---
title: "Ground Motions, Intensities, and Building Damage"
week: 9
lecture: 17
date: "2026-05-13"
topic: "Strong ground motion, seismic intensity, site effects, and earthquake-resistant design"
course_lo: ["LO-1", "LO-2", "LO-4", "LO-6", "LO-7"]
learning_outcomes: ["LO-OUT-A", "LO-OUT-C", "LO-OUT-E", "LO-OUT-F", "LO-OUT-H"]
open_sources:
  - "Lowrie & Fichtner 2020, *Fundamentals of Geophysics* 3rd ed., §3.6 (UW Libraries)"
  - "USGS ShakeMap Manual v4 (Worden et al., 2020) — open code & docs"
  - "Worden, Gerstenberger, Rhoades & Wald 2012, *BSSA* 102(1), 204–221 (DOI: 10.1785/0120110156)"
  - "Wald, Quitoriano, Heaton & Kanamori 1999, *Earthquake Spectra* 15(3), 557–564"
  - "USGS *Did You Feel It?* program — public-domain map products"
  - "PEER Ground Motion Database — open-access strong-motion records"
---

# Ground Motions, Intensities, and Building Damage

```{seealso}
📊 **Lecture slides** — [open in new tab ↗](https://uw-geophysics-edu.github.io/ess314/slides/lecture_17_slides.html)
```

::::{dropdown} Learning Objectives
:color: primary
:icon: target
:open:

By the end of this lecture, students will be able to:

- **[LO-17.1]** Distinguish *intensity* (an effect-based ordinal description of shaking) from *magnitude* (a source-based logarithmic measure) and from *peak ground motion* (an instrumental waveform measurement), and identify which quantity is appropriate for historical events, real-time alerts, building codes, and engineering design.
- **[LO-17.2]** Define peak ground acceleration (PGA), peak ground velocity (PGV), peak ground displacement (PGD), and 5%-damped pseudo-spectral acceleration $S_a(T)$; explain physically why PGA dominates the high-frequency content, PGV the intermediate band, and $S_a(T)$ at a chosen period $T$ governs the demand on a structure of natural period $T$.
- **[LO-17.3]** Predict and explain three site and source effects on shaking — geometric spreading and attenuation with distance, soft-soil amplification and resonance, and soil liquefaction — and apply the rule-of-thumb $T_{\text{building}} \approx N/10\ \text{s}$ to identify which buildings are most vulnerable to a given earthquake’s frequency content.
- **[LO-17.4]** Critique an AI-generated explanation of "what magnitude X earthquake will feel like at site Y" by separating source, path, and site contributions and identifying which assumptions are explicit and which are hidden.

::::

::::{dropdown} Syllabus Alignment
:color: secondary
:icon: list-task

| | |
|---|---|
| **Course LOs addressed** | LO-1 (observables from physical processes), LO-2 (forward models of shaking), LO-4 (limitations of intensity vs. PGA vs. $S_a$), LO-6 (communicating uncertainty), LO-7 (critique of AI shaking statements) |
| **Learning outcomes practiced** | LO-OUT-A (sketch a shaking-vs-distance curve), LO-OUT-C (explain *why* tall buildings resonate at long periods), LO-OUT-E (residuals between predicted and observed shaking), LO-OUT-F (which metric for which question), LO-OUT-H (critique an AI ShakeMap-style explanation) |
| **Prior lecture** | [Lecture 15 — Earthquake Phenomena II](15_earthquake_phenomena_II.md): magnitude, seismic moment, energy |
| **Next lecture** | [Lecture 18 — Tsunami](18_tsunami.md): the same Cascadia rupture seen as an ocean wave |
| **Lab connection** | Lab 4 (in progress): students compute PGA and PGV from PNSN waveforms and place them on a ShakeMap-style intensity scale |
| **Discussion connection** | Session 8 — Guest: Science–Society Boundary (building codes, communicating shaking risk) |

::::

## Prerequisites

Students should be comfortable with: the magnitude scale and seismic moment from
[Lecture 15](15_earthquake_phenomena_II.md); the wave equation and the concepts
of P-, S-, and surface-wave amplitude and frequency from
[Lectures 3–5](03_seismic_waves_basics.md); a base-ten logarithm; and the
single-degree-of-freedom oscillator with natural period $T_0 = 2\pi\sqrt{m/k}$
from introductory physics.

