0 from the bottom, and this will be the resulting height of the water wave when the slide suddenly stops. In that situation, the energy added to the water will be.

$$\mathbf{E\_{W1a}} = \mathbb{W}\mathbf{y}\_0 \boldsymbol{\rho} \text{ } \mathbf{g} \mathbf{y}\_0 \mathbf{B} \text{ } \mathbf{L\_h} = \mathbb{W}\mathbf{z} \mathbf{g} \mathbf{y}\_0 \text{ } ^2 \mathbf{B} \text{ } \mathbf{L\_h} \tag{3}$$

The wave progresses in the x direction with the shallow water velocity c. In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area where h = y0 in an area of size B Lh.

#### 5.1.2 Case 1b

Now the slide will leave a scar, or a hole Ls long, in the seabed of volume LsB y0. An equal part of the slide will be outside the scar and leave a heap at the slide front. The hole and the heap have the same volume. We will find.

$$\mathbf{E\_{W1b}} = \mathbb{W}\_2 \mathbf{y}\_0 \text{pg } \mathbf{L\_sB} \mathbf{y}\_0^{\ 2} = \rho \mathbf{g} \mathbf{y}\_0^{\ 2} \mathbf{B} \, \mathbf{L\_s} \tag{4}$$

In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area where h = �y0 in the hole area of size B Ls and h = +y0 in the heap area.

#### 5.2 Case 2

In this case, the slide passes the point where V = c, or the depth D = V2 /g, and the water wave will run away from the front of the translatory slide wave. When the slide front stops, the water wave front will be at a distance Lha = xv + (xw � xv)Cm/V away from the shoreline. In estimating the energy, we still have to distinguish between the two schemes (a) and (b) as before.

#### 5.2.1 Case 2a

In a point xv from the shoreline, we have c = V, the velocity of the slide, but the slide stops at the position xw from the shoreline. With Cm denoting the average shallow water wave velocity in xw � xv, we will have Lha = xv + (xw � xv)Cm/V for the distance from the shoreline to the water wave front. Now we have a wave height slightly less than before.

$$\mathbf{h\_{2a}} = \mathbf{y\_0}\mathbf{x\_w}/\mathbf{L\_{ha}}\tag{5}$$

translatory wave may be transformed into a group of oscillatory waves; the details

of the slide can be estimated, the water wave height can easily be found.

of the same configuration as the bottom disturbance is the only chance.

6. Studies of individual tsunamis and regional risk assessment

Similarly, it is not quite clear what will happen in the case when the slide starts at a depth where c > V. In this case, the distance xv is not defined, but if the run time

A movement of the ocean bottom by an earthquake usually happens fast. The movement will leave an uplift of the ocean surface where the bottom is lifted and a sink where the bottom sinks down. Both the lift and the sink contribute to the

There are two possibilities to model this: Firstly, to find the Fourier transform of the surface disturbance and, secondly, to use linear wave theory to radiate it away from the source. Analytic models can be used for this if the boundary configuration can be coped with. Otherwise, a numerical model with an initial surface disturbance

The earthquake event and the devastation caused by this tsunami is very well documented; it is the most famous tsunami event of recent years. It took place off the Pacific coast of Tohoku, Japan, on Friday, March 11, 2011 at 05:46 UTC. It was caused by a Mw 9.0 (magnitude moment) undersea megathrust earthquake with the epicenter approximately 70 km east of the Oshika Peninsula of Tohoku with the hypocenter in approximately 30 km deep water (see Figure 3 gray arrow).

From the data obtained in the exploratory drilling at the site shown in Figure 3, it was concluded in [16] that the tsunami was caused by the mass movement shown

The details of the bottom deformation are estimated and pictured in Figure 3b in [18]. This picture resembles a 150 km long slide scar with Ls and B about 110 km and y0 about 8 m using the symbols in Chapter 5.2. This would be a Case 2b slide, stopping 25–75 km from the trench, see Figure 4; here the average bottom slope is about 4/50 or 8–9%. It is interesting to note that layers of fine sediments on such a slope can easily liquify, slide down the slope, and cause a bottom deformation like the one pictured in [18] and indicated by black arrows in Figure 4. No evidence has been found in [16] to support this suggested slide event, but the information on the bottom deformation given in [18] is considered reliable, and it is supported by a coseismic slip model in Figure 4 in [17]. The suggested slide would have characteristics that can be calculated using the equations for the Case 2b slide. If the slide is due to liquefaction, the movement will start at the onset of the strong motion and stop when it stops. According to graphs in [18], this time is about 30 seconds; this is

V = 2 m/s corresponds to the 9% slope and y0 = 8 m. Together with the time 30 s, this gives a horizontal flow path of 60 m. This corresponds well to Figure 4, giving

The water depth gives c = 250 m/s so we get Lbh = 250 30 = 7500 m = 7.5 km

an information additional to what we have in Sections 5.2.2 and 5.2.3.

for the initial disturbance. As the flow path is short the κ 0. Now we get.

56 m as maximum horizontal deformation.

Lbh = Ls + 7.5 = 110 + 7.5 = 117.5 km.

of that wave group are unclear.

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

potential energy of the disturbance.

6.1 Tohoku tsunami in Japan

in Figure 4.

211

5.3 Case 3

The energy of the water wave becomes

$$\mathbf{E\_{W2a}} = \% \,\mathrm{h\_{2a}}^2 \text{\(\,\mathrm{gB}\,\,\mathrm{L\_{ha}}\,\tag{6}\)}$$

In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area; we will have h = h2a in a square of size B Lha.

#### 5.2.2 Case 2b

Assuming the slide will start where c < V, we now have Lhb = Ls + (xw � xv) Cm/V. The slide will leave a scar in the seabed of size LsB. A part of the slide, κ Ls(κ< 1) long, will be outside the scar and leave a hole in the scar of area of volume κy0LsB. At = 0 there will be a through in the water table approximately corresponding to this volume, but in the front of the slide, we have an initial wave Lhb long and h2b high with the same volume as the through. Then we have.

$$\mathbf{E\_{W2a}} = \mathbb{W} \mathbf{(y\_0}^2 \,\mathrm{\kappa L\_s} + \mathrm{h\_{2b}}^2 \,\mathrm{L\_{hb}}) \diamond \mathbf{gB} \tag{7}$$

In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area; we will have a through y0 deep and a wave h2b high at time t = 0.

### 5.2.3 Sudden increase in depth

In both Case 1 and Case 2, the slide is very likely to be in shallow water. A sudden increase in depth is therefore possible as soon as the tsunami wave sets out from the source area. A translatory wave with the velocity V, in a place where the wave celerity is c1, will in theory continue to flow until the bottom slope I0 is zero, but in practice it will stop sooner. The water wave will therefore run into deeper water with higher wave velocity c2, and that affects the wave height. When the slope where the slide is running downhill fades out to a flat bottom, there is no problem in the numerical model, but in the rare occasions when there is a sudden increase in the ocean depth just in front of that point, it may provide better results to find the height h2 of the initial wave in the deeper water:

$$\mathbf{h\_2 = h\_1(c\_1/c\_2)^{1/2}} = \mathbf{h\_1(D\_1/D\_2)}^{1/4} \tag{8}$$

Here index 1 refers to the shallower source area and 2 to deeper water. The energy flow Eq. (8) assumes the translatory wave motion to be preserved. The

#### Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

translatory wave may be transformed into a group of oscillatory waves; the details of that wave group are unclear.

Similarly, it is not quite clear what will happen in the case when the slide starts at a depth where c > V. In this case, the distance xv is not defined, but if the run time of the slide can be estimated, the water wave height can easily be found.

#### 5.3 Case 3

away from the shoreline. In estimating the energy, we still have to distinguish

EW2a ¼ ½ h2a

EW2a ¼ ½ y0

to find the height h2 of the initial wave in the deeper water:

h2 ¼ h1ð Þ c1=c2

In a point xv from the shoreline, we have c = V, the velocity of the slide, but the slide stops at the position xw from the shoreline. With Cm denoting the average shallow water wave velocity in xw � xv, we will have Lha = xv + (xw � xv)Cm/V for the distance from the shoreline to the water wave front. Now we have a wave height

2

In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area; we will have h = h2a in a square of

Assuming the slide will start where c < V, we now have Lhb = Ls + (xw � xv) Cm/V. The slide will leave a scar in the seabed of size LsB. A part of the slide, κ Ls(κ< 1) long, will be outside the scar and leave a hole in the scar of area of volume κy0LsB. At = 0 there will be a through in the water table approximately corresponding to this volume, but in the front of the slide, we have an initial wave Lhb long and h2b high with the same volume as the through. Then we have.

<sup>2</sup> <sup>κ</sup>Ls <sup>þ</sup> h2b

In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area; we will have a through y0 deep and a

In both Case 1 and Case 2, the slide is very likely to be in shallow water. A sudden increase in depth is therefore possible as soon as the tsunami wave sets out from the source area. A translatory wave with the velocity V, in a place where the wave celerity is c1, will in theory continue to flow until the bottom slope I0 is zero, but in practice it will stop sooner. The water wave will therefore run into deeper water with higher wave velocity c2, and that affects the wave height. When the slope where the slide is running downhill fades out to a flat bottom, there is no problem in the numerical model, but in the rare occasions when there is a sudden increase in the ocean depth just in front of that point, it may provide better results

Here index 1 refers to the shallower source area and 2 to deeper water. The energy flow Eq. (8) assumes the translatory wave motion to be preserved. The

<sup>1</sup>=<sup>2</sup> <sup>¼</sup> h1ð Þ D1=D2

<sup>1</sup>=<sup>4</sup> (8)

<sup>2</sup> Lhb

ρ gB (7)

h2a ¼ y0xw=Lha (5)

ρ gB Lha (6)

between the two schemes (a) and (b) as before.

Earthquakes - Impact, Community Vulnerability and Resilience

The energy of the water wave becomes

5.2.1 Case 2a

size B Lha.

5.2.2 Case 2b

wave h2b high at time t = 0.

5.2.3 Sudden increase in depth

210

slightly less than before.

A movement of the ocean bottom by an earthquake usually happens fast. The movement will leave an uplift of the ocean surface where the bottom is lifted and a sink where the bottom sinks down. Both the lift and the sink contribute to the potential energy of the disturbance.

There are two possibilities to model this: Firstly, to find the Fourier transform of the surface disturbance and, secondly, to use linear wave theory to radiate it away from the source. Analytic models can be used for this if the boundary configuration can be coped with. Otherwise, a numerical model with an initial surface disturbance of the same configuration as the bottom disturbance is the only chance.

#### 6. Studies of individual tsunamis and regional risk assessment

#### 6.1 Tohoku tsunami in Japan

The earthquake event and the devastation caused by this tsunami is very well documented; it is the most famous tsunami event of recent years. It took place off the Pacific coast of Tohoku, Japan, on Friday, March 11, 2011 at 05:46 UTC. It was caused by a Mw 9.0 (magnitude moment) undersea megathrust earthquake with the epicenter approximately 70 km east of the Oshika Peninsula of Tohoku with the hypocenter in approximately 30 km deep water (see Figure 3 gray arrow).

From the data obtained in the exploratory drilling at the site shown in Figure 3, it was concluded in [16] that the tsunami was caused by the mass movement shown in Figure 4.

