Vulnerability analysis identifies conditions in which management options can fail, either in terms of model parameter values or as scenarios.

When to use

This is a form of stress testing where the focus is specifically on identifying failures (or successes), as opposed to mapping performance or comparing alternatives.

A clear definition of success/failure is needed to identify a vulnerability.

How

Both quantitative and qualitative methods can be applied, with or without a model.

Approaches include:
  • Scenario development, e.g. constructing narratives in which failure might occur
  • Scenario discovery, which commonly identifies regions in model scenario space where policy failures occur.
  • Breakpoint analysis, which identifies parameter values at which conclusions change, e.g. policy failures occur
    • Management Option Rank Equivalence (MORE), which uses optimisation to report the changes in each variable required to change the preferred management option
    • Crossover point scenarios, which identify the closest scenarios where the preferred option changes, either numerically or within participatory methods
    • Info-gap decision theory, which identifies the deviation from a best estimate (“uncertainty horizon”) within which an action will robustly provide a minimum acceptable “reward” or within which a windfall may be achieved, quantified respectively as “robustness” and “opportuneness”.
    • Optimisation-based hypothesis testing, which seeks to identify plausible model scenarios that falsify a hypothesis

Selected examples

  • In a simple flood demonstration problem answering the question "Will regular flooding of ecological assets occur?", vulnerability analysis is performed analytically, using scenario discovery, using POMORE (a variant of MORE), and through optimisation-based hypothesis testing
  • Resources