Chapter 11

Question 1

Define fire risk

Answer 1

Characterizing conditions for a fire season across a zone. The probability or chance of fire starting determined by the presence and activities of causative agents (i.e. potential number of ignition sources).

Probability of fire

Risk = likelihood of a fire * severity of fire

Question 2

Define fire hazard

Answer 2

State of the fuel exclusive of weather.

Question 3

Define fire exposure

Answer 3

A physical quantity measured for each cell in a landscape grid to rate the potential for fire transmission over relatively localized ignition distances.

The level of risk or potential for a fire to spread and cause damage or harm to a particular area or location. ​ It is a measure of the likelihood and intensity of a fire occurring and affecting a specific area. Fire exposure takes into account factors such as the presence of flammable materials, weather conditions, topography, and proximity to ignition sources.

Question 4

List four different kinds of risk/uncertainty

Answer 4

1. Latent Risk - Unknown knowns
2. Aleatory Risk - Known knowns
3. Ontological Risk - Unknown unknowns
4. Epistemological Risk - Known unknowns

Question 5

List four components of wildfire threat rating

Answer 5

1. Fire behavior potential
2. Fire occurrence risk
3. Values at risk
4. Suppression capability

Question 6

Explain the relationship between FireSmart forest management and ecosystem memory.

Answer 6

Both have potential to decrease the fire behavior of the landscape through altered fuels. Firesmart forest mgmt aims to do what ecosystem memory does.

Question 7

Explain how burn probability is calculated using monte carlo simulation methods.

Answer 7

BP = # of times pixel burned / # of chances to burn (iterations)

Question 8

Explain why validation is an important part of the risk modeling process.

Answer 8

Used to ensure accuracy of models. Validating the model against historical data/empirical evidence/expert judgement assesses the models reliability and predictive power. Builds trust in models.

Question 9

Explain the difference between inductive and deductive research.

Answer 9

Deductive starts ‘general’ (ie a theory) and moves to ‘specific’ by developing a hypothesis, collection of observations, and confirmation of theory.

Inductive moves from ‘specific’ to ‘general’ by starting with data, observation of patterns, formulation of hypothesis, and then development of general theory/conclusions.

Question 10

Explore the importance of simplicity in science.

Answer 10

Easier to understand and work with. Wider range than complexity and specificity