The details of the bottom deformation are estimated and pictured in Figure 3b in [18]. This picture resembles a 150 km long slide scar with Ls and B about 110 km and y0 about 8 m using the symbols in Chapter 5.2. This would be a Case 2b slide, stopping 25–75 km from the trench, see Figure 4; here the average bottom slope is about 4/50 or 8–9%. It is interesting to note that layers of fine sediments on such a slope can easily liquify, slide down the slope, and cause a bottom deformation like the one pictured in [18] and indicated by black arrows in Figure 4. No evidence has been found in [16] to support this suggested slide event, but the information on the bottom deformation given in [18] is considered reliable, and it is supported by a coseismic slip model in Figure 4 in [17]. The suggested slide would have characteristics that can be calculated using the equations for the Case 2b slide. If the slide is due to liquefaction, the movement will start at the onset of the strong motion and stop when it stops. According to graphs in [18], this time is about 30 seconds; this is an information additional to what we have in Sections 5.2.2 and 5.2.3.

V = 2 m/s corresponds to the 9% slope and y0 = 8 m. Together with the time 30 s, this gives a horizontal flow path of 60 m. This corresponds well to Figure 4, giving 56 m as maximum horizontal deformation.

The water depth gives c = 250 m/s so we get Lbh = 250 30 = 7500 m = 7.5 km for the initial disturbance. As the flow path is short the κ 0. Now we get.

Lbh = Ls + 7.5 = 110 + 7.5 = 117.5 km.

Figure 3.

Location chart of the tsunami site with the epicenter (red star) and an exploration well, drilled at site C00 19, [16].

The uplift caused by the coseismic movement means that there will be just a small hole in the scar area. The volume of the heap caused by the slide will be.

WT2b = By0Ls = 1 <sup>110000</sup> <sup>8</sup> 110000 = 9.68 <sup>10</sup><sup>10</sup> m3 = 96.8 km<sup>3</sup> .

The height of the wave with same volume as in Section 5.2:

h2b = WT2b/(Lhb B) = 8 110/117.5 = 7.5 m.

Eq. (7) must be modified due to the uplift and the small scar hole; this is done by putting κ 0 as before, and then we have for the energy in the source area:

EW2a = ½h2b <sup>2</sup> Lhb<sup>ρ</sup> g B = ½ 7.5<sup>2</sup> <sup>117500</sup> <sup>1025</sup> 9.81 110000 = 3.6 10<sup>15</sup> Nm. difficult; there is considerable uncertainty in estimating the height (y0) of possible

There are many tsunami sources in the Atlantic Ocean, but in the northern regions, the tsunami risk is less than in many other places, and the source of the main threat may be unknown, both location and magnitude. A good method is presented in [9], to estimate the hazard curves for a reference point in south Iceland. This involves estimating initial wave heights at the source and their frequencies. Then the transfer functions must be applied, and the hazard curves are

To assess the risk, we have to estimate event return periods for the various event magnitudes and the correlation structure of the event history. This correlation may be between time length between events and event magnitude and autocorrelation

6.2 Tsunami risks in the North Atlantic Ocean

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

The 2011 Tohoku earthquake: Coseismic slip distribution model, from [17].

found by numerical integration.

(positive or negative) in the time history.

6.2.1 Risk assessment methods

landslides.

213

Figure 4.

This result can be checked against the simulation results published by NOAA [19]; it is on Figure 5 and shows the spread of the tsunami very well. Comparing this with a ring wave spreading in an effective 90° conical channel gives a resulting average wave height 2–3 feet 900 km from the source. According to C = 250 m/s (800 km/h), this should occur after little more than 1 hour. This checks well against Figure 5.

The bottom deformations that caused the very strong Tohoku tsunami in the Pacific Ocean, simulated numerically by the Japanese and USA scientists, [17, 19], can be explained by a submarine landslide. This suggests that the coseismic slip of the earthquake triggers a sliding of the surface sediments. In combination they cause the bottom deformation. Finally, it can thus be concluded that the coseismic slip and the landslide are both responsible for the Tohoku tsunami in March 2011, not the coseismic slip alone.

This shows that in assessing the tsunami risk in the Pacific coastal regions of Japan, the landslide risk must be considered. This fact may result in that considerably larger events than the Tohoku tsunami are possible if a larger slide than this 8 m thick slide is released. This landslide is not very high compared to what has happened elsewhere. The assessment of this possibility of larger slides can be

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

Figure 4.

The uplift caused by the coseismic movement means that there will be just a small hole in the scar area. The volume of the heap caused by the slide will be. WT2b = By0Ls = 1 <sup>110000</sup> <sup>8</sup> 110000 = 9.68 <sup>10</sup><sup>10</sup> m3 = 96.8 km<sup>3</sup>

Location chart of the tsunami site with the epicenter (red star) and an exploration well, drilled at site

Eq. (7) must be modified due to the uplift and the small scar hole; this is done by

This result can be checked against the simulation results published by NOAA [19]; it is on Figure 5 and shows the spread of the tsunami very well. Comparing this with a ring wave spreading in an effective 90° conical channel gives a resulting average wave height 2–3 feet 900 km from the source. According to C = 250 m/s (800 km/h), this should occur after little more than 1 hour. This checks well against

The bottom deformations that caused the very strong Tohoku tsunami in the Pacific Ocean, simulated numerically by the Japanese and USA scientists, [17, 19], can be explained by a submarine landslide. This suggests that the coseismic slip of the earthquake triggers a sliding of the surface sediments. In combination they cause the bottom deformation. Finally, it can thus be concluded that the coseismic slip and the landslide are both responsible for the Tohoku tsunami in March 2011,

This shows that in assessing the tsunami risk in the Pacific coastal regions of Japan, the landslide risk must be considered. This fact may result in that considerably larger events than the Tohoku tsunami are possible if a larger slide than this 8 m thick slide is released. This landslide is not very high compared to what has happened elsewhere. The assessment of this possibility of larger slides can be

<sup>2</sup> Lhb<sup>ρ</sup> g B = ½ 7.5<sup>2</sup> <sup>117500</sup> <sup>1025</sup> 9.81 110000 = 3.6 10<sup>15</sup> Nm.

putting κ 0 as before, and then we have for the energy in the source area:

The height of the wave with same volume as in Section 5.2:

h2b = WT2b/(Lhb B) = 8 110/117.5 = 7.5 m.

Earthquakes - Impact, Community Vulnerability and Resilience

EW2a = ½h2b

not the coseismic slip alone.

Figure 5.

212

Figure 3.

C00 19, [16].

.

The 2011 Tohoku earthquake: Coseismic slip distribution model, from [17].

difficult; there is considerable uncertainty in estimating the height (y0) of possible landslides.

#### 6.2 Tsunami risks in the North Atlantic Ocean

There are many tsunami sources in the Atlantic Ocean, but in the northern regions, the tsunami risk is less than in many other places, and the source of the main threat may be unknown, both location and magnitude. A good method is presented in [9], to estimate the hazard curves for a reference point in south Iceland. This involves estimating initial wave heights at the source and their frequencies. Then the transfer functions must be applied, and the hazard curves are found by numerical integration.

#### 6.2.1 Risk assessment methods

To assess the risk, we have to estimate event return periods for the various event magnitudes and the correlation structure of the event history. This correlation may be between time length between events and event magnitude and autocorrelation (positive or negative) in the time history.

#### Figure 5.

Spreading of the Tohoku tsunami in the Pacific Ocean March 11, 2011. (NOAA Center for tsunami research, Pacific marine environmental laboratory; NOAA. 2011. Printed in the N.Y. Times).

The very long records necessary for a complete picture of the event statistics are normally not available. Certain assumptions are necessary, but we must estimate the basic statistics such as average time between events, ta, the standard deviation associated to it, ts and the correlation between magnitude and event interval ρ (note the different meaning of ρ in chapter 5). Now the following formula can be derived for the interval between tectonic events, it being earthquakes, submarine slides, or volcanic events:

$$\mathbf{g\_k(i)} = \rho \,\mathbf{h\_k(i)} + \sqrt{(1-\rho^2)}\mathbf{e\_k(i)}\tag{9}$$

empirically. These are various hazard curves and event probabilities for fixed periods to come, e.g., economical lifetime of structures and so on. It must be noted that the probability of a specified event of a given class happening in the next year

There are several methods to estimate the distribution functions we have to use as building blocks in Eq. (9) recommended in the literature. The log-normal distri-

When there is more than one source, the procedure has to be repeated for all significant sources. Then the transfer functions have to be applied and Ha and Hs calculated for the chosen reference point. Hs is much more difficult to estimate from observations than Ha, but sometimes it is possible to estimate the coefficient of variation Cv = Ha/Hs. If not it has to be included as a parameter in order to estimate

In [9], all this is done for a reference point south of Iceland. There are eight possible sources for tsunamis in the North Atlantic, six of these are found significant for the reference point chosen. For clarification the reference point is shown

The only significant Icelandic source contributing to the calculated tsunami height in the reference point on Figure 6 is the Katla volcano [6]. The hazard curves for these points are in Figure 7. Here all the risk curves follow the Gumbel distribution P(H > x) = exp(exp(y)) where y = 3.91 + 1.12 x rather closely. Here the probability P does not denote the next event, but the maximum to be expected in the next year (annual maximum); it will be x = (y 3.91)/1.11 in each point in

Icelandic coastal waters, depth scale by deeper blue for each 200 m. Population centers in red [9].

is not a constant. This probability will increase with time.

bution is often usable for gk, especially when ρ is low [5].

the accuracy of calculated probabilities and risks.

6.2.2 Example from South Iceland

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

and the resulting risk curve.

Figure 7.

Figure 6.

215


The time between the tectonic events i and i + 1 is known when gk(i) is known so series for the occurrence of events in time can be simulated when hk(i) is known. If the simulation period is a limited number of years into the future, it is necessary to simulate sufficiently many series (the number k) so the statistical distribution of H is represented.

If this statistical distribution is not known, some classification that fits available observations of H has to be assumed. Three classes, small, medium, and large events, should be considered as minimum. Then the Monte Carlo method is used to simulate the k series, and they are used to determine the statistics of interest

empirically. These are various hazard curves and event probabilities for fixed periods to come, e.g., economical lifetime of structures and so on. It must be noted that the probability of a specified event of a given class happening in the next year is not a constant. This probability will increase with time.

## 6.2.2 Example from South Iceland

There are several methods to estimate the distribution functions we have to use as building blocks in Eq. (9) recommended in the literature. The log-normal distribution is often usable for gk, especially when ρ is low [5].

When there is more than one source, the procedure has to be repeated for all significant sources. Then the transfer functions have to be applied and Ha and Hs calculated for the chosen reference point. Hs is much more difficult to estimate from observations than Ha, but sometimes it is possible to estimate the coefficient of variation Cv = Ha/Hs. If not it has to be included as a parameter in order to estimate the accuracy of calculated probabilities and risks.

In [9], all this is done for a reference point south of Iceland. There are eight possible sources for tsunamis in the North Atlantic, six of these are found significant for the reference point chosen. For clarification the reference point is shown and the resulting risk curve.

The only significant Icelandic source contributing to the calculated tsunami height in the reference point on Figure 6 is the Katla volcano [6]. The hazard curves for these points are in Figure 7. Here all the risk curves follow the Gumbel distribution P(H > x) = exp(exp(y)) where y = 3.91 + 1.12 x rather closely. Here the probability P does not denote the next event, but the maximum to be expected in the next year (annual maximum); it will be x = (y 3.91)/1.11 in each point in Figure 7.

Figure 6. Icelandic coastal waters, depth scale by deeper blue for each 200 m. Population centers in red [9].

The very long records necessary for a complete picture of the event statistics are normally not available. Certain assumptions are necessary, but we must estimate the basic statistics such as average time between events, ta, the standard deviation associated to it, ts and the correlation between magnitude and event interval ρ (note the different meaning of ρ in chapter 5). Now the following formula can be derived for the interval between tectonic events, it being earthquakes, submarine slides, or

Spreading of the Tohoku tsunami in the Pacific Ocean March 11, 2011. (NOAA Center for tsunami research,

Pacific marine environmental laboratory; NOAA. 2011. Printed in the N.Y. Times).