---

## 1. The framing question: how do we describe the shaking?

The 28 February 2001 Nisqually earthquake released a moment magnitude
$M_W$ 6.8 from a focal depth of 52 km beneath the southern Puget Sound.
The number $M_W$ 6.8 captured the *source*: how much fault slipped, over
what area, multiplied by crustal rigidity. But the people sheltering
under desks in Olympia and Seattle did not experience $M_W$ 6.8. They
experienced ground motion — a particular acceleration history at their
particular building, on their particular soil, lasting roughly 30
seconds and with a peak horizontal acceleration of about 0.16 g
downtown and rather more in the Duwamish industrial flats.

That distinction is the centre of this lecture. A magnitude is one
number assigned to the source. A ground motion is a function of time
recorded at a station. An intensity is a description of the human
experience or the engineering damage at a location. None of these is
reducible to the others, and confusion among them is the most common
single error in popular accounts of earthquakes.

```{figure} ../assets/figures/fig_17_intensity_vs_pgm.png
:name: fig-16-intensity-vs-pgm
:alt: Two stacked plots. Top: peak ground acceleration on the vertical axis versus epicentral distance on the horizontal axis, with three labelled curves for soft soil, stiff soil, and rock; PGA decreases with distance and is highest on soft soil. Bottom: the same axes for Modified Mercalli Intensity, decreasing in steps from IX near the source to II at 200 km, with shaded bands.
:width: 80%

Two complementary descriptions of shaking. **Top:** peak ground
acceleration, an instrumental measurement, decays roughly as a power
of distance and depends strongly on near-surface site conditions.
**Bottom:** Modified Mercalli Intensity, an ordinal description of
felt shaking and damage, also decays with distance but in
discrete integer steps that aggregate over a wide range of physical
amplitudes. The two scales are linked statistically through Ground
Motion / Intensity Conversion Equations (GMICEs) of the form used
in USGS ShakeMap. Reproduces the qualitative content of slide 4 of
the legacy deck and slide 6 (PGA/PGV/PGD/$S_a$ definitions);
mathematical curves are computed from a synthetic
attenuation model parameterised after Worden et al. (2012).
```

The lecture proceeds in three movements. **Sections 2–3** define the
physical observables — PGA, PGV, PGD, and spectral acceleration —
and the framework that connects them through Newton's second law to
the forces on a building. **Sections 4–5** turn from instruments to
felt experience: the Modified Mercalli scale, isoseismal maps, and
the limits of intensity as a measure of "size." **Sections 6–7**
explain why the same earthquake shakes adjacent buildings
differently — site amplification, resonance, liquefaction — and how
engineers convert that knowledge into the seismic provisions of
modern building codes.

---

## 2. Governing physics: from the wave equation to a force on a building

A seismic wave reaches a station as a vector ground motion
$\boldsymbol{u}(\boldsymbol{x}, t)$. Three derivatives of that single
field generate every quantity in this lecture:

```{admonition} Key Concept — Three time derivatives, three quantities
:class: important

For a ground-motion record measured at position $\boldsymbol{x}$:

$$
\boldsymbol{u}(\boldsymbol{x}, t)\quad\xrightarrow{\partial/\partial t}\quad
\boldsymbol{v}(\boldsymbol{x}, t) = \dfrac{\partial \boldsymbol{u}}{\partial t}
\quad\xrightarrow{\partial/\partial t}\quad
\boldsymbol{a}(\boldsymbol{x}, t) = \dfrac{\partial^2 \boldsymbol{u}}{\partial t^2}.
$$

The three are linked by Fourier transformation: at angular frequency
$\omega$, $\hat{v} = i\omega\,\hat{u}$ and $\hat{a} = -\omega^2\,\hat{u}$.
A factor of $\omega$ in the spectrum amplifies the high-frequency
content at each step. Therefore:

- **Displacement** $u$ emphasises *long* periods (large eddies of the
  wavefield, surface waves at distance, static offset of permanent
  deformation).
- **Velocity** $v$ emphasises *intermediate* periods (the body of the
  shaking, roughly 0.3–3 s for crustal earthquakes).
- **Acceleration** $a$ emphasises *short* periods (sharp arrivals,
  high-frequency body waves). By Newton's second law,
  $\boldsymbol{F} = m\boldsymbol{a}$, the acceleration is also the
  force-per-unit-mass that the ground exerts on a rigid object
  resting on it.
```

The three peak amplitudes of these signals are called **peak ground
acceleration (PGA)**, **peak ground velocity (PGV)**, and **peak ground
displacement (PGD)**. Strong-motion engineering uses the maximum
horizontal value of each, taken either as the larger of the two
recorded horizontal components or, in modern practice, as the maximum
over all azimuths obtained by rotating the two horizontal traces
through 360° (the "RotD100" measure of @Boore2010).

