| setup_risk_events {care4cmodel} | R Documentation |
setup_risk_events
Description
Low-level function for setting up a risk matrix for a simulation run.
Available for users who want to build simulation runs out of single elements.
Regular users are recommended to use the function
simulate_single_concept for running a simulation with one
single command (where this function is internally used).
Usage
setup_risk_events(time_span, avg_event_strength = 1, area_risks)
Arguments
time_span |
Simulation time span to be covered (integer) |
avg_event_strength |
Number which indicates the average strength of a damage event in the simulation. Default is 1 which means that the survival probabilities as defined in the silvicultural concept of interest are applied exactly as they are. A value of 2 would mean that one damage event would have the same effect as would two subsequent events with normal strength. A value of 0 would trigger no damage events at all. |
area_risks |
Vector of subphase-wise baseline damage risks, contained in
the list made with |
Details
The function uses exponentially distributed random numbers (with expectation
= 1) for simulating the strenghth of damaging events. Such kind of
distribution where small events are much more frequent than strong ones is a
realistic assumption for forest damages. Such a random number is drawn for
each simulation point in time. The actual damage strength (i.e. relative area
loss) for a given subphase is then calculated as follows:
rel_area_loss = 1 - ((1 - x) ^ avg_event_strength) ^ event_strength,
where
x: The baseline area loss risk of a given stand development subphase as resulting from the silvicultural concept definition of interest
avg_event_strength: The user defined overall average event strenghth
event_strength: Exponentially distributed random number with expectation 1, indicating the damage event strength in a given year
Value
A matrix where each row is a point in simulation time, and each column represents a subphase of the silvicultural concept of interest (in increasing order). Each matrix element describes the relative area loss that will happen at a given time to a given subphase.
Examples
parms <- setup_parms(pine_no_thinning_and_clearcut_1)
setup_risk_events(time_span = 200,
avg_event_strength = 3,
area_risks = parms$risk)