Earthquakes - Impact, Community Vulnerability and Resilience

i Number of event occurring at time t(i) gk(i) = ((t(i + 1) � t(i) � ta)/ts Dimensionless relative time between events hk(i) = ρ(Hk(i) � Ha)/Hs Relative magnitude, e.g., wave height

ek(i) Random function ek(0.1)

k Series number

ρ = E{gk(i)hk(i)} Magnitude time correlation (E denotes average)

The time between the tectonic events i and i + 1 is known when gk(i) is known so series for the occurrence of events in time can be simulated when hk(i) is known. If the simulation period is a limited number of years into the future, it is necessary to simulate sufficiently many series (the number k) so the statistical distribution of H

If this statistical distribution is not known, some classification that fits available

observations of H has to be assumed. Three classes, small, medium, and large events, should be considered as minimum. Then the Monte Carlo method is used to simulate the k series, and they are used to determine the statistics of interest

gkðÞ¼ <sup>i</sup> <sup>ρ</sup> hkðÞþ<sup>i</sup> <sup>√</sup> <sup>1</sup> � <sup>ρ</sup><sup>2</sup> ekð Þ<sup>i</sup> (9)

volcanic events:

Figure 5.

is represented.

214

standard deviation will always be difficult to estimate; usually there are not enough

In the example taken in Section 6.2, there are eight identified tsunami sources in the North Atlantic Ocean, six of these contribute significantly to the hazard curve in the danger zone on Figure 7. This is the zone above 2 m, meaning that the tsunami has to be 2 m or higher to pose any significant threat alone, i.e., without being accompanied by a flood of different origin [9] or attacking upon a spring

The effect of the coefficient of variation on the hazard curve Figure 7 is quiet surprising. The estimation of its value is very difficult. However, to leave it out corresponds to estimating its value to be zero, and that is totally unsatisfactory. In Figure 7 the effect of three different values, common in geophysical data, is demonstrated, and the difference is quite striking. The difference in frequency of

The translatory wave theory is used to estimate the expressions for energy and wave height in the source area, and it can be used for the initial conditions in wave

Earthquakes, of too small a magnitude to produce dangerous tsunamis them-

approximation for the transfer functions that link the wave heights in the source area to wave heights in a reference point selected in the wave propagation path. The best position for such a point is offshore, outside the zone of nonlinear shoaling and wave breaking, but near the places where the attack of the tsunami is expected. Then a hazard assessment may produce a wave height-frequency curve for this

It is clearly demonstrated that it is very important to include the C<sup>v</sup> factor for the event magnitude in the hazard assessment. Otherwise the tsunami wave heights for

For high Cv values the hazard curves may be expected to follow the Gumbel distribution or possibly another distribution of the extreme value distribution family because the hazard curve is the maximum expected frequency for a given wave

Part of the theories herein is developed for the Básendaflóð (The Flood at Basendar Iceland in 1799) research directed by Sigurður Sigurðarson, Section Engineer, Icelandic Road and Coastal Administration, and in cooperation with Gísli Viggósson Consulting Engineer, Reykjavík Iceland. This project was supported financially by the Research Fund of the Icelandic Road and Coastal Administration who also sponsored this publication. Their support is greatly

The authors acknowledge Japan Agency for Marine-Earth Science and Technology and the NOAA Center for Tsunami Research, Pacific Marine Environmental

observations of serious tsunami events to establish a reliable value for this

occurrence is of one decade, up or down, from the Cv = 1/2 value.

Approximate analytical methods can give good results as a first

selves, can do so by triggering submarine landslides.

a given frequency may be seriously underestimated.

Laboratory, for the use of material referred by them.

coefficient.

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

tide flood.

8. Conclusion

models.

point.

height.

Acknowledgements

acknowledged.

217

Figure 7. Hazard curves for the reference point with three different C<sup>v</sup> values. The abscissa is the Gumbel variate [9].

The probability is for the maximum to be expected in the next year (annual maximum). To take an example, the maximum to be expected in the very next year with probability P = 1% or 0.01 has the Gumbel variate 0.4, corresponding to a wave height of x = 0.1 m which is rather insignificant, but for P = 0.1%, the Gumbel variate is 2.8 giving seven times larger wave height.

#### 7. Discussions

Tsunami attack is very difficult to predict, even though the models that simulate the propagation of the tsunami wave over deep water are very good and in most cases reliable. The mathematics of these models is very difficult, but effective, as long as the wave stays in deep water [20]. The difficulty in modeling is to predict the shoaling and the run-up. And then there is the uncertainty about the initial wave height and wave energy formation in the source area.

The importance in such analysis is to identify the sources that cause the largest tsunami threats. The methods devised in Chapter 5 can be used to estimate the initial wave and energy in the source area when the bottom deformation is known. This is demonstrated in the case study of the Tohoku tsunami, in Section 6.1; in [21] is a detailed description of this huge event and its consequences.

The cause of the bottom deformation is directly or indirectly an earthquake. It can start a submarine landslide, or the earthquake wave itself can deform the bottom so much that a large tsunami is produced, especially earthquakes above 7 in magnitude. But this very information tells us that the variability in tsunami properties will be very great in the source area. The magnitude of the average event may be possible to estimate from existing observations and geophysical data, but their

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

standard deviation will always be difficult to estimate; usually there are not enough observations of serious tsunami events to establish a reliable value for this coefficient.

In the example taken in Section 6.2, there are eight identified tsunami sources in the North Atlantic Ocean, six of these contribute significantly to the hazard curve in the danger zone on Figure 7. This is the zone above 2 m, meaning that the tsunami has to be 2 m or higher to pose any significant threat alone, i.e., without being accompanied by a flood of different origin [9] or attacking upon a spring tide flood.

The effect of the coefficient of variation on the hazard curve Figure 7 is quiet surprising. The estimation of its value is very difficult. However, to leave it out corresponds to estimating its value to be zero, and that is totally unsatisfactory. In Figure 7 the effect of three different values, common in geophysical data, is demonstrated, and the difference is quite striking. The difference in frequency of occurrence is of one decade, up or down, from the Cv = 1/2 value.

## 8. Conclusion

The probability is for the maximum to be expected in the next year (annual maximum). To take an example, the maximum to be expected in the very next year with probability P = 1% or 0.01 has the Gumbel variate 0.4, corresponding to a wave height of x = 0.1 m which is rather insignificant, but for P = 0.1%, the Gumbel

Hazard curves for the reference point with three different C<sup>v</sup> values. The abscissa is the Gumbel variate [9].

Tsunami attack is very difficult to predict, even though the models that simulate the propagation of the tsunami wave over deep water are very good and in most cases reliable. The mathematics of these models is very difficult, but effective, as long as the wave stays in deep water [20]. The difficulty in modeling is to predict the shoaling and the run-up. And then there is the uncertainty about the initial wave

The importance in such analysis is to identify the sources that cause the largest tsunami threats. The methods devised in Chapter 5 can be used to estimate the initial wave and energy in the source area when the bottom deformation is known. This is demonstrated in the case study of the Tohoku tsunami, in Section 6.1; in [21]

The cause of the bottom deformation is directly or indirectly an earthquake. It

can start a submarine landslide, or the earthquake wave itself can deform the bottom so much that a large tsunami is produced, especially earthquakes above 7 in magnitude. But this very information tells us that the variability in tsunami properties will be very great in the source area. The magnitude of the average event may be possible to estimate from existing observations and geophysical data, but their

variate is 2.8 giving seven times larger wave height.

Earthquakes - Impact, Community Vulnerability and Resilience

height and wave energy formation in the source area.

is a detailed description of this huge event and its consequences.

7. Discussions

216

Figure 7.

The translatory wave theory is used to estimate the expressions for energy and wave height in the source area, and it can be used for the initial conditions in wave models.

Earthquakes, of too small a magnitude to produce dangerous tsunamis themselves, can do so by triggering submarine landslides.

Approximate analytical methods can give good results as a first approximation for the transfer functions that link the wave heights in the source area to wave heights in a reference point selected in the wave propagation path. The best position for such a point is offshore, outside the zone of nonlinear shoaling and wave breaking, but near the places where the attack of the tsunami is expected. Then a hazard assessment may produce a wave height-frequency curve for this point.

It is clearly demonstrated that it is very important to include the C<sup>v</sup> factor for the event magnitude in the hazard assessment. Otherwise the tsunami wave heights for a given frequency may be seriously underestimated.

For high Cv values the hazard curves may be expected to follow the Gumbel distribution or possibly another distribution of the extreme value distribution family because the hazard curve is the maximum expected frequency for a given wave height.

### Acknowledgements

Part of the theories herein is developed for the Básendaflóð (The Flood at Basendar Iceland in 1799) research directed by Sigurður Sigurðarson, Section Engineer, Icelandic Road and Coastal Administration, and in cooperation with Gísli Viggósson Consulting Engineer, Reykjavík Iceland. This project was supported financially by the Research Fund of the Icelandic Road and Coastal Administration who also sponsored this publication. Their support is greatly acknowledged.

The authors acknowledge Japan Agency for Marine-Earth Science and Technology and the NOAA Center for Tsunami Research, Pacific Marine Environmental Laboratory, for the use of material referred by them.

## Conflict of interest

The author declares that there are no conflict of interests regarding the publication of this chapter.

References

Division; 2005

153(3):F6-F10

10(2):179-200

1999;61(1–2):121-137

2003

[1] Benfield Hazard Research Centre. Tsunami Hazards in the Atlantic Ocean. London, England: The Centre;

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

> [10] Synolakis CE, Bernard EN, Titov VV, Kânoğlu U, Gonzalez FI. Validation and verification of tsunami numerical models. In: Tsunami Science Four Years after the 2004 Indian Ocean Tsunami. Basel: Birkhäuser; 2008. pp. 2197-2228

[11] Julien PY. River Mechanics. New York, United States of America: Cambridge University Press; 2002

[12] Stoker JJ. Water Waves. NY: Interscience Publishers; 1957

[13] Svendsen IA. Introduction to Nearshore Hydrodynamics. Singapore:

[14] Bryant E. Tsunami—the Underrated Hazard. 3rd ed. Springer International Publishing; 2014. DOI: 10.1007/978-3-

[15] Rupakhety R, Ólafsson S, editors. Earthquake Engineering and Structural Dynamics in Memory of Ragnar

Sigbjörnsson: Selected Topics. Chapter 8.

[16] JAMSTEC. Causal Mechanisms of

Earthquake of 2011. Revealed through Hydraulic Analysis of Fault Drilling Samples from the Deep–Sea Scientific Drilling Vessel Chikyu; Japan Agency

Large Slip during the Tohoku

for Marine-Earth Science and Technology. 2013. Available from: http://www.jamstec.go.jp/e/about/

[17] Land and Sea Areas of Crustal Movement and Slip Distribution Model

Earthquake: Coseismic Slip Distribution Model. Report by the Geographical Survey Institute, Japan. 2011. Available from: http://www.gsi.go.jp/cais/topic

of the Tohoku-Pacific Ocean

[18] Fujii Y, Satake K, Sakai SI, Shinohara M, Kanazawa T. Tsunami

110520-index-e.html

press\_release/20131008/

World Scientific; 2006

319-06133-7

Springer; 2017

[2] Kerridge D. The Threat Posed by Tsunami to the UK. London, UK: Department for Environment, Food and Rural Affairs, Flood Management

[3] Ward SN, Asphaug E. Asteroid impact tsunami of 2880 March 16. Geophysical Journal International. 2003;

[4] Tinti S, Bortolucci E, Armigliato A. Numerical simulation of the landslideinduced tsunami of 1988 on Vulcano Island, Italy. Bulletin of Volcanology.

