1

Hazards Concepts:

Explanatory Paradigm

• Behavioral: choices made by individuals and governments.

– Aka: Decision-making or choice paradigm

– (mis) Perception

– Technical solutions

• Development: the political-economic context, especially:– LDC vs. MDCs

– Often a critique of, colonization and development models.

– Reform of development and development institutions (e.g., World Bank) as solution

Hazards Concepts

• Natural Hazards: the interaction of human exposure and vulnerability and natural extremes

that creates loss and disruption in social and

environmental systems. (We include Smith’s “super

hazards” like asteroids, in this category).

• Disasters: hazard events causing large loss of life and severe property / economic loss. (Chap. 2)

We’ll deal mostly with natural disasters. [Smith and

Petley: actualization of a hazard].

• Risk: a measure of likelihood of an event and its

consequence (Chap. 4)

Hazards Concepts

• Exposure: physical and geographical coincidence of human occupancy and

investment and spatial extent of natural

extremes.

– Population and Property “at risk”

– Hazard zone occupance

• Vulnerability: tendency of place, group, or society to incur losses to hazards (“given

hazard”).

Hazards Concepts

• Factors in Vulnerability (pp. 15-20)tendency of place, group, or society to incur

losses to hazards.

– Economic: poverty = vulnerability (lacking of

capital, land, tools, options, information) Also:

higher proportionate loss

– Social: Age, gender, disability, health

– Political: bad government, war, political minority

– Environmental: unsustainable resources and

degraded environments

Hazards ConceptsTogether, trends in Exposure and Vulnerability must yield loss trends. BUT: how defined and measured?

– Simple total loss or loss trend?

– Distribution of loss across society?

– Proportionate loss of population or property at risk?

Impact / Loss trends:• Total (gross)---but should be de-trended for inflation (=constant dollars)

• Uncompensated or mitigated (net; also insured and un-insured)

• Benefit/Cost accounting (net)

• Marginal Benefit/Cost (additional value minus additional loss)

• Per unit of exposure (= vulnerability) Re-analyzed versions of this NOAA flood damage data set, similar to graph in the

textbook. Here is deflated (or constant) dollar losses.

BUT---how should we “normalize” to measure loss

per unit of exposure? First, constant dollars (1995):

2

THEN: ratio of some logical measure of exposure:

e.g., per population:

Or unit of wealth, development (buildings, homes),

investment, etc.:

Hazards Concepts

Resilience: the capacity to absorb and recover from a hazard event: rate of recovery

– Individual

–Collective

– Varies with wealth, preparedness, and other factors

Reliability: frequency with which systems (including hazard protection systems) fail (or don’t fail!)

Hazard Concepts

• Smith, Ch. 1

• Burton, Kates, and White, Ch. 2, pp. 19-31

Smith and Petley offer a bit

of a challenging illustration,

in which natural vs. man-

made (I would say

“technological”) and

voluntary vs. involuntary

make sense, but intense vs.

diffuse makes less sense (at

least to me).

As discussed in class,

certainly the middle natural

hazards like flood, drought,

and wildfire can have their

basic processes altered by

human action (as opposed

say to (EQ and volcano) like

land development, forest

management, and the

spread of irrigated

agriculture.

3

Societies range from

those that are

“secure” (e.g., high

absorptive capacity

and lots of

adjustments

available) to those

less so (poorer

societies with fewer

options), and these

can be in risky places

(Bangladesh, New

Orleans) or in relative

safe places (Colorado

or Dubai).

Ian Burton, Gilbert White, and Robert Kates

The Environment as Hazard (Oxford UP) pp. 19-31:

Defining and Measuring

Hazards

We’ll focus on Geophysical events

as hazards.

Measuring Hazards• Magnitude (or intensity): speed of wind, height of flood,

depth of snow, ground motions of earthquake.

• Frequency:

– Simple frequency: how often event occurs in given time frame,

– probability: chance in % or fraction of one of occurrence in some time frame (coming in Ch. 4)

– return period: average time between occurrences (of given magnitude). (coming in Ch. 4)

• Temporal spacing random vs. cyclical, clumpy, etc.

• Duration

• Areal extent

• Speed of onset

• Spatial dispersion

Intensity or magnitude

is measured and expressed in various ways (wind speed, central pressure,

ground movement as % of g---the acceleration of gravity, etc.).

