Multi-Criteria Decision Aide (MCDA) at the Watershed Scale

1. 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

2. 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?

3. 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

4. GOAL Alternative 1 Alternative 2 Alternative 3 What are the decision alternatives that could help reach that goal? Examples: • Business as usual • Directed growth policies; technical fixes • Steady state

5. GOAL Alternative 1 Alternative 2 Alternative 3 CEc CEc CEc CSc CSc CSc CEv CEv CEv How do we choose amongst alternatives? What criteria? • Examples: • Economic (CEc): Employment, income, tax base • Social (CSc): Income distribution, landscape character • Environmental (CEv): Impervious surface, IBIs

6. 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 . . .

7. GOAL DM 1 DM 2 DM 3 A1 A1 A1 A2 A2 A2 A3 A3 A3 How do we arrive at a goal when multiple perspectives are involved? Examples: • Equity weights • Alliances and consensus building • Group process design

8. How do we identify decision-makers’ preferences withinand between each criterion?

9. 1 1 Linear Score Score Non-linear 0 0 Difference Difference Absolute Relative • Within each criterion: • Maximize or minimize • Absolute or relative preference

10. 1 Score 0 Difference Indifference Threshold • Within each criterion: • Degree of indifference threshold

11. 1 Score 0 Difference Preference Threshold • Within each criterion: • Degree of indifference threshold • Degree of preference threshold

12. 1 Score 0 Indifference Threshold Preference Threshold • Within each criterion: • Degree of indifference threshold, AND • Degree of preference threshold

13. GOAL Alternative 1 Alternative 2 Alternative 3 CEc CEc CEc CSc CSc CSc CEv CEv CEv • Between criteria: • Weights w1 + w2 + w3 = 1

14. Outcomes of the MCDA decision process • Performance of each alternative by multiple criteria C1 1 C4 C6 0 C2 C5 -1 C3 C7

15. Outcomes of the MCDA decision process • Pairwise comparison of alternatives by multiple criteria Alt-1 Alt-2

16. Outcomes of the MCDA decision process • Preference ordering of alternatives for each individual, and the group as a whole A2 A3 Partial A1 A5 A4 Complete A3 A2 A4 A1 A5

17. CEc CSc Alt-3 pi Alt-2 CEv Alt-1 Outcomes of the MCDA decision process • Simultaneous comparison of criteria and alternatives (individual GAIA Plane)

18. DM-2 pi Alt-3 Alt-2 Alt-1 DM-3 DM-1 Outcomes of the MCDA decision process • Simultaneous comparison of decision-makers and alternatives (group GAIA Plane)

19. CEc CSc Alt-3 pi Alt-2 CEv Alt-1 Outcomes of the MCDA decision process • Sensitivity analysis – walking weights and stability intervals

20. 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