[5] Eliasson J, Larsen G, Gudmundsson MT, Sigmundsson F. Probabilistic model for eruptions and associated flood events in the Katla caldera, Iceland. Computational Geosciences. 2006;

[6] Elíasson J. A glacial burst tsunami near Vestmannaeyjar, Iceland. Journal of Coastal Research. 2008;241:13-20. https://doi.org/10.2112/05-0568.1

[7] Elíasson J, Kjaran SP, Holm SL, Gudmundsson MT, Larsen G. Large hazardous floods as translatory waves. Environmental Modelling & Software.

[8] Tinti S, Bortolucci E, Vannini C. A block-based theoretical model suited to gravitational sliding. Natural Hazards.

[9] Eliasson J, Sigbjörnsson R. Assessing

the risk of landslide-generated Tsunamis, using translatory wave theory. International Journal of Earthquake Engineering and Hazard

Mitigation. 2013;1(1):61-71

2007;22(10):1392-1399

1997;16(1):1-28

219

## Author details

Jonas Eliasson Earthquake Engineering Research Centre, School of Engineering and Natural Sciences, University of Iceland, Iceland

\*Address all correspondence to: jonaseliassonhi@gmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Earthquake-Generated Landslides and Tsunamis DOI: http://dx.doi.org/10.5772/intechopen.84807

## References

Conflict of interest

Earthquakes - Impact, Community Vulnerability and Resilience

tion of this chapter.

Author details

Sciences, University of Iceland, Iceland

provided the original work is properly cited.

Jonas Eliasson

218

The author declares that there are no conflict of interests regarding the publica-

Earthquake Engineering Research Centre, School of Engineering and Natural

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

\*Address all correspondence to: jonaseliassonhi@gmail.com

[1] Benfield Hazard Research Centre. Tsunami Hazards in the Atlantic Ocean. London, England: The Centre; 2003

[2] Kerridge D. The Threat Posed by Tsunami to the UK. London, UK: Department for Environment, Food and Rural Affairs, Flood Management Division; 2005

[3] Ward SN, Asphaug E. Asteroid impact tsunami of 2880 March 16. Geophysical Journal International. 2003; 153(3):F6-F10

[4] Tinti S, Bortolucci E, Armigliato A. Numerical simulation of the landslideinduced tsunami of 1988 on Vulcano Island, Italy. Bulletin of Volcanology. 1999;61(1–2):121-137

[5] Eliasson J, Larsen G, Gudmundsson MT, Sigmundsson F. Probabilistic model for eruptions and associated flood events in the Katla caldera, Iceland. Computational Geosciences. 2006; 10(2):179-200

[6] Elíasson J. A glacial burst tsunami near Vestmannaeyjar, Iceland. Journal of Coastal Research. 2008;241:13-20. https://doi.org/10.2112/05-0568.1

[7] Elíasson J, Kjaran SP, Holm SL, Gudmundsson MT, Larsen G. Large hazardous floods as translatory waves. Environmental Modelling & Software. 2007;22(10):1392-1399

[8] Tinti S, Bortolucci E, Vannini C. A block-based theoretical model suited to gravitational sliding. Natural Hazards. 1997;16(1):1-28

[9] Eliasson J, Sigbjörnsson R. Assessing the risk of landslide-generated Tsunamis, using translatory wave theory. International Journal of Earthquake Engineering and Hazard Mitigation. 2013;1(1):61-71

[10] Synolakis CE, Bernard EN, Titov VV, Kânoğlu U, Gonzalez FI. Validation and verification of tsunami numerical models. In: Tsunami Science Four Years after the 2004 Indian Ocean Tsunami. Basel: Birkhäuser; 2008. pp. 2197-2228

[11] Julien PY. River Mechanics. New York, United States of America: Cambridge University Press; 2002

[12] Stoker JJ. Water Waves. NY: Interscience Publishers; 1957

[13] Svendsen IA. Introduction to Nearshore Hydrodynamics. Singapore: World Scientific; 2006

[14] Bryant E. Tsunami—the Underrated Hazard. 3rd ed. Springer International Publishing; 2014. DOI: 10.1007/978-3- 319-06133-7

[15] Rupakhety R, Ólafsson S, editors. Earthquake Engineering and Structural Dynamics in Memory of Ragnar Sigbjörnsson: Selected Topics. Chapter 8. Springer; 2017

[16] JAMSTEC. Causal Mechanisms of Large Slip during the Tohoku Earthquake of 2011. Revealed through Hydraulic Analysis of Fault Drilling Samples from the Deep–Sea Scientific Drilling Vessel Chikyu; Japan Agency for Marine-Earth Science and Technology. 2013. Available from: http://www.jamstec.go.jp/e/about/ press\_release/20131008/

[17] Land and Sea Areas of Crustal Movement and Slip Distribution Model of the Tohoku-Pacific Ocean Earthquake: Coseismic Slip Distribution Model. Report by the Geographical Survey Institute, Japan. 2011. Available from: http://www.gsi.go.jp/cais/topic 110520-index-e.html

[18] Fujii Y, Satake K, Sakai SI, Shinohara M, Kanazawa T. Tsunami source of the 2011 off the Pacific coast of Tohoku earthquake. Earth, Planets and Space. 2011;63(7):55

[19] Available from: https://www. youtube.com/watch?v=Lo5uH1UJF4A& feature=youtu.beNOAA. 2011

[20] Dutykh D, Dias F. Energy of tsunami waves generated by bottom motion. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2008;465(2103): 725-744

[21] Wikipedia. 2011 Tohoku earthquake and tsunami. 2016. Available from: https://en.wikipedia.org/wiki/2011\_T% C5%8Dhoku\_earthquake\_and\_tsunami

**221**

**Chapter 13**

*Chi-Yu King*

and S/L = 0.3–1.5 × 10<sup>−</sup><sup>6</sup>

fault gouge, friction

**1. Introduction**

**Abstract**

Kinematics of Slow-Slip Events

Large earthquakes are often preceded or followed by slow-slip events, which when better understood may help better understand the mechanisms of the earthquakes and the possibility of their prediction. This chapter summarizes kinematic values of large slow-slip events observed in Circum-Pacific subduction zones and creep events observed along strike-slip faults in California. The kinematic parameters include maximum slip S, duration T, rupture length L, rupture width, magnitude M, slip velocity VS, rupture velocity VR, and maximum slip/rupture length ratio S/L. For a large surface and subsurface creep event in California: S = 0.9–2.5 cm, T = 2–5 day, L = 6–8 km, W = 3–4 km, M = 4.7–4.8,

term slow-slip event in Circum-Pacific subduction zones: S = 1–20 cm, T = 2–50 day, L = 20–260 km, W = 10–90 km, M = 5.6–7.0, VS = 0.1–0.8 cm/d, VR = 2–20 km/d,

tion, rupture length/width, and magnitude than the former, but are comparable in slip velocity, rupture velocity, and S/L ratio. The kinematic behaviors of both are similar, despite their large difference in temperature, pressure, and composition of the fault-zone materials. The larger size of the latter is probably due to their larger inertia caused by their larger overburden. Compared with normal earthquakes, the slip and rupture velocities of both are smaller by many orders of magnitude. But their S/L values, and thus stress drops, are smaller by only one or two orders of magnitude. For a large long-term slow-slip event in the subduction zones: S = 1–50 cm, T = 50–2500 day, L = 40–1000 km, W = 30–750 km, M = 6.0–7.7,

duration, rupture length, and magnitude values are larger than the short-term events, but the average slip and rupture velocities are much smaller. This difference suggests that the long-term events may have commonly encountered stronger asperities, which can slow down or even break them into smaller short-term events.

**Keywords:** slow-slip, events, earthquake, tremor, fault zone, strike-slip, downdip, updip, plate interface, seismic, geodetic, Circum-Pacific, subduction zone, asperity,

Tectonic faults may rupture rapidly (seismically) to generate earthquakes or slowly (aseismically) without doing so. During the last two decades, many slow-slip events have been discovered, especially in the subduction zones around the Pacific Ocean [1–4]. Some of them preceded or followed major earthquakes [5–15]. This chapter summarizes kinematic parameters of these slow-slip events reported in the literature and compares them with creep events and shallow slow-slip events

. The latter kind of events have larger sizes in slip, dura-

. For a large short-

. The estimated slip,

VS = 0.4–0.5 cm/d, VR = 1.6–3.0 km/d, and S/L = 0.3–1.5 × 10<sup>−</sup><sup>6</sup>

VS = 0.01–0.10 cm/d, VR = 0.1–2 km/d, and S/L = 0.1–2 × 10<sup>−</sup><sup>6</sup>

## **Chapter 13** Kinematics of Slow-Slip Events

*Chi-Yu King*

## **Abstract**

source of the 2011 off the Pacific coast of Tohoku earthquake. Earth, Planets

Earthquakes - Impact, Community Vulnerability and Resilience

[19] Available from: https://www. youtube.com/watch?v=Lo5uH1UJF4A&

[20] Dutykh D, Dias F. Energy of tsunami waves generated by bottom motion. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2008;465(2103):

[21] Wikipedia. 2011 Tohoku earthquake and tsunami. 2016. Available from: https://en.wikipedia.org/wiki/2011\_T% C5%8Dhoku\_earthquake\_and\_tsunami

feature=youtu.beNOAA. 2011

and Space. 2011;63(7):55

725-744

220

Large earthquakes are often preceded or followed by slow-slip events, which when better understood may help better understand the mechanisms of the earthquakes and the possibility of their prediction. This chapter summarizes kinematic values of large slow-slip events observed in Circum-Pacific subduction zones and creep events observed along strike-slip faults in California. The kinematic parameters include maximum slip S, duration T, rupture length L, rupture width, magnitude M, slip velocity VS, rupture velocity VR, and maximum slip/rupture length ratio S/L. For a large surface and subsurface creep event in California: S = 0.9–2.5 cm, T = 2–5 day, L = 6–8 km, W = 3–4 km, M = 4.7–4.8, VS = 0.4–0.5 cm/d, VR = 1.6–3.0 km/d, and S/L = 0.3–1.5 × 10<sup>−</sup><sup>6</sup> . For a large shortterm slow-slip event in Circum-Pacific subduction zones: S = 1–20 cm, T = 2–50 day, L = 20–260 km, W = 10–90 km, M = 5.6–7.0, VS = 0.1–0.8 cm/d, VR = 2–20 km/d, and S/L = 0.3–1.5 × 10<sup>−</sup><sup>6</sup> . The latter kind of events have larger sizes in slip, duration, rupture length/width, and magnitude than the former, but are comparable in slip velocity, rupture velocity, and S/L ratio. The kinematic behaviors of both are similar, despite their large difference in temperature, pressure, and composition of the fault-zone materials. The larger size of the latter is probably due to their larger inertia caused by their larger overburden. Compared with normal earthquakes, the slip and rupture velocities of both are smaller by many orders of magnitude. But their S/L values, and thus stress drops, are smaller by only one or two orders of magnitude. For a large long-term slow-slip event in the subduction zones: S = 1–50 cm, T = 50–2500 day, L = 40–1000 km, W = 30–750 km, M = 6.0–7.7, VS = 0.01–0.10 cm/d, VR = 0.1–2 km/d, and S/L = 0.1–2 × 10<sup>−</sup><sup>6</sup> . The estimated slip, duration, rupture length, and magnitude values are larger than the short-term events, but the average slip and rupture velocities are much smaller. This difference suggests that the long-term events may have commonly encountered stronger asperities, which can slow down or even break them into smaller short-term events.

