1. © K.Fedra 2007 1 DSS for Integrated Water Resources Management (IWRM) Terms and definitions (suggested for self-study) DDr. Kurt Fedra ESS GmbH, Austria kurt@ess.co.at http://www.ess.co.at Environmental Software & Services A-2352 Gumpoldskirchen DDr. Kurt Fedra ESS GmbH, Austria kurt@ess.co.at http://www.ess.co.at Environmental Software & Services A-2352 Gumpoldskirchen

2. © K.Fedra 2007 2 Terminology defined Actor, stakeholder, participantActor, stakeholder, participant AlternativeAlternative AttributeAttribute ChoiceChoice Compromise, trade-off Conflict ConstraintConstraint Criterion, criteriaCriterion, criteria Decision matrix Decision, to decideDecision, to decide Decision Support System (DSS)Decision Support System (DSS) Decision variableDecision variable Dominated, non-dominatedDominated, non-dominated Feasible, infeasibleFeasible, infeasible Multi attribute theoryMulti attribute theory Multi-criteria analysisMulti-criteria analysis Objectives, multiple objectivesObjectives, multiple objectives Optimization Simulation, modeling Simulation, modeling Scenario, scenario analysis Scenario, scenario analysis Pareto optimality, set, surface Referene point Utopia, nadir Uncertainty Risk Robustness, resilience Instrument, measure Conservation laws, mass budget Valuation, CVM, TCM Economics NPV, EAC Game theory Zero sum games Cooperative games Win-win solutions

3. © K.Fedra 2007 3 Terminology defined Hobsons’ choiceHobsons’ choice ScoreScore Pugh methodPugh method ElicitationElicitation Preference structurePreference structure Ranking, orderRanking, order Cardinal (criteria)Cardinal (criteria) Ordinal (criteria)Ordinal (criteria) Nominal (criteria)Nominal (criteria) NormalizationNormalization Benefits, non-monetaryBenefits, non-monetary ComplianceCompliance Rational choice, maximizationRational choice, maximization Utility, utility functionUtility, utility function First order logic Modus ponens Implementation Efficiency Equity Sustainability Price elasticity Value (of water) Investment (EAC, cost recovery) Operating costs Cost-benefit analysis Monetization Damages, penalties Demand, Supply Reliability (of supply)

4. © K.Fedra 2007 4 Actor, stakeholder Any legitimate participant in the decision making process, affecting or affected by the underlying issues and problem situation: Any legitimate participant in the decision making process, affecting or affected by the underlying issues and problem situation: –Major water users, suppliers: e.g., utilities, communities, irrigation consortia, farmers/associations, industries; –Governmental regulatory and administrative institutions; –Interests groups (commercial, NGOs) –Academic and research institutions, consultants –Media

5. © K.Fedra 2007 5 Alternative:Alternative: one of several solutions to the problem;one of several solutions to the problem; a set of actions, measures, defined by one or more decision variables;a set of actions, measures, defined by one or more decision variables; Alternative: L, alius, other. Webster’s: Offering or expressing a choiceOffering or expressing a choice A proposition offering choice between two or more thingsA proposition offering choice between two or more things One of two or more things to be chosen.One of two or more things to be chosen.

6. © K.Fedra 2007 6 Attribute:Attribute: Property, variable, parameter, criterion describing a problem or solution (alternative); measurable (scalar or ordinal) Attribute: L. ad tribuere, to bestow) An inherent (measurable) characteristicAn inherent (measurable) characteristic An object closely related or belonging to a specific thingAn object closely related or belonging to a specific thing To regard as a characteristic of a thing (verb).To regard as a characteristic of a thing (verb).

7. © K.Fedra 2007 7 Choice:Choice: Option, the power of choosing;Option, the power of choosing; Selection, the act of choosing;Selection, the act of choosing; A sufficient number or variety to choose from.A sufficient number or variety to choose from. Choice, (old G, koisan, to choose) syn: option, alternative, preference, selection, election

8. © K.Fedra 2007 8 Constraint:Constraint: A limitation of possible (acceptable) attribute values for an alternativeA limitation of possible (acceptable) attribute values for an alternative Constraint: L, constringere, constrict, constrain The act, result of constraining :The act, result of constraining : To force by imposed stricture, restriction, or limitationTo force by imposed stricture, restriction, or limitation To restrict … to a particular modeTo restrict … to a particular mode

9. © K.Fedra 2007 9 Constraints:Constraints: CONSTRAINTS are minimal or maximal values of CRITERIA (target values) that a feasible alternative must fulfil.