A real building, however, does not respond uniformly to all
frequencies. A flagpole, a single-storey house, and a 60-storey tower
each have a characteristic *natural period* of vibration — the period
at which they sway most easily in response to any forcing. The
quantity that most directly governs how much that flagpole or that
tower will be excited is not PGA itself but **5%-damped pseudo-spectral
acceleration** $S_a(T)$: the peak acceleration a single-degree-of-freedom
oscillator of natural period $T$ would experience while sitting on
this ground. Mathematically, $S_a(T)$ is the maximum of the response
of the equation

$$
\ddot{x}(t) + 2\zeta\omega_0\,\dot{x}(t) + \omega_0^2\,x(t)
\;=\; -\,\ddot{u}_g(t),
\qquad \omega_0 = 2\pi/T,
$$ (eq:sdof)

where $x(t)$ is the deflection of the oscillator's mass relative to
its base, $\ddot{u}_g(t)$ is the recorded ground acceleration,
$\zeta = 0.05$ is the standard damping ratio used in design codes, and
$S_a(T) \equiv \omega_0^2\,\max_t |x(t)|$ has units of acceleration
(commonly reported in $g$). Building codes specify design values of
$S_a(T)$ at $T = 0.2$ s (short-period, governing low-rise structures)
and $T = 1.0$ s (long-period, governing taller buildings), often with
values at $T = 3.0$ s as well for very tall structures.

```{figure} ../assets/figures/fig_17_response_spectrum.png
:name: fig-16-response-spectrum
:alt: Three panels stacked vertically. Top: a synthetic ground acceleration time series, lasting about 30 seconds, with a maximum near 5 seconds. Middle: the same record as ground velocity, with longer-period oscillations. Bottom: the 5%-damped pseudo-spectral acceleration as a function of period from 0.05 to 10 seconds, showing a broad peak between 0.2 and 1 second.
:width: 90%

The journey from a recorded ground motion to a design quantity. The
top panel shows a synthetic acceleration record. Integrating once in
time gives the velocity (middle), whose longer-period content is
visible. The bottom panel shows the 5%-damped response spectrum
$S_a(T)$ — the peak acceleration that an idealised single-degree-of
freedom oscillator of natural period $T$ would experience under this
shaking. A building of period $T$ feels the shaking most strongly at
the height of its corresponding peak; a stiff one-storey house
($T \approx 0.1$ s) and a 60-storey tower ($T \approx 7$ s) read
quite different "intensities" of the same earthquake.
```

### 2.1 The rule of thumb: $T_{\text{building}} \approx N/10$ s

Decades of measurements on real buildings — most systematically
compiled by ATC-72 and quoted in @Lowrie2020 — show that the
fundamental period of a regular framed building scales approximately
linearly with its number of storeys $N$:

$$
T_{\text{building}} \approx \frac{N}{10}\,\text{s}.
$$ (eq:building-period)

A two-storey wood-frame house has $T \approx 0.2$ s and is excited
strongly by PGA-rich high-frequency shaking. The 60-storey Columbia
Tower in Seattle has $T \approx 6$ s and barely feels a typical
crustal $M_W$ 6 earthquake, but is excited efficiently by the
long-period surface waves of a Cascadia $M_W$ 9 — for which it must
be designed. The Tokyo Skytree at 634 m has $T \approx 10$ s; the
Akashi-Kaikyō suspension bridge has $T = 8$–$20$ s. As cities have
built taller, their resonant periods have lengthened and the
relevant ground-motion band has shifted to longer periods —
precisely the band where megathrust subduction earthquakes radiate
most efficiently.

---

## 3. Mathematical framework: site amplification

Why should the same wave shake adjacent buildings differently? Two
adjacent stations on rock and on soft soil can record peak velocities
that differ by a factor of two to five. The physics is captured by
the **impedance contrast** between the deep crustal rock through which
the wave travels and the shallow sediments through which it must
emerge.