But some analysts create simpler, categorical measures or scales, so they

create simple scales like the Safir-Simpson hurricane scale, Fujita tornado

intensity scale, Mercalli earthquake scale, and volcano explosivity index. In my

view, intelligent people can deal with more direct measures, and these scales

lack specificity, and some, the Snowstorm scale (below), just seem a bit silly.

4

Sample Scales of Hazard Intensity

We’ll take these and other measures up in

detail in the hazard-specific lectures and

chapters----here we use these as

examples to introduce the various ways

we measure intensity.

The Mercalli scale was developed to categorize the surface effects of an

earthquake as experienced by people and buildings, all affected by magnitude of

waves, type of surface, and type of human use.

“Drivers of autos disturbed”

“Waves seen on ground, line

of sight distorted”

“Many frightened and run

outdoors”

“Everyone runs outdoors”

10% chance in 50 years

Here’s example ground motion risk map---we go over steps in

EQ risk assessment in EQ lectures.

Ground motions for known magnitudes and relationship b/w ML and shaking

can be established, and then linked to frequency of seismic activity. Here are

peak velocity contours for the magnitude 6.7 1994 Northridge earthquake.

Contours of velocity are in cm/sec, measured by accelerometers. Red star is

epicenter, note peak motions off-set to north along foothills.

Another step in risk assessment is to map actual damage, here expressed

by the Modified Mercalli eq intensity scale, and link it to ground shaking, and

thus be able to project damage into the future.

5

Frequency is measured and analyzed in other ways. A typical starting

point is a histogram of events that plots frequency (number of

occurrences) against magnitude, with magnitude arrayed into classes

(aka “class intervals” or “bins”---in Excel).

Here is histogram of annual average temps for Boulder, 1948-2005.

Ann vbg Temp 1948-2005

024681012141618

46 47 48 49 50 51 52 53 54 55 56 57 58

More

Avg. Temp

Freq

You will create a histogram of

snowfalls in exercise 1, so be

sure you know what they how

and how to construct one.

This is straightforward

descriptive statistics, can be

done in Excel, and you can

count on the voracity of

Wikipedia entry on it.

Same data with different

intervals.

Mean (average) often is most frequent (mode), but not

always!

We’ll also use: Probability and Return Period to define

frequency, but won’t get to those until in Chap. 4.

The previous graph was a histogram of intensity plotted against frequency, this is

a time series of intensity (snow depth) over a period of years. Note it is plotted as

% of average (so 100% = mean; this method, also called “departure from normal”

or average, is often used for meteorological variables). A time series reveals the

temporal pattern & trend—in this case seemingly random over time (e.g., not

clumped with no obvious trend).

Mean

The times series

of rainfall in

Switzerland

(top) appears

relatively

random over

time, but the

rainfall in the

Sub-Saharan

Africa (the

“Sahel”--

bottom) does

show strong

clumping of

extremes over

time, especially

in the second

half of the

record.

Measuring Hazards• Magnitude (or intensity): speed of wind, height of flood,

depth of snow, ground motions of earthquake.

• Frequency:

– Simple frequency: how often event occurs in given time frame,

– probability: chance in % or fraction of one of occurrence in some time frame

– return period: average time between occurrences (of given magnitude).

• Temporal spacing random vs. cyclical, clumpy, etc.

• Duration

• Areal extent

• Speed of onset

• Spatial dispersion

6

Comparative

Measures:

Characteristic profiles

for hazards can

illustrate differences in

monitoring (e.g.,

immediate for

earthquakes, long-term

for droughts) and

warning systems.

Smith and Petley offer a bit

of a challenging illustration,

in which natural vs. man-

made (I would say

“technological”) and

voluntary vs. involuntary

make sense, but intense vs.

diffuse makes less sense (at

least to me).

Certainly the middle natural

hazards like flood, drought,

and wildfire can have their

basic processes altered by

human action (as opposed

say to (EQ and volcano) like

land development, forest

management, and the

spread of irrigated

agriculture.

Societies range from

those that are

“secure” (e.g., high

absorptive capacity

and lots of

adjustments

available) to those

less so (poorer

societies with fewer

options), and these

can be in risky places

(Bangladesh, New

Orleans) or in relative

safe places (Colorado

or Dubai).