The document discusses factors that affect risk perception of natural hazards and provides tables to assess relationships between risk, probability, losses, and preparedness for different case studies. It also evaluates methods for predicting earthquakes, tsunamis, tropical cyclones, and droughts using monitoring technologies and factors like animal behavior or changes in groundwater. Respondents are asked to provide their own perception of risks and examples for factors that can increase or decrease risk perception.

1. HAZARD RISK
1. Assess the relationships between degree of risk, probability of hazard event occurring, predicted losses and level of preparedness
2. Fill out the white cells in the table below with case-studies/examples. Example: Industrial leak in LEDC = high risk + low probability

2. TYPES OF PERCEPTION OF NATURAL HAZARDS
Domination
“Hazards are extreme events,
predictable and their
magnitude can be forecast
through scientific research.
Their impact can be
Acceptance controlled”
“Hazards are natural events, Adaptation
“acts of God”, happen
randomly. “Hazards are influenced by
We can only hope we’ll be both natural and human
able to respond efficiently if factors, their magnitude can
they happen” be guessed based on
experience, we must adjust to
them flexibly”

3. State and explain your own perception of those risks
Texas (2011)
San Francisco (1989)
Finland (2011) Japan (2011)

4. FACTORS AFFECTING RISK PERCEPTION
Find examples for each factor
FACTORS INCREASING RISK PERCEPTION FACTORS DECREASING RISK PERCEPTION
Involuntary hazard Voluntary “chosen” hazard
Immediate impact Delayed impact
Direct impact Indirect impact
Fear of impact Lack of fear of impact
High fatalities Low fatalities
Fatalities peaked (time/space) Fatalities spread out (time/space)
“Personal” victims “Impersonal” victims (statistics)
Process not understood Process understood
Uncontrollable hazard Controllable hazard
Unfamiliar hazard Familiar hazard
Lack of trust in authority (government, scientists) Trust in authority (government, scientists)
High media attention Low media attention

5. Earthquake Prediction

6. Tsunami Prediction
Which regions are more/less
protected?

7. PREDICTION OF HAZARD EVENTS
Using named examples, evaluate the following hazard prediction methods
Hazard Hazard prediction methods
• Some, but not all faults are mapped and monitored
EARTHQUAKES • Foreshocks can be detected by seismographs
• Magnetometers can detect changes in magnetic field
• Lasers or sensors can monitor small movements along a fault
• Predictive factors: increase of radon in groundwater, unusual animal behavior
• Warning systems via cell phones or sirens if a shock wave is coming (S-wave travels at about 3-5 km/s)
• Pacific Warning System established in the Pacific ocean in 1948 (Hawaii) linked to seismographs, tidal stations
TSUNAMIS • DART (Deep-ocean Assessment and Reporting of Tsunamis) uses buoys linked to sea bed receptors and satellites
to monitor unusual ocean movements
• Warning is about 1hr per 1,000 km from epicenter (10hrs between Japan and California)
• Cost of fake warning is about $30M
• Known “Hurricane season” (July to October in Northern hemisphere)
TROPICAL • National Hurricane Center (NHC) in Miami, FL
CYCLONES • Monitoring of wind patterns in the ITCZ between 5° and 30° latitude (satellite, weather balloons, reinforced
weather airplanes) input in computer models at NHC
• Geostationary satellite monitoring of storm path over warm waters vs land
• Link between monitoring and vulnerability of at-risk population
• Accurate warnings rarely issued until 12-20 hours before landfall
• Risk of too many wrong warnings: complacency, economic cost, panic
• Monitoring of weather patterns (ex: ENSO)
DROUGHTS • Monitoring of rainfall and water reservoir levels
• Monitoring of crop failures or vegetation behavior
• Monitoring of food distribution system to detect shortages before they happen