### 3.1 Energy flux and the impedance ratio

Consider an SH wave propagating vertically upward through a half-space
of seismic impedance $Z_1 = \rho_1 \beta_1$ (density times shear-wave
velocity) and refracting into a shallow soft layer of impedance
$Z_2 = \rho_2 \beta_2$, with $Z_2 \ll Z_1$. The transmitted-wave
amplitude $A_2$ at the surface — accounting for the free-surface
reflection that doubles it — relates to the incident amplitude $A_1$
in the rock by

$$
\frac{A_2}{A_1} \;=\; \frac{2\,Z_1}{Z_1 + Z_2} \;\approx\; \frac{2\,Z_1}{Z_1}\;=\;2,
\qquad\text{(if }Z_2\ll Z_1\text{)},
$$ (eq:impedance)

a factor of two amplification before any resonance is considered. For
a 30-m-thick layer of soft mud over crystalline basement
($\beta_2 \approx 200$ m/s, $\rho_2 \approx 1700$ kg/m³ versus
$\beta_1 \approx 3500$ m/s, $\rho_1 \approx 2700$ kg/m³), the impedance
ratio is $Z_1/Z_2 \approx 28$ and equation {eq}`eq:impedance` predicts
an amplification of $\sim 2$ for the upgoing wave. This is the
*single-layer linear* prediction; real soft soils amplify more at
their resonant frequencies and less at other frequencies, and they
deamplify when the shaking exceeds their elastic limit.

### 3.2 Site resonance

A flat-lying soft layer of thickness $H$ over rigid rock acts as a
quarter-wavelength resonator for vertically propagating SH waves.
The fundamental resonance condition is

$$
H \;=\; \frac{\lambda}{4} \;=\; \frac{\beta_2}{4\,f_0},
\qquad
f_0 \;=\; \frac{\beta_2}{4\,H}.
$$ (eq:site-resonance)

The Duwamish industrial flats in Seattle, for instance, sit on
$H \approx 200$ m of unconsolidated sediment with average
$\beta_2 \approx 350$ m/s, predicting $f_0 \approx 0.4$ Hz — a period
of $T_0 \approx 2.3$ s, dangerously close to the natural period of
20–30-storey buildings. The 1985 Mexico City earthquake, in which
the deep lacustrine clay basin amplified $T \approx 2$-s motion by
factors approaching 50 and selectively destroyed mid-rise buildings,
is the canonical illustration.

```{admonition} Notation
:class: note dropdown

| Symbol | Meaning | Units |
|---|---|---|
| $u, v, a$ | ground displacement, velocity, acceleration | m, m/s, m/s² |
| PGA, PGV, PGD | peak ground acceleration, velocity, displacement | $g$ or m/s², cm/s, cm |
| $S_a(T)$ | 5%-damped pseudo-spectral acceleration at period $T$ | $g$ or m/s² |
| $T$ | period (of an oscillator or of a wave) | s |
| $\omega = 2\pi/T$ | angular frequency | rad/s |
| $\zeta$ | damping ratio (0.05 = 5%) | — |
| $\rho$, $\beta$ | density, shear-wave velocity | kg/m³, m/s |
| $Z = \rho\beta$ | seismic impedance | kg m⁻²s⁻¹ |
| $H$ | thickness of soft layer | m |
| $f_0 = \beta_2/(4H)$ | fundamental site resonance frequency | Hz |
| $N$ | number of building storeys | — |
| $V_{S30}$ | average $S$-wave speed in upper 30 m | m/s |
| $I_{\text{MMI}}$ | Modified Mercalli Intensity | I–XII (ordinal) |

```

---

## 4. The forward problem: ground-motion prediction

Given an earthquake with magnitude $M$, distance $R$ from the
station, and site parameter $V_{S30}$ (the time-averaged shear-wave
velocity in the upper 30 m), can we predict PGA, PGV, and $S_a(T)$?
This is the forward problem of *engineering seismology*, and its
empirical solution is the **Ground-Motion Prediction Equation
(GMPE)**, a regression of observed records on these source, path,
and site variables. A schematic GMPE has the form

$$
\ln Y \;=\; f_{\text{source}}(M)\;+\;f_{\text{path}}(M, R)\;+\;f_{\text{site}}(V_{S30}) \;+\; \varepsilon,
$$ (eq:gmpe)

where $Y$ is the ground-motion intensity measure (PGA, $S_a(T)$, etc.)
and $\varepsilon$ is a residual with standard deviation $\sigma \approx 0.6$
in natural-log units — a factor of $e^{0.6} \approx 1.8$ in linear
amplitude. **Even with the best modern GMPEs, predicted motions and
observed motions disagree by a factor of two on a routine basis.**
That irreducible scatter is fundamental to the forecasting problem
and propagates into every seismic-hazard map.

