Decision support experiments and evaluations using seasonal to ...

Decision-Support Experiments and Evaluations using Seasonal to
Interannual Forecasts and Observational Data: A Focus on Water Resources
Figure 3.3 An example of a decision calendar for reservoir management planning. Shaded bars
indicate the timing of information needs for planning and operational issues over the year (Source:
Ray and Webb, 2000).
3.3.1.2 inFormation may not be available
at the time it could be uSeFul
It is well established in the climate science community
that information must be timely in order
to be useful to decision makers. This requires
that researchers understand and be responsive to
the time frames during the year for which specific
types of decisions are made. Pulwarty and
Melis (2001), Ray and Webb (2000), and Wiener
et al. (2000) have developed and introduced the
concept of “decision calendars” in the context
of the Western Water Assessment in Boulder,
Colorado (Figure 3.3). Failure to provide information
at a time when it can be inserted into the
annual series of decisions made in managing
water levels in reservoirs, for example, may result
in the information losing virtually all of its
value to the decision maker. Likewise, decision
makers need to understand the types of predictions
that can be made and trade-offs between
longer-term predictions of information at the
local or regional scale and potential decreases
in accuracy. They also need to help scientists
in formulating research questions.
The importance of leadership in initiating
change cannot be overstated (Chapter 4), and
its importance in facilitating information ex-
change is also essential; making connections
with on-the-ground operational personnel and
data managers in order to facilitate information
exchange is of particular importance. The presence
of a “champion” within stakeholder groups
or agencies may make the difference in successful
integration of new information. Identifying
people with leadership qualities and working
through them will facilitate adoption of new
applications and techniques. Recently-hired
water managers have been found to be more
likely to take risks and deviate from precedent
and “craft skills” that are unique to a particular
water organization (Rayner et al., 2005).
The following vignette on the Advanced Hydrologic
Prediction System (AHPS), established
in 1997, exemplifies a conscious effort by the
National Weather Service to respond to many
of these chronic relational problems in a decisional
context. AHPS is an effort to go beyond
traditional river stage forecasts which are shortterm
(one to three days), and are the product of
applied historical weather data, stream gage
data, channel cross-section data, water supply
operations information, and hydrologic model
characteristics representing large regions. It is
an effort that has worked, in part, because it has
Information must
be timely in order
to be useful to
decision makers.
This requires
that researchers
understand and be
responsive to the time
frames during the year
for which specific
types of decisions
are made.
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