**Keywords:** slow-slip, events, earthquake, tremor, fault zone, strike-slip, downdip, updip, plate interface, seismic, geodetic, Circum-Pacific, subduction zone, asperity, fault gouge, friction

## **1. Introduction**

Tectonic faults may rupture rapidly (seismically) to generate earthquakes or slowly (aseismically) without doing so. During the last two decades, many slow-slip events have been discovered, especially in the subduction zones around the Pacific Ocean [1–4]. Some of them preceded or followed major earthquakes [5–15]. This chapter summarizes kinematic parameters of these slow-slip events reported in the literature and compares them with creep events and shallow slow-slip events

observed along the strike-slip faults in California. By such comparison, I hope to better understand not only the physical mechanisms of the different kinds of fault-slip behaviors but also the mechanisms of the related hydrological, geochemical, and geophysical changes often accompanying them [16, 17]. Such understanding, in turn, may help us to explore the possibility of short-term prediction of some earthquakes.

## **2. Creep events in California**

The fact that a tectonic fault may slip slowly was first found on a surface trace of a strike-slip fault in central California [18]. Early measurements by creepmeters showed that the slow-slip motion can occur not only steadily but also episodically in small steps of several millimeters in short durations of a few days with no slip in between [19]. Subsequent measurements by widely distributed networks of creepmeters showed that the occurrence of creep events was quite common along many fault segments in central California, and elsewhere [20–22].

By studying creep events recorded at neighboring sites, Nason [20] noticed that they often began at different times, suggesting that a creep event is a rupture propagation process with a velocity of about 1–10 km/day. King et al. [23] estimated the maximum slip velocity to be about 0.01–1 cm/day. By analyzing creep data recorded at many network sites (**Figure 1**) and by fitting the creep data to a faulting model [24], King et al. [25] found that a large creep event might have a rupture length of

#### **Figure 1.**

*Distribution of creepmeters along San Andreas, Calaveras, and Hayward faults in central California. The longterm fault motion in this region is right-lateral strike slip, ranging from 0 to 3 cm/year (after King et al. [25]).*

**223**

**Figure 3.**

**Figure 2.**

*et al. [25]).*

*Kinematics of Slow-Slip Events*

*DOI: http://dx.doi.org/10.5772/intechopen.84904*

*Two creep events that occurred within a dense array of creepmeters on Hayward-Calaveras fault (a and b). The records are arranged properly in both time and space, except for BRT2 where the timer was out of order (after King* 

*Fit of the observed creep curves for the 17 July 1971 event with a theoretical model with three different guidingcenter depths: 0 km (open circle), 0.5 km (dot), and 1.0 km (dashed line). The model curves are significantly* 

*different only at BLS. 2u is the amount of slip (after King et al. [25]).*

#### **Figure 2.**

*Earthquakes - Impact, Community Vulnerability and Resilience*

fault segments in central California, and elsewhere [20–22].

**2. Creep events in California**

observed along the strike-slip faults in California. By such comparison, I hope to better understand not only the physical mechanisms of the different kinds of fault-slip behaviors but also the mechanisms of the related hydrological, geochemical, and geophysical changes often accompanying them [16, 17]. Such understanding, in turn, may help us to explore the possibility of short-term prediction of some earthquakes.

The fact that a tectonic fault may slip slowly was first found on a surface trace of a strike-slip fault in central California [18]. Early measurements by creepmeters showed that the slow-slip motion can occur not only steadily but also episodically in small steps of several millimeters in short durations of a few days with no slip in between [19]. Subsequent measurements by widely distributed networks of creepmeters showed that the occurrence of creep events was quite common along many

By studying creep events recorded at neighboring sites, Nason [20] noticed that they often began at different times, suggesting that a creep event is a rupture propagation process with a velocity of about 1–10 km/day. King et al. [23] estimated the maximum slip velocity to be about 0.01–1 cm/day. By analyzing creep data recorded at many network sites (**Figure 1**) and by fitting the creep data to a faulting model [24], King et al. [25] found that a large creep event might have a rupture length of

*Distribution of creepmeters along San Andreas, Calaveras, and Hayward faults in central California. The longterm fault motion in this region is right-lateral strike slip, ranging from 0 to 3 cm/year (after King et al. [25]).*

**222**

**Figure 1.**

*Two creep events that occurred within a dense array of creepmeters on Hayward-Calaveras fault (a and b). The records are arranged properly in both time and space, except for BRT2 where the timer was out of order (after King et al. [25]).*

#### **Figure 3.**

*Fit of the observed creep curves for the 17 July 1971 event with a theoretical model with three different guidingcenter depths: 0 km (open circle), 0.5 km (dot), and 1.0 km (dashed line). The model curves are significantly different only at BLS. 2u is the amount of slip (after King et al. [25]).*

#### **Figure 4.**

*Fault-plane view of a theoretical faulting model that can reasonably fit the creep data of the 17 July 1971 event (case of 0 km depth in Figure 3). The fault trace is along the x-axis, below which is the fault plane. The rupture expands with a circular boundary whose positions are shown for several specified times (after King et al. [25]).*

several kilometers, an offset of about 1 cm. They also concluded that a creep event was kinematically similar to seismic faulting, but with rates that are five or more orders of magnitude smaller. **Figures 2**–**4** show the records of two creep events and the model fitting of the larger (**Figure 2b**) by King et al. [25], who found the following kinematic values: maximum slip S = 0.9 cm, duration T = 2 days, rupture length L = 6 km, rupture width W = 3 km, magnitude M = 4.7, average slip velocity VS = S/T = 0.45 cm/day, average rupture velocity VR = L/T = 3 km/d, and slip/rupture length ratio S/L = 1.5 × 10<sup>−</sup><sup>6</sup> . The S/L ratio, which is a measure of stress drop, is an order of magnitude smaller than that of seismic faulting.

#### **3. Subsurface slow-slip events in California**

Subsurface slow-slip event was first observed at San Juan Bautista (SJB) in central California, by using two continuously recording borehole strainmeters [24]. The recorded slip curves showed some kinks, which are probably caused by some higher-resistance patches, for similar kinks were found in a theoretical faulting model by barriers [25]. This event reached an estimated depth of 4 km and lasted about 5 days with an estimated maximum slip of 2.5 cm, a rupture length of 8 km, and a magnitude of 4.8. The kinematic values are comparable to those of the surface creep event described above.

In Parkfield area of California, Guilhem and Nadeau [26] studied 52 tremor episodes, which may be related to slow-slip events about 25 km deep. They estimated that a typical event has a duration of about 10 days, maximum slip of about 7.8 mm, rupture length of about 25 km, width of 15 km, and equivalent magnitude of 5.0–5.4. Excepting the slip value, it is larger than the surface and subsurface events described above. Similar slow-slip events have been detected along other inland faults also [7, 13].

#### **4. Slow-slip events in Circum-Pacific subduction zones**

Since about the beginning of the twenty-first century, with the deployment of an increasing number of geodetic instruments, many below-surface slow-slip events have been detected, especially along plate boundaries in the subduction zones

**225**

**Figure 5.**

ratio = S/L.

*Kinematics of Slow-Slip Events*

*DOI: http://dx.doi.org/10.5772/intechopen.84904*

estimate their kinematic values [2, 31–33].

in New Zealand and Costa Rica, however [41].

around the Pacific Ocean, where megathrust earthquakes often occur [1, 4, 27–30]. Most slow-slip events occurred offshore and were relatively far away from onland instruments. In areas where such events were continuously detected by dense networks of geodetic and seismic instruments, the resultant data have been analyzed to

In the Circum-Pacific subduction zones, most observed slow-slip events occur in transition areas downdip the seismogenic areas (asperities) and updip the stablesliding areas of the plate interfaces (e.g., **Figure 5**). Except in New Zealand and Costa Rica, they are mostly located quite far from onland instruments, including strainmeters, tiltmeters, and GPS stations [27–28, 34]. To delineate the kinematic parameters of a slip event, data have to be recorded continuously at multiple sites and inverted with the help of some elastic dislocation models, such as that by Okada [35]. Thus, the estimated kinematic values are rather uncertain. Some slow-slip events occurred in transition areas of plate interfaces updip the seismic asperities also. They have been detected more frequently as more instruments are deployed further offshore [9, 36]. Some slow-slip events were found to be accompanied by seismic tremors and low-frequency/regular earthquakes in/near the same areas of the plate interface [29, 37–40]. This suggested that these tremors and earthquakes were generated at small asperities swept over by the rupture front of the slow-slip events. Since then, additional information about the slow-slip kinematics has been obtained from the distribution and migration of these events recorded by seismic instruments. The depths of the observed slow-slip events usually range from 25 to 60 km; the durations in some zones show bimodal distribution of long term (of months to years) and short term (days to weeks). Short-term events in most subduction zones occurred closer to the deeper stable-sliding zone, while long-term events closer to the shallower seismogenic zone (**Figure 5**) [4]. The situation is somewhat different

The estimated kinematic parameters are given in the following order: maximum

slip S, duration T, rupture length L, width W, magnitude M, average slip velocity Vs = S/T, average rupture velocity VR = L/T, maximum slip/rupture length

In *Northeast Japan*, where the Pacific plate subducts west-northwestward beneath the North American or Okhotsk plate along the Northeast Japan Arc and the M 9.0 Tohoku-Oki megathrust earthquake occurred in 2011, a 9-year-long geodetic transient was detected that can be attributed to a very-long-term slow-slip event (possibly consisting of a serious of short-term subevents) with S = 40 cm,

*A cross-sectional sketch of the Nankai subduction zone in Japan (after Obara and Kato [4]).*

#### *Kinematics of Slow-Slip Events DOI: http://dx.doi.org/10.5772/intechopen.84904*

*Earthquakes - Impact, Community Vulnerability and Resilience*

ture length ratio S/L = 1.5 × 10<sup>−</sup><sup>6</sup>

**Figure 4.**

creep event described above.

inland faults also [7, 13].

an order of magnitude smaller than that of seismic faulting.

**4. Slow-slip events in Circum-Pacific subduction zones**

**3. Subsurface slow-slip events in California**

several kilometers, an offset of about 1 cm. They also concluded that a creep event was kinematically similar to seismic faulting, but with rates that are five or more orders of magnitude smaller. **Figures 2**–**4** show the records of two creep events and the model fitting of the larger (**Figure 2b**) by King et al. [25], who found the following kinematic values: maximum slip S = 0.9 cm, duration T = 2 days, rupture length L = 6 km, rupture width W = 3 km, magnitude M = 4.7, average slip velocity VS = S/T = 0.45 cm/day, average rupture velocity VR = L/T = 3 km/d, and slip/rup-

*Fault-plane view of a theoretical faulting model that can reasonably fit the creep data of the 17 July 1971 event (case of 0 km depth in Figure 3). The fault trace is along the x-axis, below which is the fault plane. The rupture expands with a circular boundary whose positions are shown for several specified times (after King et al. [25]).*

Subsurface slow-slip event was first observed at San Juan Bautista (SJB) in central California, by using two continuously recording borehole strainmeters [24]. The recorded slip curves showed some kinks, which are probably caused by some higher-resistance patches, for similar kinks were found in a theoretical faulting model by barriers [25]. This event reached an estimated depth of 4 km and lasted about 5 days with an estimated maximum slip of 2.5 cm, a rupture length of 8 km, and a magnitude of 4.8. The kinematic values are comparable to those of the surface

In Parkfield area of California, Guilhem and Nadeau [26] studied 52 tremor episodes, which may be related to slow-slip events about 25 km deep. They estimated that a typical event has a duration of about 10 days, maximum slip of about 7.8 mm, rupture length of about 25 km, width of 15 km, and equivalent magnitude of 5.0–5.4. Excepting the slip value, it is larger than the surface and subsurface events described above. Similar slow-slip events have been detected along other

Since about the beginning of the twenty-first century, with the deployment of an increasing number of geodetic instruments, many below-surface slow-slip events have been detected, especially along plate boundaries in the subduction zones

. The S/L ratio, which is a measure of stress drop, is

**224**

around the Pacific Ocean, where megathrust earthquakes often occur [1, 4, 27–30]. Most slow-slip events occurred offshore and were relatively far away from onland instruments. In areas where such events were continuously detected by dense networks of geodetic and seismic instruments, the resultant data have been analyzed to estimate their kinematic values [2, 31–33].