The USGS ShakeMap system @Worden2020 implements the forward problem
in near-real time after every felt earthquake. It takes the rapidly
estimated source, predicts ground motion everywhere using a chosen
GMPE, and then **conditions** the prediction on whatever observed
PGAs, PGVs, and felt-intensity reports are available — a Bayesian
update of the prior GMPE prediction. ShakeMap is the operational
embodiment of equations {eq}`eq:gmpe` and the impedance/resonance
ideas of §3.

---

## 5. The inverse problem: from observation to source — the modern intensity scale

For an earthquake recorded only by historical descriptions
(newspapers, diaries, structural damage reports), no instrumental
PGA exists. The only available observable is the human or
engineering response: was there panic? Did chimneys fall? Did
masonry collapse? The **Modified Mercalli Intensity (MMI) scale**, a
revision by @Wood1931 of the original 12-point scale of Mercalli
(1902), is the standard ordinal description of these effects
(Table 1).

```{list-table} Modified Mercalli Intensity scale (paraphrased from USGS public-domain definitions).
:header-rows: 1
:name: tab-mmi

* - Level
  - Effect
  - Approx. PGA
* - I
  - Not felt except by very few
  - $< 0.0017\,g$
* - III
  - Felt by people indoors, vibrations like a passing truck
  - $\sim 0.005\,g$
* - V
  - Felt by all; some dishes broken, plaster cracks
  - $0.04$–$0.09\,g$
* - VI
  - Felt by all; furniture moved, slight damage
  - $0.09$–$0.18\,g$
* - VII
  - Damage negligible in well-built structures, considerable in poorly built
  - $0.18$–$0.34\,g$
* - VIII
  - Damage slight in specially designed structures, great in poorly built
  - $0.34$–$0.65\,g$
* - IX
  - Damage considerable in specially designed structures
  - $0.65$–$1.24\,g$
* - X
  - Most masonry destroyed; rails bent
  - $> 1.24\,g$
```

Three properties of intensity follow from the table.

**It is ordinal, not interval.** The step from VI to VII is not the
same physical jump as VII to VIII. Statistical relations between
intensity and PGA must therefore be estimated, not assumed —
@Worden2012 calibrated the modern Ground Motion / Intensity
Conversion Equation (GMICE) from thousands of paired California
records and DYFI reports, fitting a piecewise linear regression of
MMI on $\log_{10}\text{PGA}$ and on $\log_{10}\text{PGV}$.

**It mixes source, path, and site.** A wood-frame house in Olympia
on glacial outwash and an unreinforced-masonry building in Seattle
on the Duwamish flats will report different MMI values for the same
event. Felt-shaking maps (USGS *Did You Feel It?*) therefore reveal
both the earthquake and the geology.

**It depends on the building stock.** The Mercalli scale was
calibrated against early-twentieth-century unreinforced-masonry
construction. Modern wood-frame houses fail at higher intensities
than the original scale assumes; modern URMs collapse at lower
values. The same shaking is reported as a different MMI in
San Francisco today than it would have been in 1906.

These three caveats explain Robert Mallet's old warning, repeated
throughout the field: **intensity is not a measure of an earthquake,
it is a measure of an earthquake at a place**.

```{figure} ../assets/figures/fig_17_isoseismals_eastvswest.png
:name: fig-16-isoseismals
:alt: Two side-by-side outline maps of the contiguous United States. Left panel labelled "M6.0 Central California 2004" shows felt-it markers concentrated within roughly 200 km of the central California coast. Right panel labelled "M5.8 Central Virginia 2011" shows felt-it markers spread across the entire eastern half of the continent.
:width: 90%

Two earthquakes of similar magnitude, vastly different felt areas.
The 2004 Parkfield, California, $M_W$ 6.0 was felt across a region
roughly 300 km in diameter. The 2011 Mineral, Virginia, $M_W$ 5.8
was felt across more than 2 million km², from Atlanta to Toronto.
The difference is not the source: it is the path. The eastern
North-American crust has a quality factor $Q$ several times larger
than the western United States, and seismic waves attenuate far
less per unit distance. Reproduces the qualitative content of
slide 9 of the legacy deck using synthetic isoseismal contours
parameterised after USGS *Did You Feel It?* data products.
```