10. © K.Fedra 2007 10 Cooperative games: Payoffs are calculated for coalitions (groups) of players that coordinate their strategies, assuming: Transferable utilities (sharing of benefits) Aiming at non-zero sum win-win solutions (increase in resource base) Payoffs are calculated for coalitions (groups) of players that coordinate their strategies, assuming: Transferable utilities (sharing of benefits) Aiming at non-zero sum win-win solutions (increase in resource base)

11. © K.Fedra 2007 11 Cooperative games: Assume water is used competitively by inefficient irrigation (farmer) high value (agro)industry Industry provides funds (bank loan) to farmer to improve irrigation efficiency (flooding  drip), using the (future) revenues of the additional income from water saved (increased production value) water market ? Assume water is used competitively by inefficient irrigation (farmer) high value (agro)industry Industry provides funds (bank loan) to farmer to improve irrigation efficiency (flooding  drip), using the (future) revenues of the additional income from water saved (increased production value) water market ?

12. © K.Fedra 2007 12 Criterion, criteria: Measurable attributes of the problem and decision alternatives; valued attributes or components of the system; measures of system performance. Measurable attributes of the problem and decision alternatives; valued attributes or components of the system; measures of system performance.

13. © K.Fedra 2007 13 Criteria examples: Supply/Demand ratio, availability Reliability of Supply (%) Efficiencies (water, economic) Sustainability (content change) Water quality (BOD, FC, NO 3, …) Equity, sustainability Costs and benefits: $$$ ! Supply/Demand ratio, availability Reliability of Supply (%) Efficiencies (water, economic) Sustainability (content change) Water quality (BOD, FC, NO 3, …) Equity, sustainability Costs and benefits: $$$ !

14. © K.Fedra 2007 14 Criteria and Preferences Feasibility (physical/technical, economic, socio-political: acceptability)Feasibility (physical/technical, economic, socio-political: acceptability) Economic efficiency (benefit/cost, net benefit, IRR, opportunity costs)Economic efficiency (benefit/cost, net benefit, IRR, opportunity costs) Compliance (water law, international agreements, environmental standards)Compliance (water law, international agreements, environmental standards) Sustainability (long-term effects)Sustainability (long-term effects) Equity (distribution of costs and benefits)Equity (distribution of costs and benefits)

15. © K.Fedra 2007 15 Decision, decide: Decision: L, decidere: to cut off Decision: L, decidere: to cut off to arrive at a solution that ends uncertainty or dispute about …to arrive at a solution that ends uncertainty or dispute about … to make a choice or judgementto make a choice or judgement to come or cause to come to a conclusionto come or cause to come to a conclusion

16. © K.Fedra 2007 16 Decision Support System: A Decision Support System is a A Decision Support System is a computer based problem solving system (HW, SW, data, people) that cancomputer based problem solving system (HW, SW, data, people) that can assist non-trivial choiceassist non-trivial choice between alternatives inbetween alternatives in complex and controversial domains.complex and controversial domains.

17. © K.Fedra 2007 17 Decision Support System: A DSS provides A DSS provides structured presentation of problem context (physical, regulatory, political, economic ),structured presentation of problem context (physical, regulatory, political, economic ), and tools for theand tools for the – design, – evaluation, – selection of alternatives (for non-trivial problems). A DSS provides A DSS provides structured presentation of problem context (physical, regulatory, political, economic ),structured presentation of problem context (physical, regulatory, political, economic ), and tools for theand tools for the – design, – evaluation, – selection of alternatives (for non-trivial problems).

18. © K.Fedra 2007 18 Decision variable: Attributes of a decision (alternative) that can be set or defined by the decision maker(s); Variables or parameters that define the measures, instruments, technologies, strategies, policies that implement the decision. Attributes of a decision (alternative) that can be set or defined by the decision maker(s); Variables or parameters that define the measures, instruments, technologies, strategies, policies that implement the decision.

19. © K.Fedra 2007 19 Decision making processes Basic components: Describe (understand) the problem situation, background, context, genesis, physiography, resources, stakeholders, rules = awareness)Describe (understand) the problem situation, background, context, genesis, physiography, resources, stakeholders, rules = awareness) Identify a preference structure (participation):Identify a preference structure (participation): –Criteria, Objectives/Constraints Identify or design alternatives, instrumentsIdentify or design alternatives, instruments Evaluate the alternatives, measure their contribution to the objectivesEvaluate the alternatives, measure their contribution to the objectives Rank and select an alternative (participation)Rank and select an alternative (participation) Basic components: Describe (understand) the problem situation, background, context, genesis, physiography, resources, stakeholders, rules = awareness)Describe (understand) the problem situation, background, context, genesis, physiography, resources, stakeholders, rules = awareness) Identify a preference structure (participation):Identify a preference structure (participation): –Criteria, Objectives/Constraints Identify or design alternatives, instrumentsIdentify or design alternatives, instruments Evaluate the alternatives, measure their contribution to the objectivesEvaluate the alternatives, measure their contribution to the objectives Rank and select an alternative (participation)Rank and select an alternative (participation)

20. © K.Fedra 2007 20 Dominated:Dominated: DOMINATED alternative: There is at least one alternative that is better in all criteria (or better in at least one and equal in all other) and thus to be preferred ! DOMINATED alternative: There is at least one alternative that is better in all criteria (or better in at least one and equal in all other) and thus to be preferred !

