Decision Support Systems in Water Resources Planning and Management: Stakeholder Participation and the Sustainable Path to Science-Based Decision Making - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 428

model has been designed to help them make informed decisions. Further, any decisions
based on information provided by the models will not be considered sufficiently
trustworthy if the models are perceived by the stakeholders as a) not being transparent,
and/or b) if they are not convinced the model addresses their views and concerns, and/or c)
their input has not been requested or integrated into the development of the model.
So, how can we merge the science, data and models with decision-making at different levels
of operations, policy and governance, in a sustainable way over the long term? For all the
integrative science described in the previous chapter to be perceived as credible, relevant
and transparent (Liu et al 2008; Gupta et al 2011) - thus acceptable to inform and guide
decision-making in the public eye - one key factor is essential: stakeholder participation
through science-fed collaborative processes. In a participatory planning process, technical
models used to support planning and decision-making are developed collaboratively. That
is, decisions embedded in models are a product of agreement - sometimes after extensive
discussion - between scientists and stakeholders during periodic meetings. Such model
development forces the individuals involved to focus their communication on important
issues, ranging from processes and features represented in the model, to assumptions,
conservation measures, alternative scenarios, etc. This process provides an excellent setting
for ongoing simultaneous discussions about specific issues, being key to a better
understanding of the overall behavior of a system, the nature of certain problems and
potential solutions. Importantly, the participants educate each other, and a better overall
understanding is gained at many levels. First, it helps stakeholders understand the physical
system, and in particular the spatial distributions of pumping, diversions and land-use
management impacts in the basin. Second, such participatory processes allow for a better
understanding of the drivers and constraints of each stakeholder, of the agencies and
institutions being represented, i.e. what limits exist on each stakeholder's range of action. In
this way, stakeholders can gain insights into the bases for their divergent viewpoints, and
through increased understanding, be able to identify potential strategies to negotiate trade-
offs between opposing groups.
4.1 The conceptual model: A common understanding of how the system works
One of the essential steps sometimes underestimated in the collaborative development of a
model is the description and agreement on a common conceptual model of the system
(Gupta et al 2011). A conceptual model of a system is the understanding of how it works
and how the different components of the system interact with each other. Individuals - and
especially those of us who are scientists and academicians -may often think we understand
the overall system enough to develop a software model ourselves. However, our views and
understanding of the system, as those of any stakeholder or individual involved in the
process, are likely to be incomplete and conditioned by our background and our limited
individual experience. In a collaborative and participatory process, with representation from
all relevant stakeholders, all of these partial conceptual models will be shared and put in
common as pieces of a collective conceptual model. Through these interactions, individual
stakeholders will go through a process that has been termed social learning by improving
their own understanding of the socio-ecological system. As the collective conceptual model
becomes the basis on which decisions will be made, sustainability learning is the process by
which actors gain shared understanding of what decisions are likely to be sustainable and
which ones are not (Pahl-Wostl et al., 2007).