Environmental Engineering Reference
In-Depth Information
Elements
Modules
Explorative Scenarios
Development out of
present
Anticipative Scenarios
Development out of future
Starting point of scenario
development
Anticipative
Scenarios
Step-by-step
building of data
Deductive
Method
Framework plus
data
Incremental
Method
Official future is
starting point
Methods of scenario
development
Model-based Scenarios
Computer-based models,
using algorithms
Intuitive Scenarios
No usage of algorithms
Qualitative methods
Approach of scenario
development
Mode of scenario
development
Generative mode
Iterative process
Adaptive mode
Linear process
Figure 2.12
Scenario generation
Source
: From Frommelt, 2008; drawing on Van der Heijden, 1996.
results depends largely on the level of uncertainty, range of factors (internal and external)
being considered and the quality of the scenario-building exercises.
Model-based scenarios involve a quantification of prominent uncertainties, often using
probabilistic tools. Intuitive approaches depend more on qualitative knowledge and insights
from which scenarios are developed. The development of storylines is a typical approach.
In some studies a combination of model-based and intuitive approaches is used, and increasingly
scenarios are being quantified so as to illustrate their likely impacts, their 'realism' and the
contributions of important policy measures within the scenarios. This is an important progression
from the earlier narrative-based approaches, though of course a quantitative basis can often
give a spurious level of certainty to future scenario impacts, when the assumptions taken in
the modelling are driving the impacts as much as other issues (Hickman et al., 2010a; Hickman
and Banister, 2007a).
There are two views concerning the means of scenario development. The generative mode
is to 'raise important questions for the future and advance understanding until a new and
unique insight has been gained' (Van der Heijden, 1996), whilst the adaptive mode considers
a range of scenarios to see whether they can respond to the uncertainty, but still remain flexible.
Coherence, plausibility, internal consistency and logical underpinning are obvious tests for
the resulting scenarios (Bradfield et al., 2005), but are often not achieved in scenario-based
studies.
One method has been to develop a scenario matrix, usually with two key parameters being
used to define the scenario dimensions. Key factors and uncertainties can be used. These are
clustered or ranked, with the scenarios typically using the key perceived uncertainties (ideally
