Tools for Better Decision Making: Bridges from Science to Policy - Climate Change Impacts on Freshwater Ecosystems - page 279

For each of the climate scenario/management combinations the decision criteria
were quantified. These decision criteria were quantified under each scenario/
management combination using modelling and expert judgement. Water quality
and water quantity criteria were modelled using the INCA-N model. INCA-N
predicts stream nitrate concentration and flow using input data for land-use
distribution, fertilizer application rates for different land-use types and daily
climate variables (Whitehead et al . 1998a, b; Wade et al . 2002). Climate data for
the A2 and B2 SRES scenarios were provided by Sveriges Meteorologiska och
Hydrologiska Institut (SMHI) derived from the ECHAM General Circulation
Model (Roeckner et al . 2003). The ECHAM model outputs were downscaled to
the Tamar catchment using the method of Wade et al . (2008).
Data on land use, fertilizer application and stocking density for the BAU man-
agement options under the A2 and B2 climate scenarios were taken from the
CLUAM outputs and modified according to the scheme set out in Table 11.1 for
PT and DG options. Table 11.1 summarizes the data sources and assumptions
made to quantify the driving forces for diffuse pollution under each climate/
management combination. These data then formed the input data to the INCA-N
model.
The area of non-farmed land is provided as an output from the CLUAM
described above. Data for the potential maximum area of floodplain wetland is
taken from a survey of wetland areas (Hogan et al . 2001) and this figure was
used for the DG option. Current wetland areas are estimated to be approximately
25% of historical extent (Hogan et al . 2001). These data were modified
according to the scheme set out in Table 11.1 for different management
options.
The costs of implementing the measures are estimated using the Gross Margin
figures for different agricultural activities calculated by the CLUAM. The cost
of implementing the measures for BAU options are considered to be zero, as
this is the laissez-faire option. Other management options are costed according
to the estimated loss of total gross margin resulting from implementing the
management measure. For instance, if there is a reduction in head of cattle
between the A2 2050 BAU option and the A2 2050 PT option, then the cost is
estimated as the reduction in head of cattle multiplied by the gross margin per
head of cattle estimated by the CLUAM in 2050. The assumption is that in
order to encourage the reduction in stocking density as set out in the option
definition table, the cost, in terms of grants or subsidies to landowners, would
have to at least equal the loss of income compared with the BAU option for that
particular climate scenario.
Figure 11.6 shows results for the Current, Business as Usual, Policy Targets
and Deep Green scenarios under IPCC A2 and B2 climate scenarios for 2050. It
illustrates the potential usefulness of the DSS to decision makers at the catchment
scale as it shows that, under the A2 climate scenario, putting in place progressively
more stringent packages of the management measures defined in the scenarios
(Business as Usual, Policy Targets and Deep Green) can improve the overall MCA
score, indicating a more positive outcome in some of the sub-catchments.
Conversely, under the B2 climate scenarios, the total MCA score decreases with
progressively more stringent packages of the management measures in most