---

## 6. Site effects and soil failure

### 6.1 Liquefaction

In saturated, loosely packed sand, prolonged shaking causes the
intergranular water pressure to rise faster than it can drain. When
the **pore pressure** $p$ approaches the **effective confining stress**
$\sigma' = \sigma - p$, the granular skeleton temporarily loses
contact and the deposit flows like a liquid. This is **liquefaction**,
and three conditions favour it:

1. **Loose sandy soil** below the water table.
2. **Strong, sustained shaking** (PGA $\gtrsim 0.1\,g$ for at least 10 cycles).
3. **Shallow ground water** (within a few metres of the surface).

The 1964 Niigata earthquake, the 2011 Christchurch earthquake, and
sections of the 1989 Loma Prieta and 2001 Nisqually events all
produced spectacular liquefaction. The physical signature — sand
boils at the surface, buildings settling or tilting on intact
foundations — distinguishes liquefaction damage from direct shaking
damage. In Seattle, the Duwamish flats and Harbor Island are mapped
liquefaction-prone areas; the Washington Geological Survey's
*Liquefaction Susceptibility of Washington* maps are derived from
exactly this physical reasoning combined with $V_{S30}$ and depth-
to-water-table compilations.

### 6.2 Building failure modes

Damage in framed buildings has a small number of recurring patterns,
each diagnostic of a particular mismatch between the input ground
motion and the building's resistance:

```{figure} ../assets/figures/fig_17_failure_modes.png
:name: fig-16-failure-modes
:alt: Four side-by-side line drawings of a two-storey building. From left to right: undeformed reference, soft-story collapse with ground floor sheared sideways, full collapse with roof on the ground, and foundation rotation with the building tilted as a rigid body. Each drawing is labelled and shows arrows for the input force.
:width: 95%

Four characteristic failure modes of framed buildings under strong
shaking. **Soft-storey collapse** localises the deformation in a
single weak floor — typically the ground floor of a building with
parking openings — leading to total loss of that floor. **Frame
collapse** results from inadequate shear strength in the lateral
load path. **Foundation failure** can be uniform settlement, tipping,
or differential — the latter being the most damaging because it
introduces internal stresses absent in pure rigid-body motion. The
geometry redrawn from the slide deck of the legacy course; the
deformation kinematics computed from a Timoshenko-beam idealisation.
```

The engineering counterpart to each failure mode is a retrofit
strategy: **shear walls** (vertical reinforced concrete elements
between window openings) defeat soft-storey collapse; **cross-bracing
or gussets** add shear strength to existing frames;
**base isolation** (laminated rubber-and-steel bearings beneath the
foundation) decouples the building from the ground motion and shifts
the building's effective natural period upward, away from the
high-frequency band where most shaking energy lives; **viscous
dampers** convert kinetic energy into heat.

---

## 7. Connecting to Cascadia: ground motions in the Pacific Northwest

The Pacific Northwest faces three distinct earthquake source
populations, each generating a characteristic ground-motion
signature. **Crustal earthquakes** on faults such as the Seattle
Fault produce relatively short-duration, high-frequency shaking;
their PGA can be large (the 2001 Nisqually deep-slab event reached
$\sim 0.3\,g$ at some Olympia stations) but $S_a(T)$ at long periods
remains modest. **Intraslab earthquakes** within the subducting Juan
de Fuca plate, of which Nisqually is the canonical example, occur
deep enough that high-frequency surface motion is attenuated by
several orders of magnitude over the path. **Megathrust earthquakes**
on the plate-interface — last in 1700, expected at unknown future
date — radiate enormously long-period energy ($T = 3$–$30$ s) over
durations of two to five minutes. The same Cascadia $M_W$ 9 will
produce relatively modest PGA at Seattle but record-setting
$S_a(3\text{ s})$ — exactly the band that excites the city's
high-rise inventory.

The PNSN's nearly 200 strong-motion stations across Washington and
Oregon provide the ground-truth data that constrain the GMPEs used
in the Washington Department of Natural Resources' tsunami- and
shaking-hazard maps. This is the inverse problem in operational
form: instrument the network densely, accumulate a record set,
regress the GMPE, and use it to forecast where an as-yet-unrecorded
$M_W$ 9 will most strongly damage the built environment.

