4.6.3. Implications of Climate Change for Water Management
Policy
Climate change exaggerates current pressures in water management—adding
to the debate on sound management strategies—and adds a new component.
This new component relates to uncertainty in climate change: How can water management
efficiently adapt to climate change, given that the magnitude (or possibly even
the direction) of change is not known? Conventionally, water resource managers
assume that the future resource base will be the same as that of the past and
therefore that estimates of indices such as average reservoir yield or probable
maximum flood that are based on past data will apply in the future. There are
two issues: assessing alternatives in the face of uncertainty and making decisions
on the basis of this assessment.
Techniques for assessing alternatives include scenario analysis and risk analysis.
Scenario analysis is central to climate change impact assessment, but it is
not widely used in water resource assessment (although there are some very important
exceptions, such as at the federal level in the United States). Scenario analysis,
as in climate change impact assessment, tends to involve simulation of the effects
of different scenarios, although in water resources assessment these tend to
be different demand and operational scenarios rather than different climate
scenarios. Stakhiv (1998) argues that if water managers already adopt a scenario-based
approach, as at the federal level in the United States (Lins and Stakhiv, 1998),
climate change therefore does not cause any additional conceptual challenges
to water management: Climate change can be regarded simply as an extra type
of scenario. However, the uncertain nature of climate change and the potential
for nonlinearities in impact mean not only that the range of scenarios conventionally
considered may be too narrow but also that a larger number of scenarios must
be evaluated. In practice, scenario-based approaches are used in few water management
agencies, and adoption of scenario analysis would challenge conventional water
management practices in many countries.
Risk analysis involves assessment of the risk of certain thresholds being crossed
under different possible futures (Major, 1998). It generally involves stochastic
simulation of hydrological data to develop a sampling distribution of possible
futures. In principle, climate change can be incorporated into risk analysis
by changing the underlying population from which data are generated according
to climate change scenarios. Matalas (1997) discusses the role of stochastic
simulation in the context of climate change and argues that given the wide range
in futures that often is simulated by assuming a stationary climate, the operational
assumption of stationarity may remain appropriate in the face of climate change
in some regions. However, it is possible that climate change could generate
futures outside those produced under stationarity, and it cannot be assumed
that climate change can be ignored in all circumstances.
The second main issue is that of decisionmaking under uncertainty. This issue
was widely investigated during the 1960s and 1970s, largely in the context of
uncertainties about demands or the precise distribution of floods and droughts
over the short and medium terms. Climate change has revived interest in decisionmaking
under uncertainty, and several analyses of different techniques have been published
(e.g., Fisher and Rubio, 1997; Frederick, 1997; Hobbs, 1997; Hobbs et al., 1997;
Luo and Caselton, 1997; Chao et al., 1999). There still is considerable debate.
Hobbs (1997), for example, concludes that Bayesian approaches involving allocation
of probabilities to specific outcomes are more suitable than Dempster-Shafer
reasoning (which requires the analyst to assign probabilities to ranges—perhaps
overlapping—of outcomes), but Luo and Caselton (1997) conclude the reverse.
Particularly significant is the issue of assigning probabilities to alternative
possible futures. Hobbs et al. (1997) note unease among water planners in assigning
subjective probabilities to different futures.
| Table 4-14: Headroom “score” characterizing
effect of climate change on resource zone yield: an approach used in UK
(UKWIR, 1998). |
 |
|
Range in Resource
Zone Yield between
Four Defined Scenarios a
|
Case 1:
Two Scenarios Above
and Two Below Mean
|
Case 2:
Three Scenarios Below
and One Above Mean
|
Case 3:
Three Scenarios Above
and One Below Mean
|
|
|
<15%
|
2
|
3
|
1
|
|
15–25%
|
4
|
6
|
2
|
|
25–35%
|
6
|
9
|
3
|
|
>35%
|
8
|
10
|
4
|
|
Planners of water resource and flood protection schemes conventionally cope
with uncertainty by adding a safety factor to design estimates. This safety
factor usually is defined arbitrarily. As part of a review of water resource
design practices in the UK, a more formal approach to calculation of this safety
factor, or “headroom,” has been developed (UKWIR, 1998). This procedure
identifies eight sources of supply-side uncertainty and three sources of demand-side
uncertainty, each of which is given a score. The total score is summed and converted
into a percentage value for the headroom allowance (with a maximum of 20%).
Climate change is included as one of the supply-side uncertainties; its score
depends on the range of estimates of supply-yield under four defined climate
change scenarios (Table 4-14). Although this approach
has many arbitrary elements, it does represent a systematic approach to the
treatment of climate change uncertainties in water resources assessment.
Different aspects of the water sector have different planning horizons and
infrastructure lifetimes. The parts of the water sector with long horizons and
lifetimes need to take a different approach to climate change than parts with
shorter lead times; one assessment and decision methodology will not be suitable
for all managers.
