Transcript Multi-Criteria Decision Aide (MCDA) at the Watershed Scale Biophysical Land Use Society Community Economy Firms Households Individuals Economic Structure and Change Land-Use Change and Social Context Watershed Health.

Multi-Criteria Decision Aide (MCDA)
at the Watershed Scale
Biophysical
Land Use
Society
Community
Economy
Firms
Households
Individuals
Economic Structure
and Change
Land-Use Change
and Social Context
Watershed Health
Decisions at the watershed scale are
characterized by:
Multiple goals
 Multiple alternatives to meet goals
 Multiple criteria for alternatives
 Multiple metrics, scale, and time dimensions of criteria
 Multiple decision-makers with . . .
 Diverse preferences
All within a decision environment where the only thing that
is certain is: CHANGE.
How can we structure such a decision-making process?
At the watershed scale, what is the
decision to make?
GOAL
Examples:
• Quantitative growth oriented goals
• Qualitative development oriented goals
• Specific management or action plans
What are the decision alternatives
that could help reach that goal?
GOAL
Alternative 1
Alternative 2
Alternative 3
Examples:
• Business as usual
• Directed growth policies; technical fixes
• Steady state
How do we choose amongst
alternatives? What criteria?
GOAL
Alternative 1
Alternative 2
Alternative 3
CEc CSc CEv
CEc CSc CEv
CEc CSc CEv
Examples:
• Economic (CEc): Employment, income, tax base
• Social (CSc): Income distribution, landscape character
• Environmental (CEv): Impervious surface, IBIs
How do we evaluate these criteria?
Metrics: Quantitative, qualitative
Degree of uncertainty
Data availability
Scale: Stream site, tax parcel, neighborhood,
sub-catchment, township, catchment,
county, state . . .
Time: Stream flow, industry and household processes,
land-use change, policy change, economic
change, government change . . .
How do we arrive at a goal when
multiple perspectives are involved?
GOAL
DM 1
A1
A2
DM 2
A3
A1
A2
DM 3
A3
Examples:
• Equity weights
• Alliances and consensus building
• Group process design
A1
A2
A3
How do we identify decision-makers’
preferences within
and between each criterion?
Within each criterion:
• Maximize or minimize
• Absolute or relative preference
Score
1
Score
1
0
0
Difference
Absolute
Difference
Relative
Within each criterion:
• Degree of indifference threshold
Score
1
0
Difference
Indifference
Threshold
Within each criterion:
• Degree of indifference threshold
• Degree of preference threshold
Score
1
0
Difference
Preference
Threshold
Within each criterion:
• Degree of indifference threshold, AND
• Degree of preference threshold
Score
1
0
Indifference Preference
Threshold Threshold
Between criteria:
• Weights
GOAL
Alternative 1
Alternative 2
Alternative 3
CEc CSc CEv
CEc CSc CEv
CEc CSc CEv
w1 + w2 + w3 = 1
Outcomes of the MCDA decision process
• Performance of each alternative by multiple
criteria
1
C1
C4
C6
0
C2
C5
-1
C3
C7
Outcomes of the MCDA decision process
• Pairwise comparison of alternatives by
multiple criteria
Alt-1
Alt-2
Outcomes of the MCDA decision process
• Preference ordering of alternatives for each
individual, and the group as a whole
A2
Partial
A3
A1
A5
A4
Complete
A3
A2
A4
A1
A5
Outcomes of the MCDA decision process
• Simultaneous comparison of criteria and
alternatives (individual GAIA Plane)
CEc
CSc
Alt-3
pi
Alt-2
CEv
Alt-1
Outcomes of the MCDA decision process
• Simultaneous comparison of decision-makers
and alternatives (group GAIA Plane)
DM-2
pi
Alt-1
Alt-2
Alt-3
DM-1
DM-3
Outcomes of the MCDA decision process
• Sensitivity analysis – walking weights and
stability intervals
CEc
CSc
Alt-3
pi
Alt-2
CEv
Alt-1
Outcomes of the MCDA decision process
•
•
•
•
Shared understanding
Coalition and/or consensus building
Concrete problem definition
Visualization of points and strength of
conflict
• Ample opportunities for revision
AND
• Ranking of decision alternatives