---

## 8. Research Horizon

Three open frontiers in strong-motion seismology drive much of the
current literature. They are all areas where geophysics intersects
machine learning, real-time computation, and engineering decision-
making.

**Site-specific GMPEs from machine learning.** The largest residuals
in equation {eq}`eq:gmpe` come from the assumption that a single
parameter ($V_{S30}$) captures all site effects. Modern work uses
full $V_S$ profiles, deep-learning-based site classifications, and
microtremor horizontal-to-vertical spectral ratios to fit
station-specific corrections — typically halving the residual at
well-instrumented sites @Bahrampouri2024.

**Earthquake early warning.** The USGS ShakeAlert system, deployed
across Washington, Oregon, and California in 2021–2023, uses the
first few seconds of P-wave arrivals at the closest stations to
estimate magnitude and predict the ground motion that the *S* and
surface waves will produce moments later. Machine-learning models
trained on the entire global strong-motion catalogue are being
integrated to refine these predictions @Mousavi2020.

**Physics-based simulation.** Empirical GMPEs cannot extrapolate to
the next Cascadia $M_W$ 9 — there is no instrumental record of one.
Physics-based simulations using anelastic 3D earth models and
kinematic or dynamic rupture descriptions @Frankel2018,
@Wirth2018 are now the state of the art for forecasting Cascadia
shaking, with results increasingly anchored to paleoseismic
constraints on rupture extent and slip distribution.

---

## 9. Societal Relevance — the Cascadia building-code conversation

The 2018 Washington State Building Code Council adopted the 2015
International Building Code with a Cascadia-specific amendment
extending the long-period spectral acceleration design value
$S_a(1.0\text{ s})$ in coastal counties to reflect the 2014 USGS
National Seismic Hazard Maps' updated Cascadia rupture model. In
practical terms, every new mid-rise apartment building from Bellingham
to Astoria is being designed today against an explicit forecast of
Cascadia long-period shaking — a forecast that did not exist a
generation ago.

The conversation between geophysics and building codes is the most
direct line from strong-motion research to public safety. The PNSN's
ShakeAlert deployment, the WA DNR's HAZUS loss estimates, and the
2024–2025 update of the Washington State CSZ Tsunami Loss Estimate
@WGS2024 all rest on the GMPEs and site-effect models described in
this lecture. For students considering geophysics careers, the
resilience-engineering interface — geotechnical site
characterisation, performance-based earthquake engineering, and the
real-time shaking-prediction pipeline at USGS — is one of the most
direct paths from a degree to public-impact work.

---

## 10. AI Literacy — *Critique an AI explanation of expected shaking*

```{admonition} AI Epistemics — Critique a generated shaking forecast (LO-7, LO-OUT-H)
:class: tip

Use a generative AI assistant (Claude, ChatGPT, Gemini) and submit
the following prompt:

> "I live in Seattle, in a wood-frame house. A magnitude 9.0
> earthquake happens on the Cascadia subduction zone, 200 km west
> of me. How strong will the shaking feel, and what should I expect?"

Then evaluate the response against the framework of this lecture:

1. **Does it separate source, path, and site?** A correct answer
   distinguishes how big the earthquake is, how far the waves
   travelled, and what soil the questioner sits on. An incorrect
   answer conflates these.
2. **Does it commit to a number, or quantify uncertainty?** A
   trustworthy answer reports a range (e.g., "MMI VI–VIII at
   different sites in Seattle, depending on soil") and notes the
   factor-of-two scatter inherent to GMPEs.
3. **Does it correctly invoke the period dependence?** A wood-frame
   house has $T \approx 0.2$ s — exactly the band where megathrust
   PGA is *not* as severe as for crustal events at the same
   distance. An AI that says "the house will be flattened" without
   noting this is reasoning from a generic earthquake template, not
   from Cascadia-specific physics.
4. **Does it handle non-uniqueness?** The question itself
   underspecifies the answer (no soil class, no building age, no
   distance precision). A good answer flags those missing inputs.

Submit a 250-word critique that: (i) reproduces the AI's response
verbatim, (ii) identifies at least three claims that are
quantitatively wrong, qualitatively misleading, or
unsupported, and (iii) rewrites one paragraph as you would have
it said. This is the LO-OUT-H critique, with the rubric attached
to Lab 4.

