Decision support experiments and evaluations using seasonal to ...

The U.S. Climate Change Science Program Chapter 3
66
•
•
•
Decision makers need to understand the types of predictions that can be made, and the
trade-offs between longer-term predictions of information at the local or regional scale
on the one hand, and potential decreases in accuracy resulting from transition to smaller
spatial scales on the other.
Decision makers and scientists need to work together in formulating research questions
relevant to the spatial and temporal scale of problems the former manage that can be supported
by current understandings of physical conditions.
Scientists should aim to generate findings that are accessible and viewed as useful, accurate
and trustworthy by stakeholders by working to enhance transparency of the scientific
process.
3.1 INTRODUCTION
Over the past century, the United States has
built a vast and complex infrastructure to provide
clean water for drinking and for industry,
dispose of wastes, facilitate transportation,
generate electricity, irrigate crops, and reduce
the risks of floods and droughts.To the average
citizen, the nation’s dams, aqueducts, reservoirs,
treatment plants, and pipes are taken for
granted. Yet they help insulate us from wet and
dry years and moderate other aspects of our
naturally variable climate. Indeed they have
permitted us to almost forget about our complex
dependences on climate. We can no longer ignore
these close connections (Gleick, 2000).
This Chapter synthesizes and distills lessons
for the water resources management sector
from efforts to apply decision-support experiments
and evaluations using SI forecasts and
observational climate data. Its thesis is that,
while there is a growing, theoretically-grounded
body of knowledge on how and why resource
decision makers use information, there is little
research on barriers to use of decision-support
products in the water management sector. Much
of what we know about these barriers comes
from case studies on the application of SI
forecast information and by efforts to span organizational
boundaries dividing scientists and
users. Research is needed on factors that can be
generalized beyond these single cases in order
to develop a strong, theoretically-grounded
understanding of the processes that facilitate information
dissemination, communication, use,
and evaluation, and to predict effective methods
of boundary spanning between decision makers
and information generators.
Decision support is a three-fold process that encompasses:
(1) the generation of climate science
products; (2) the translation of those products
into forms useful for decision makers (i.e., usercentric
information); and, (3) the processes that
facilitate the dissemination, communication,
and use of climate science products, information,
and tools (NRC, 2007). As shall be seen,
because users include many private and small
users, as well as public and large users serving
multiple jurisdictions and entities, effective
decision support is difficult to achieve.
Section 3.2 describes the range of major decisions
water users make, their decision-support
needs, and the role decision-support systems
can play in meeting them. We examine the attributes
of water resource decisions, their spatial
and temporal characteristics, and the implications
of complexity, political fragmentation, and
shared responsibility on forecast use. We also