In the Circum-Pacific subduction zones, most observed slow-slip events occur in transition areas downdip the seismogenic areas (asperities) and updip the stablesliding areas of the plate interfaces (e.g., **Figure 5**). Except in New Zealand and Costa Rica, they are mostly located quite far from onland instruments, including strainmeters, tiltmeters, and GPS stations [27–28, 34]. To delineate the kinematic parameters of a slip event, data have to be recorded continuously at multiple sites and inverted with the help of some elastic dislocation models, such as that by Okada [35]. Thus, the estimated kinematic values are rather uncertain. Some slow-slip events occurred in transition areas of plate interfaces updip the seismic asperities also. They have been detected more frequently as more instruments are deployed further offshore [9, 36].

Some slow-slip events were found to be accompanied by seismic tremors and low-frequency/regular earthquakes in/near the same areas of the plate interface [29, 37–40]. This suggested that these tremors and earthquakes were generated at small asperities swept over by the rupture front of the slow-slip events. Since then, additional information about the slow-slip kinematics has been obtained from the distribution and migration of these events recorded by seismic instruments.

The depths of the observed slow-slip events usually range from 25 to 60 km; the durations in some zones show bimodal distribution of long term (of months to years) and short term (days to weeks). Short-term events in most subduction zones occurred closer to the deeper stable-sliding zone, while long-term events closer to the shallower seismogenic zone (**Figure 5**) [4]. The situation is somewhat different in New Zealand and Costa Rica, however [41].

The estimated kinematic parameters are given in the following order: maximum slip S, duration T, rupture length L, width W, magnitude M, average slip velocity Vs = S/T, average rupture velocity VR = L/T, maximum slip/rupture length ratio = S/L.

In *Northeast Japan*, where the Pacific plate subducts west-northwestward beneath the North American or Okhotsk plate along the Northeast Japan Arc and the M 9.0 Tohoku-Oki megathrust earthquake occurred in 2011, a 9-year-long geodetic transient was detected that can be attributed to a very-long-term slow-slip event (possibly consisting of a serious of short-term subevents) with S = 40 cm,

#### **Figure 5.**

*A cross-sectional sketch of the Nankai subduction zone in Japan (after Obara and Kato [4]).*

T = 3000 days, L = 250 km, W = 150 km, and M = 7.7. Also short-term slow-slip events here have the following kinematic values: S = 2–20 cm, T = 7– 35 days, L = 30–80 km, W = 30–50 km, and M = 6.8–7.0 [8–9, 42–44].

*Boso Peninsula* is in a complicated tectonic setting, where the Philippine Sea plate subducts northwestward beneath the Okhotsk plate at the Sagami trough, and the Pacific plate subducting westward beneath the Philippine Sea plate. Slow-slip events occur here roughly every 5–7 years on the interface between the Philippine Sea plate and the Okhotsk plate at a shallow depth of about 13 km. Short-term large events have the following kinematic values: S = 1.6–20 cm, T = 2–50 days, L = 40–100 km, W = 30–50 km, M = 6.0–6.7 [11, 45–50].

In the tectonically more complicated Southwest Japan including Tokai region and Kii and Bungo Channels, where quite a few great earthquakes occurred in history, the Pacific plate in the east subducts westward beneath the Philippine Sea plate, which in turn subducts northwestward beneath the Eurasian plate along the Nankai trough and northeastward beneath the Okhotsk plate along the Sagami trough. Many "long-term" and "short-term" slow-slip events at depths of 30–40 km have been observed since 1997.

In *Tokai region* near the Suruga trough, where the Philippine Sea plate subducts northwestward beneath the Eurasian plate at an annual rate of 2–3 cm/year, large long-term events have the following kinematic values: S = 7–30 cm, T = 2000– 2500 days, L = 80–100 km, W = 60–70 km, and M = 6.6–7.1. Large short-term events have the following kinematic values: S = 0.7–1.8 cm, T = 2–5 days, L = 20–90 km, W = 20–40 km, and M = 5.6–6.2 [38, 50–53].

In/near *Kii channel*, long-term slow-slip events have the following kinematic values: T = 398 days and M = 6.7 [54]. Short-term slow-slip events have the following kinematic values: S = 1–2 cm, T = 2–5 days, L = 20–90km, W = 20–30km, and M = 5.3–6.1 [36, 38, 55].

In/near *Bungo Channel*, large long-term events have the following kinematic values: S = 1–50 cm, T = 90–700 days, L = 40–200 km, W = 40–100 km, and M = 6.0–7.3. Some of them were found to possibly consist of multiple short-term events. Large short-term events have the following kinematic values: S = 1–4 cm, T = 4–10 days, L = 20–100 km, W = 20–50 km, and M = 5.8–6.3 [27, 38, 56–64].

In *Gisborne/Raukumara Peninsula*, *New Zealand*, where the Pacific plate subducts westward beneath the eastern North Island at the Hikurangi subduction zone, longterm events downdip the seismogenic interface area at the depth of 25–60 km in the southern margin have the following kinematic values: S = 4–56 cm, T = 50-550 days, L = 60–200 km, W = 30–150 km, and M = 6.5–7.2. Short-term events updip the seismogenic area (5–15 km deep) along northern Hikurangi margin have the following kinematic values: S = 1.2–24 cm, T = 5–36 days, L = 50–180 km, W = 50–90 km, and M = 5.8–7.0 [41, 65–75].

In *Alaska* subduction zone, where the great Mw = 9.21964 Prince William Sound earthquake ruptured a large portion of the shallow plate interface above 30 km depth at the eastern end, several long-term slow-slip events were detected just below the seismogenic zone at depths between 25 and 45 km with the following kinematic values: S = 2–40 cm, T = 620–1600 days, L = 150–1000 km, W = 140– 750 km, and M = 6.9–7.5 [76–78].

In *Cascadia* subduction zone, where the Juan de Fuca plate subducts beneath the North American plate, geodetic measurements show that the plate interface along an entire 1000 km segment between British Columbia and northern California is locked from near the surface to a depth of about 20 km [84]. No long-term slowslip event has been detected here. Large short-term slow-slip events at depths of 30–55 km in this segment have the following kinematic values: S = 1–8 cm, T = 7–50 days, L = 25–400 km, W = 25–70 km, and M = 6.1–6.9 [2, 28, 79–86].

**227**

**Table 1.** *Kinematic values.*

*Kinematics of Slow-Slip Events*

Circum-Pacific short

Hikurangi, New Zealand

Northwestern Costa

Circum-Pacific long

Hikurangi, New Zealand

Rica

term

term

*DOI: http://dx.doi.org/10.5772/intechopen.84904*

W = 50–130 km, and M = 6.3–7.2 [10, 87–96].

**Events S (cm) T (day) L (km) W** 

In *Mexico*, where the Cocos plate subducts beneath the North American plate along the Middle American Trench and great earthquakes occurred every 30–100 years, several long-term slow-slip events were detected below the seismogenic depth of 15–40 km with the following kinematic values: S = 9–30 cm, T = 90–400 days, L = 200–500 km, and W = 150–230 km. Short-term events have the following kinematic values: S = 2–10 cm, T = 30–45 days, L = 200–260 km,

In northwestern *Costa Rica*, the Nicoya Peninsula is located along the Middle America Trench where the Cocos plate subducts beneath the Caribbean plate at about 8 cm/yr. The subduction segment has ruptured repeatedly in the past. The peninsula lies directly over the seismogenic zone, and several slow-slip events possibly updip the seismic interface were detected with the following kinematic values: S = 1.5–15 cm,

California surface creep 0.9 2 6 3 4.7 0.45 3 1.5 SJB subsurface slow slip 2.5 5 8 4 4.8 0.5 1.6 0.31 Parkfield deep slow slip 0.8 10 25 15 5.0–5.4 0.08 2.5 0.03

Northeast Japan 2–20 7–35 30–80 30–50 6.8–7.0 0.29–0.57 2.3–4.3 0.67–2.50 Boso Peninsula 1.6–2.0 2–50 40–100 30–50 6.0–6.7 0.04–0.80 2–20 0.20–0.40 Tokai region 0.7–1.8 2–5 20–90 20–40 5.6–6.2 0.35–0.36 10–18 0.20–0.35 Kii Channel 1–2 2–5 20–90 20–30 5.3–6.1 0.40–0.50 10–18 0.22–0.50 Bungo Channel 1–4 4–10 20–100 20–50 5.8–6.3 0.25–0.40 5–10 0.40–0.50

Cascadia 1–8 7–50 25–400 25–70 6.1–6.9 0.14–0.16 3.6–8.0 0.20–0.40 Mexico 2–10 30–45 200–260 50–130 6.3–7.2 0.07–0.22 5.8–6.7 0.10–0.38

Central Ecuador 8–40 4–40 30–80 10–60 6.0–6.8 1.00–2.00 2.0–7.5 2.67–5.00 Chile 1.3–8 2–15 20–60 20–30 6.5–6.7 0.53–0.65 4–10 0.65–1.33

Northeast Japan 40 3000 250 150 7.7 0.013 0.08 1.60

Bungo Channel 1–50 90–700 40–200 40–100 6.0–7.3 0.01–0.07 0.29–0.44 0.25–2.50

Mexico 9–30 90–400 200–500 150–230 6.5–7.6 0.08–0.10 1.25–2.22 0.45–0.60 Chile 50–80 240 70–150 20–30 6.5–6.9 0.21–0.33 0.29–0.63 5.33–7.14

1000

Tokai region 7–30 2000–2500 80–100 60–70 6.6–7.1 0.004–

Alaska 2–40 620–1600 150–

**(km)**

1.2–24 5–36 50–180 50–90 5.8–7.0 0.24–0.67 5–10 0.24–1.33

1.5–15 20–180 30–120 20–40 6.6–6.7 0.07–0.08 0.7–1.5 0.50–1.25

4–56 50–550 60–200 30–150 6.5–7.2 0.08–0.10 0.36–1.20 0.67–2.80

140–750 6.9–7.5 0.003–

0.012

0.025

0.04 0.86–3.00

0.24–0.63 0.13–0.04

**M S/T (cm/d)**

**L/T (km/d)** **S/L**

T = 20–180 days, L = 30–120 km, W = 20–40 km, and M = 6.6–7.2 [97–103].

#### *Kinematics of Slow-Slip Events DOI: http://dx.doi.org/10.5772/intechopen.84904*

*Earthquakes - Impact, Community Vulnerability and Resilience*

W = 30–50 km, M = 6.0–6.7 [11, 45–50].

W = 20–40 km, and M = 5.6–6.2 [38, 50–53].

have been observed since 1997.

M = 5.3–6.1 [36, 38, 55].

M = 5.8–7.0 [41, 65–75].

750 km, and M = 6.9–7.5 [76–78].

L = 30–80 km, W = 30–50 km, and M = 6.8–7.0 [8–9, 42–44].

