Geoscience Reference
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combine the quantitative sophistication of numerical models with the accessibility
of qualitative visioning and scenario based approaches. These qualitative processes
range from single-day events involving members of the public, to six-month pro-
cesses involving civil servants in the Dutch government. A number of examples are
summarised in table 21.1.
One example of how qualitative and participatory models can be combined with
quantitative modeling tools is the recent Canadian effort to use a scenario tool -
known as Quest - to develop a regional strategy for sustainable development. It
was based on an explicitly normative approach approach to forecasting and future
scenario development called 'backcasting'. Rather than beginning with the present
state of affairs and projecting forwards, either through a formal predictive approach
or through a less formal effort to identify alternative pathways, backcasting defi nes
one or more normative endpoints fi rst and then works backwards to identify the
steps that would necessary to achieve the endpoint. It is similar to normative vision-
ing exercises, although most applications have populated backcasting scenarios with
quantitative data and have often used formal models to support the exercise. One
of the ambitions behind this initiative was to not only sketch out a normatively
desirable future and represent it using integrated modeling frameworks, but also to
provide an opportunity for participants in the exercise to modify their positions
based on the interaction between discrete choices.
The term 'backcasting' describes an approach used in the soft path energy studies,
which emerged following the oil shocks of the 1970s. Soft path energy studies dif-
fered from traditional approaches to energy planning by focusing on demand-side
management, energy effi ciency, alternative non-fossil fuelled and decentralised
supply technologies, behavioural change, rather than focusing on conventional
centralised supply-side options. These studies took experts' articulation of a desir-
able future and analysed how feasible such goals were. The purpose of the analyses
was to shed light on the policy and resource implications of different sectoral end-
points by describing the trajectories required to connect the current state-of-play
with the desired future.
The conceptual basis of backcasting lies in the recognition that the distant future
is inherently unknowable, particularly in problem contexts like sustainability.
Human choice and behavioural change can shape a desirable future, which is not
necessarily the most likely based on past and present conditions (Robinson, 2003).
Policy choices in such contexts are oriented by goals that require substantive change
from current trends. These discontinuities are not typically resolved by forecasting
approaches that are concerned with extrapolating what is most likely (Morgan
et al., 1999). Rather than focusing on the likelihood of various version of the future,
backcasting explores the feasibility of desirable futures. Backcasting forces a plural-
ity of futures by asking 'what would it take to make this happen?' (Robinson, 1988;
Dreborg, 1996).
According to Quist (2003), backcasting is composed of four principal steps:
strategic problem orientation; articulation of values and generation of desirable
future scenario(s); backcasting of trajectories; and identifi cation of interventions to
implement or initiate backcast trajectories. Backcast trajectories are typically
described in terms of fi rst-order economic, social, technological and institutional
milestones and changes. These in turn inform the types of policy measures and
behavioural shifts upon which the trajectories would be founded. Backcasting pro-
vides a framework for identifying the interventions or actions required to imple-