```

---

## 11. Concept Checks

1. A two-storey wood-frame house and a 30-storey steel-frame
   apartment building stand on the same lot in downtown Seattle. A
   crustal $M_W$ 6 earthquake produces shaking with PGA 0.2 $g$
   and $S_a(3\text{ s}) = 0.05\,g$. Which structure is in more
   danger from this event, and why? How would the answer change
   for a Cascadia $M_W$ 9 with PGA 0.15 $g$ and
   $S_a(3\text{ s}) = 0.4\,g$?

2. Sketch (qualitatively) PGA versus epicentral distance for two
   $M_W$ 6 earthquakes — one with hypocentre on basement rock at
   Bremerton, one beneath the Duwamish fill. Both at 30 km from
   downtown Seattle. Which station records higher PGA at downtown,
   and by what mechanism?

3. The 1556 Shaanxi earthquake killed an estimated 830,000 people
   and is described in Chinese chronicles as catastrophic. The
   2010 Maule, Chile, earthquake was $M_W$ 8.8 and killed 521. Why
   is using "intensity" to compare these two events more
   informative than using "magnitude," and why is the inverse
   *also* true?

---

## 12. Connections

This lecture closes Module 4 (Earthquake Phenomenology). The next
lecture — [Lecture 18 — Tsunami](18_tsunami.md) — takes the same
Cascadia rupture but views it as an oceanic forcing rather than as
a forcing of the built environment. The forward and inverse
problems are mathematically parallel: there too we predict a wave
field from a source, observe it imperfectly, and invert for the
fault slip. The site-amplification arguments of §3 reappear as
**bay amplification** and **harbour resonance**.

The methods described here also reappear in Module 7 (Geodynamics):
the impedance-contrast reasoning of §3 is the same physics that
governs free oscillations of the Earth (Lecture 11) and the
behaviour of Love and Rayleigh waves in a layered halfspace
(Lecture 4).

---

## Further Reading

- **Lowrie & Fichtner 2020**, *Fundamentals of Geophysics*, 3rd ed.,
  §3.6.5 (seismic risk and ground shaking). UW Libraries.

- **USGS ShakeMap Manual v4** — Worden, C.B., Thompson, E.M.,
  Hearne, M., Wald, D.J. (2020). [Open documentation](https://ghsc.code-pages.usgs.gov/esi/shakemap/manual4_0/index.html).

- **Worden, C.B., Gerstenberger, M.C., Rhoades, D.A., & Wald, D.J.
  (2012)**. Probabilistic relationships between ground-motion
  parameters and Modified Mercalli Intensity in California.
  *Bulletin of the Seismological Society of America*, **102**(1), 204–221.
  [DOI: 10.1785/0120110156](https://doi.org/10.1785/0120110156).

- **Mousavi, S.M., Ellsworth, W.L., Zhu, W., Chuang, L.Y., &
  Beroza, G.C. (2020)**. Earthquake transformer — an attentive
  deep-learning model for simultaneous earthquake detection and
  phase picking. *Nature Communications*, **11**, 3952.
  [DOI: 10.1038/s41467-020-17591-w](https://doi.org/10.1038/s41467-020-17591-w). Open access.

- **Frankel, A., Wirth, E.A., Marafi, N., Vidale, J., & Stephenson, W.J.
  (2018)**. Broadband synthetic seismograms for magnitude 9
  earthquakes on the Cascadia megathrust based on 3D simulations
  and stochastic synthetics. *Bulletin of the Seismological Society
  of America*, **108**(5A), 2347–2369.
  [DOI: 10.1785/0120180034](https://doi.org/10.1785/0120180034).

- **Washington Geological Survey, 2024**. Tsunami hazard — GIS data,
  Digital Data Series 22, v2.2. [Open data portal](https://www.dnr.wa.gov/programs-and-services/geology/geologic-hazards/Tsunamis).

- **PNSN Strong Motion** — [pnsn.org](https://pnsn.org). Real-time PGA/PGV maps for Washington and Oregon earthquakes.

- **PEER Ground Motion Database** — Pacific Earthquake Engineering
  Research Center. [Open-access](https://ngawest2.berkeley.edu) strong-motion record archive used for GMPE
  development.

```{bibliography}
:filter: docname in docnames
```