T = 3000 days, L = 250 km, W = 150 km, and M = 7.7. Also short-term slow-slip events here have the following kinematic values: S = 2–20 cm, T = 7– 35 days,

*Boso Peninsula* is in a complicated tectonic setting, where the Philippine Sea plate subducts northwestward beneath the Okhotsk plate at the Sagami trough, and the Pacific plate subducting westward beneath the Philippine Sea plate. Slow-slip events occur here roughly every 5–7 years on the interface between the Philippine Sea plate and the Okhotsk plate at a shallow depth of about 13 km. Short-term large events have the following kinematic values: S = 1.6–20 cm, T = 2–50 days, L = 40–100 km,

In the tectonically more complicated Southwest Japan including Tokai region and Kii and Bungo Channels, where quite a few great earthquakes occurred in history, the Pacific plate in the east subducts westward beneath the Philippine Sea plate, which in turn subducts northwestward beneath the Eurasian plate along the Nankai trough and northeastward beneath the Okhotsk plate along the Sagami trough. Many "long-term" and "short-term" slow-slip events at depths of 30–40 km

In *Tokai region* near the Suruga trough, where the Philippine Sea plate subducts northwestward beneath the Eurasian plate at an annual rate of 2–3 cm/year, large long-term events have the following kinematic values: S = 7–30 cm, T = 2000– 2500 days, L = 80–100 km, W = 60–70 km, and M = 6.6–7.1. Large short-term events have the following kinematic values: S = 0.7–1.8 cm, T = 2–5 days, L = 20–90 km,

In/near *Kii channel*, long-term slow-slip events have the following kinematic values: T = 398 days and M = 6.7 [54]. Short-term slow-slip events have the following kinematic values: S = 1–2 cm, T = 2–5 days, L = 20–90km, W = 20–30km, and

In/near *Bungo Channel*, large long-term events have the following kinematic values: S = 1–50 cm, T = 90–700 days, L = 40–200 km, W = 40–100 km, and M = 6.0–7.3. Some of them were found to possibly consist of multiple short-term events. Large short-term events have the following kinematic values: S = 1–4 cm, T = 4–10 days, L = 20–100 km, W = 20–50 km, and M = 5.8–6.3 [27, 38, 56–64].

In *Gisborne/Raukumara Peninsula*, *New Zealand*, where the Pacific plate subducts westward beneath the eastern North Island at the Hikurangi subduction zone, longterm events downdip the seismogenic interface area at the depth of 25–60 km in the southern margin have the following kinematic values: S = 4–56 cm, T = 50-550 days, L = 60–200 km, W = 30–150 km, and M = 6.5–7.2. Short-term events updip the seismogenic area (5–15 km deep) along northern Hikurangi margin have the following kinematic values: S = 1.2–24 cm, T = 5–36 days, L = 50–180 km, W = 50–90 km, and

In *Alaska* subduction zone, where the great Mw = 9.21964 Prince William Sound

In *Cascadia* subduction zone, where the Juan de Fuca plate subducts beneath the North American plate, geodetic measurements show that the plate interface along an entire 1000 km segment between British Columbia and northern California is locked from near the surface to a depth of about 20 km [84]. No long-term slowslip event has been detected here. Large short-term slow-slip events at depths of 30–55 km in this segment have the following kinematic values: S = 1–8 cm, T = 7–50 days, L = 25–400 km, W = 25–70 km, and M = 6.1–6.9 [2, 28, 79–86].

earthquake ruptured a large portion of the shallow plate interface above 30 km depth at the eastern end, several long-term slow-slip events were detected just below the seismogenic zone at depths between 25 and 45 km with the following kinematic values: S = 2–40 cm, T = 620–1600 days, L = 150–1000 km, W = 140–

**226**

In *Mexico*, where the Cocos plate subducts beneath the North American plate along the Middle American Trench and great earthquakes occurred every 30–100 years, several long-term slow-slip events were detected below the seismogenic depth of 15–40 km with the following kinematic values: S = 9–30 cm, T = 90–400 days, L = 200–500 km, and W = 150–230 km. Short-term events have the following kinematic values: S = 2–10 cm, T = 30–45 days, L = 200–260 km, W = 50–130 km, and M = 6.3–7.2 [10, 87–96].

In northwestern *Costa Rica*, the Nicoya Peninsula is located along the Middle America Trench where the Cocos plate subducts beneath the Caribbean plate at about 8 cm/yr. The subduction segment has ruptured repeatedly in the past. The peninsula lies directly over the seismogenic zone, and several slow-slip events possibly updip the seismic interface were detected with the following kinematic values: S = 1.5–15 cm, T = 20–180 days, L = 30–120 km, W = 20–40 km, and M = 6.6–7.2 [97–103].


**Table 1.** *Kinematic values.*

In the Central *Ecuador* subduction zone, short-term slow-slip events along this segment of the North Andean subduction zone, where the Nazca plate subducts beneath South America plate, are estimated to have the following kinematic values: S = 8–40 cm, T = 4–40 days, L = 30–80 km, W = 10–60 km, and M = 6.0–6.8 [42, 104–105].

In *Chile*, along a megathrust fault off northernmost Chile, where the Nazca plate subducts beneath the South American plate, a long-term slow-slip event occurred in a transition zone at depth of 40–60 km with the following kinematic values: S = 50–80 cm, T = 240, L = 70–150 km, W = 20–30 km, and M = 6.5–6.9. Also a short-term event indicated by earthquake migration occurred with S = 1.3–8 cm, T = 2–15 days, L = 20–60 km, W = 20–30 km, and M = 6.5–6.7 [11, 106–108].

**Table 1** gives a summary of the estimated kinematic values of slip S, duration T, rupture length L, rupture width W, and magnitude M, as well as calculated values of slip velocity VS = S/T, rupture velocity VR = L/T, and S/L, which is a measure of stress drop. In this table, a factor of 10<sup>−</sup><sup>6</sup> is omitted from the S/L values.

## **5. Discussion**

Among the short-term slow-slip events included in **Table 1**, those in New Zealand and Costa Rica occurred updip the seismogenic area of the subduction interface. Yet the estimated kinematic values are comparable to those downdip the seismogenic interface areas in other subduction zones. On the other hand, the kinematic values for central Ecuador are quite different, due to the unusually large slips reported. The same is true with Chile in the case of long-term events, and the opposite is true for the Parkfield events, when compared with two other cases in California. In the following discussion, we shall exclude these three cases from further consideration.

It may be seen that most short-term slow-slip events in the various Circum-Pacific subduction zones have comparable kinematic values: a slip of about 1–20 cm, duration of 2–50 days, rupture length of 20–260 km, width of 10–90 km, magnitude of 5.6–7.0, slip velocity of 0.1–0.8 cm/d, rupture velocity of 2–20 km/d, and an S/L value of 0.1–1.3. Compared with creep and shallow slow-slip events in California, they have larger values in slip, duration, rupture length/width, and magnitude, but comparable values in slip velocity, rupture velocity, and S/L ratio. This result indicates that kinematics of slow-slip events are basically similar, independent of temperature, pressure, and composition of the fault-zone materials, as long as they are mostly velocity-strengthening fault-gouge type; the larger sizes of the subduction events are probably due to their larger inertia associated with larger overburden at greater depth. Compared with normal earthquakes, the slip and rupture velocities of the slow-slip events are all smaller by many orders of magnitude, and the estimated S/L values are smaller by one or two orders of magnitude. Since S/L is proportional to stress drop, this result shows that the stress drops for the slow-slip events are one or two orders of magnitude smaller than normal earthquakes.

The long-term events have large variations in their kinematic values: slip of about 1–50 cm, duration of 50–2500 days, rupture length of 40–1000 km, width of 30–750 km, magnitude of 6.0–7.7, slip velocity of 0.01–0.10 cm/d, rupture velocity of 0.1–2 km/d, and S/L of 0.2–3. Compared with the short-term events, they have larger values in slip, duration, rupture length, and magnitude, comparable values in slip/rupture length ratios (thus stress drops) and smaller values in average slip and rupture velocities. This feature arose may be because they occurred closer to the seismogenic area of the plate interface [4], which has more asperities to hinder the

**229**

earthquakes and aftershocks.

*Kinematics of Slow-Slip Events*

*DOI: http://dx.doi.org/10.5772/intechopen.84904*

rupture process or even to break them into smaller events, as shown in the cases of northeast Japan and Bungo Channel. Being more remote from the instruments, they are less distinguishable, thus giving an appearance of slower propagation. This possibility is further supported by some recent analysis of long-term events [109, 110]. The reason why slow-slip events and seismic tremors occur in the transition areas, both downdip and updip the seismogenic area, of a subduction interface (e.g., **Figure 5**) is not well known, but may possibly be understood by the following consideration of a five-stage evolution of a subducting seafloor, which consists of seamounts of different heights and strengths embedded in sediments at its surface. At the initial stage of subduction, while under the front edge of the accretionary wedge where the temperature and confining pressure are low, the effect of heterogeneity of sliding friction is small, and thus fault slip caused by crustal convergence proceeds in the form of aseismic stable sliding. When the same seafloor subducts further down and encounter larger confining pressure but still relatively low temperature, the friction at the stronger patches (seamounts) begins to show its stick-slip (velocity weakening) feature in sliding, while the sedimentary parts acts like (velocity strengthening) fault gouge. As a relatively strong asperity breaks under increasing shear stress, the rupture propagates slowly into a larger area of interface consists of weaker asperities embedded in compliant gouge materials, thus causing slow-slip events and small earthquakes in the transition zone updip the seismogenic area of the plate interface. When the same seafloor subducts further down to the seismogenic depth, where the confining pressure becomes sufficiently large while the temperature is not, the heterogeneity contrast becomes very sharp, and thus when a strong patch (asperity) breaks, it may cause a rupture to propagate rapidly into a large area of the interface, sweeping through smaller asperities embedded in compliant gouge materials and resulting in a large or even megathrust earthquake in the seismogenic area of the interface. When the seafloor subducts further down and encounter still larger confining pressure and higher temperature, the large asperities may have been worn down by now and become softened, while the surrounding fault-gouge materials further cumulated in volume and strength. When such a weaker asperity breaks, it encounters stronger resistance and thus may cause only a slowly rupturing event in the transition zone of the downdip area; as the rupture sweeps through some even smaller asperities, it may cause seismic tremors and perhaps small earthquakes. When the seafloor subducts further down and encounters still higher confining pressure and temperature at the deepest level of subduction, the asperities may have become sufficiently worn and softened and the gouge materials further cumulated; the frictional heterogeneity may finally

become insignificant and thus the sliding becomes stable again.

What further directions should be pursued? Besides acquiring additional highquality data through more continuous monitoring efforts closer to the events, it is important to analyze the data with appropriate faulting models to better understand the mechanics of slow-slip events and their role as a silent agent in stress adjustment along fault zones. Such knowledge should help us to better understand the occurrence pattern of earthquakes, such as foreshocks, main shocks, aftershocks, earthquake swarm, and earthquake migration [111], as well as crustal deformation without earthquakes [112]. It may also help us better understand the mechanisms of various earthquake-related hydrological, geochemical, and geophysical changes [16]. Together with better monitoring efforts of such changes, especially those that precede earthquakes [14, 15], it may finally be possible to predict some destructive

#### *Kinematics of Slow-Slip Events DOI: http://dx.doi.org/10.5772/intechopen.84904*

*Earthquakes - Impact, Community Vulnerability and Resilience*

stress drop. In this table, a factor of 10<sup>−</sup><sup>6</sup>

[42, 104–105].

**5. Discussion**

further consideration.

normal earthquakes.

In the Central *Ecuador* subduction zone, short-term slow-slip events along this segment of the North Andean subduction zone, where the Nazca plate subducts beneath South America plate, are estimated to have the following kinematic values: S = 8–40 cm, T = 4–40 days, L = 30–80 km, W = 10–60 km, and M = 6.0–6.8

In *Chile*, along a megathrust fault off northernmost Chile, where the Nazca plate subducts beneath the South American plate, a long-term slow-slip event occurred in a transition zone at depth of 40–60 km with the following kinematic values: S = 50–80 cm, T = 240, L = 70–150 km, W = 20–30 km, and M = 6.5–6.9. Also a short-term event indicated by earthquake migration occurred with S = 1.3–8 cm, T = 2–15 days, L = 20–60 km, W = 20–30 km, and M = 6.5–6.7 [11, 106–108].

**Table 1** gives a summary of the estimated kinematic values of slip S, duration T, rupture length L, rupture width W, and magnitude M, as well as calculated values of slip velocity VS = S/T, rupture velocity VR = L/T, and S/L, which is a measure of

Among the short-term slow-slip events included in **Table 1**, those in New Zealand and Costa Rica occurred updip the seismogenic area of the subduction interface. Yet the estimated kinematic values are comparable to those downdip the seismogenic interface areas in other subduction zones. On the other hand, the kinematic values for central Ecuador are quite different, due to the unusually large slips reported. The same is true with Chile in the case of long-term events, and the opposite is true for the Parkfield events, when compared with two other cases in California. In the following discussion, we shall exclude these three cases from

It may be seen that most short-term slow-slip events in the various Circum-Pacific subduction zones have comparable kinematic values: a slip of about

1–20 cm, duration of 2–50 days, rupture length of 20–260 km, width of 10–90 km, magnitude of 5.6–7.0, slip velocity of 0.1–0.8 cm/d, rupture velocity of 2–20 km/d, and an S/L value of 0.1–1.3. Compared with creep and shallow slow-slip events in California, they have larger values in slip, duration, rupture length/width, and magnitude, but comparable values in slip velocity, rupture velocity, and S/L ratio. This result indicates that kinematics of slow-slip events are basically similar, independent of temperature, pressure, and composition of the fault-zone materials, as long as they are mostly velocity-strengthening fault-gouge type; the larger sizes of the subduction events are probably due to their larger inertia associated with larger overburden at greater depth. Compared with normal earthquakes, the slip and rupture velocities of the slow-slip events are all smaller by many orders of magnitude, and the estimated S/L values are smaller by one or two orders of magnitude. Since S/L is proportional to stress drop, this result shows that the stress drops for the slow-slip events are one or two orders of magnitude smaller than

The long-term events have large variations in their kinematic values: slip of about 1–50 cm, duration of 50–2500 days, rupture length of 40–1000 km, width of 30–750 km, magnitude of 6.0–7.7, slip velocity of 0.01–0.10 cm/d, rupture velocity of 0.1–2 km/d, and S/L of 0.2–3. Compared with the short-term events, they have larger values in slip, duration, rupture length, and magnitude, comparable values in slip/rupture length ratios (thus stress drops) and smaller values in average slip and rupture velocities. This feature arose may be because they occurred closer to the seismogenic area of the plate interface [4], which has more asperities to hinder the

is omitted from the S/L values.

**228**

rupture process or even to break them into smaller events, as shown in the cases of northeast Japan and Bungo Channel. Being more remote from the instruments, they are less distinguishable, thus giving an appearance of slower propagation. This possibility is further supported by some recent analysis of long-term events [109, 110].

The reason why slow-slip events and seismic tremors occur in the transition areas, both downdip and updip the seismogenic area, of a subduction interface (e.g., **Figure 5**) is not well known, but may possibly be understood by the following consideration of a five-stage evolution of a subducting seafloor, which consists of seamounts of different heights and strengths embedded in sediments at its surface. At the initial stage of subduction, while under the front edge of the accretionary wedge where the temperature and confining pressure are low, the effect of heterogeneity of sliding friction is small, and thus fault slip caused by crustal convergence proceeds in the form of aseismic stable sliding. When the same seafloor subducts further down and encounter larger confining pressure but still relatively low temperature, the friction at the stronger patches (seamounts) begins to show its stick-slip (velocity weakening) feature in sliding, while the sedimentary parts acts like (velocity strengthening) fault gouge. As a relatively strong asperity breaks under increasing shear stress, the rupture propagates slowly into a larger area of interface consists of weaker asperities embedded in compliant gouge materials, thus causing slow-slip events and small earthquakes in the transition zone updip the seismogenic area of the plate interface. When the same seafloor subducts further down to the seismogenic depth, where the confining pressure becomes sufficiently large while the temperature is not, the heterogeneity contrast becomes very sharp, and thus when a strong patch (asperity) breaks, it may cause a rupture to propagate rapidly into a large area of the interface, sweeping through smaller asperities embedded in compliant gouge materials and resulting in a large or even megathrust earthquake in the seismogenic area of the interface. When the seafloor subducts further down and encounter still larger confining pressure and higher temperature, the large asperities may have been worn down by now and become softened, while the surrounding fault-gouge materials further cumulated in volume and strength. When such a weaker asperity breaks, it encounters stronger resistance and thus may cause only a slowly rupturing event in the transition zone of the downdip area; as the rupture sweeps through some even smaller asperities, it may cause seismic tremors and perhaps small earthquakes. When the seafloor subducts further down and encounters still higher confining pressure and temperature at the deepest level of subduction, the asperities may have become sufficiently worn and softened and the gouge materials further cumulated; the frictional heterogeneity may finally become insignificant and thus the sliding becomes stable again.

What further directions should be pursued? Besides acquiring additional highquality data through more continuous monitoring efforts closer to the events, it is important to analyze the data with appropriate faulting models to better understand the mechanics of slow-slip events and their role as a silent agent in stress adjustment along fault zones. Such knowledge should help us to better understand the occurrence pattern of earthquakes, such as foreshocks, main shocks, aftershocks, earthquake swarm, and earthquake migration [111], as well as crustal deformation without earthquakes [112]. It may also help us better understand the mechanisms of various earthquake-related hydrological, geochemical, and geophysical changes [16]. Together with better monitoring efforts of such changes, especially those that precede earthquakes [14, 15], it may finally be possible to predict some destructive earthquakes and aftershocks.

*Earthquakes - Impact, Community Vulnerability and Resilience*

## **Author details**

Chi-Yu King Earthquake Prediction Research, Inc., El Macero, CA, USA

\*Address all correspondence to: chiyuking@gmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**231**

2013;**600**:14-26

*Kinematics of Slow-Slip Events*

10.1029/2006RG000208

2012;**102**:352-360

2014;**119**:6512-6533

Science. 2016;**353**:253-257

Letters. 2002;**203**:265-275

1989;**16**:1305-1308

2011;**331**(6019):877-880

[8] Kato A, Obara K, Igarashi T, Tsuruoka H, Nakagawa S, Hirata N. Propagation of slow slip leading to the 2011 Mw 9.0 Tohoku-Oki earthquake. Science. 2012;**335**:705-798

[9] Ito Y, Hino R, Fujimoto H, Osada Y, Inazu D, Ohta Y. Episodic slow slip events in the Japan subduction zone before the 2011 Mw 9.0 Tohoku-Oki earthquake. Tectonophysics.

[6] Linde AT, Silver PG. Elevation changes and the great 1960 Chilean earthquake: Support for aseismic slip. Geophysical Research Letters.

[7] Bouchon M, Karabulut H, Aktar M, Özalaybey S, Schmittbuhl J, Bouin MP. Extended nucleation of the 1999 Mw 7.6 Izmit earthquake. Science.

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**Author details**

Chi-Yu King

provided the original work is properly cited.

Earthquake Prediction Research, Inc., El Macero, CA, USA

\*Address all correspondence to: chiyuking@gmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

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Central California. Earth and Planetary Science Letters. 2012;**357-358**:1-10

[29] Hirose H, Hirahara K, Kimata F, Fujii N, Miyazaki S. A slow thrust event following the two 1996 Hyuganada earthquakes beneath the Bungo Channel, southwest Japan. Geophysical Research Letters.

[30] Drager H, Wang K, James TS. A silent slip event on the deeper Cascadia

subduction interface. Science.

[31] Obara K. Nonvolcanic deep tremor associated with subduction in southwest Japan. Science. 2002;**296**(5573):1679-1681

[32] Beroza GC, Ide S. Slow earthquakes and nonvolcanic tremor. Annual

Review of Earth and Planetary Sciences.

[33] Ide S, Beroza GC, Shelly DR, Uchide T. A scaling law for slow earthquakes. Nature. 2007;**447**:76-79. DOI: 10.1038/

[34] Obara K. Phenomenology of deep slow earthquake family in southwest Japan: Spatiotemporal characteristics

Geophysical Research. 2010;**115**:B00A25.

[35] Peng Z, Gomberg J. An integrated perspective of the continuum between earthquakes and slow-slip phenomena. Nature Geoscience. 2010;**3**:599-607.

[36] Heki K, Miyazaki S, Tsuji H. Silent fault slip following an interplate thrust earthquake at the Japan Trench. Nature.

[37] Okada Y. Surface deformation due to shear and tensile faults in a half-space. Bulletin of the Seismological Society of

America. 1985;**75**(4):1135-1154

and segmentation. Journal of

DOI: 10.1029/2008JB006048

DOI: 10.1038/ngeo940

1997;**386**:595-598

1999;**26**:3237-3240

2001;**292**:1525-1528

2011;**39**:271-296

nature05780

Processes: A Multi-disciplinary Approach

[18] Steinbrugge KV, Zacher EG. Creep on the San Andrea fault. Bulletin of the Seismological Society of America.

[19] Tocher D. Creep on the San Andreas Fault. Bulletin of the Seismological Society of America. 1960;**50**:396-404

[20] Nason RD. Earthq. Res. In: ESSA, 1969-70, ESSA Tech. Rep. ERL 1970;

[21] Schulz SS, Mavko GM, Burford RO, Stuart WD. Long-term fault creep observations in central California. Journal of Geophysical Research: Solid

[22] Harris RA. Large earthquakes and creeping fault. Reviews of Geophysics.

D. Characteristics of fault creep. Earthq. Res. In: ESSA, 1969-1970, ESSA Tech

Earth. 1982;**87**(B8):6977-6982

[23] King C-Y, Nason RD, Tocher

[24] King C-Y. Particle motion along a kinematic fault model. Bulletin of the Seismological Society of America.

[25] King CY, Nason RD, Tocher D. Kinematics of fault creep. Philosophical Transactions. Royal Society of London. 1973;**A.274**:355-360

[26] Linde AT, Gladwin M, Johnston M, Gwyther R, Bilham R. A slow earthquake sequence on the San Andreas Fault. Nature. 1996;**383**:65-68

[27] King C-Y. A shallow faulting model. Bulletin of the Seismological Society of

[28] Guilhem A, Nadeau RM. Episodic tremors and deep slow-slip events in

America. 1972;**62**:551-559

'Rep. ERL 182-ESL 11: 15-18

to Earthquake Prediction Studies. Washington: AGU/Wiley; 2018. 385 p

1960;**50**:389-396

182-ESL 11: 12-15

2017;**55**:169-198

1970;**60**:491-501

**232**

[38] Nakano M, Hori T, Araki E, Kodaira S, Ide S. Shallow very-low-frequency earthquakes accompany slow slip events in the Nankai subduction zone. Nature Communications. 2018;**9**(1): Article number 984

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## *Edited by Jaime Santos-Reyes*

This book is a collection of scientific papers on earthquake preparedness, vulnerability, resilience, and risk assessment. Using case studies from various countries, chapters cover topics ranging from early warning systems and risk perception to long-term effects of earthquakes on vulnerable communities and the science of seismology, among others. This volume is a valuable resource for researchers, students, nongovernmental organizations, and key decision-makers involved in earthquake disaster management systems at national, regional, and local levels.

Published in London, UK © 2019 IntechOpen © pavelalexeev / iStock

Earthquakes - Impact, Community Vulnerability and Resilience

IntechOpen Book Series

Earthquakes, Volume 2

Earthquakes

Impact, Community Vulnerability

and Resilience

*Edited by Jaime Santos-Reyes*