21. © K.Fedra 2007 21 Economics, NPV, EAC: Costs and benefits are central criteria of any problem or solution (alternative); to compare streams of money over time in projects or components of different life time and a discount rate (cost of capital). NPV: net present value computes the current value of (discounted) future costs and benefits; EAC: equivalent annual cost, combines annualized capital outlays (based on a discounted capital recovery factor) and annual operational costs. Costs and benefits are central criteria of any problem or solution (alternative); to compare streams of money over time in projects or components of different life time and a discount rate (cost of capital). NPV: net present value computes the current value of (discounted) future costs and benefits; EAC: equivalent annual cost, combines annualized capital outlays (based on a discounted capital recovery factor) and annual operational costs.

22. © K.Fedra 2007 22 Efficiency:Efficiency: is a ratio of ouput per unit input. Economic efficiency: cost per unit output or benefit, benefit cost ratio.Economic efficiency: cost per unit output or benefit, benefit cost ratio. Water efficiency: water use per unit output, e.g., hydropower or crop production.Water efficiency: water use per unit output, e.g., hydropower or crop production. is a ratio of ouput per unit input. Economic efficiency: cost per unit output or benefit, benefit cost ratio.Economic efficiency: cost per unit output or benefit, benefit cost ratio. Water efficiency: water use per unit output, e.g., hydropower or crop production.Water efficiency: water use per unit output, e.g., hydropower or crop production.

23. © K.Fedra 2007 23 Feasible, infeasible: Alternatives can be Feasible : they meet a set of requirements or CONSTRAINTS (specified a priori)Feasible : they meet a set of requirements or CONSTRAINTS (specified a priori) Infeasible : they fail to meet any or all of the CONSTRAINTSInfeasible : they fail to meet any or all of the CONSTRAINTS Alternatives can be Feasible : they meet a set of requirements or CONSTRAINTS (specified a priori)Feasible : they meet a set of requirements or CONSTRAINTS (specified a priori) Infeasible : they fail to meet any or all of the CONSTRAINTSInfeasible : they fail to meet any or all of the CONSTRAINTS

24. © K.Fedra 2007 24 Game theory Branch of applied mathematics, economics (von Neumann, Morgenstern 1944): Players, (agents, actors, stakeholders) choose Strategies that maximise their Payoff (return, gain net benefit) given the strategies of other agents. Branch of applied mathematics, economics (von Neumann, Morgenstern 1944): Players, (agents, actors, stakeholders) choose Strategies that maximise their Payoff (return, gain net benefit) given the strategies of other agents.

25. © K.Fedra 2007 25 Hobson’s choice Decision problem with only one alternative (take it or leave it) Identification or design of alternatives is crucial: probability of a good solution increases with the number of alternatives ! Thomas Hobson (1544-1630), stable owner, offered only the horse nearest to the gate: Where to elect there is but one, Tis’ Hobson’s choice, take that - or none. (Thomas Ward, 1688) Decision problem with only one alternative (take it or leave it) Identification or design of alternatives is crucial: probability of a good solution increases with the number of alternatives ! Thomas Hobson (1544-1630), stable owner, offered only the horse nearest to the gate: Where to elect there is but one, Tis’ Hobson’s choice, take that - or none. (Thomas Ward, 1688)

26. © K.Fedra 2007 26 Instrument, measure: Instruments, measures, strategies, policies, are defined in terms of Decision variables which define the specific configuration Effectiveness (which attributes and criteria will be affected) Efficiencies (costs and benefits) which together define the alternatives. Instruments, measures, strategies, policies, are defined in terms of Decision variables which define the specific configuration Effectiveness (which attributes and criteria will be affected) Efficiencies (costs and benefits) which together define the alternatives.

27. © K.Fedra 2007 27 Multi-attribute theory Multi-Attribute (Utility) Theory is an evaluation scheme that combines several attributes (criteria) in the evaluation of (the utility of) an object, decision, plan, project, …. by using some weighted sum of the individual attributes to arrive at a global overall summary or total evaluation.

28. © K.Fedra 2007 28 Multi-criteria analysis Includes a number of methods to arrive at a single evaluation (scoring, and subsequent ranking) for objects, decisions, plans, projects that are described by multiple (and non- commensurable) criteria (see also: multi-attribute theory).

29. © K.Fedra 2007 29 Non-zero sum games: Some (cooperative) strategies can increase the resource base Sum of benefits greater zero Non-zero sum games describe HOW TO MAKE A BIGGER CAKE Some (cooperative) strategies can increase the resource base Sum of benefits greater zero Non-zero sum games describe HOW TO MAKE A BIGGER CAKE

30. © K.Fedra 2007 30 Objectives, multiple objectives Something towards which effort is directed An aim or end of action Criteria we want to maximize or minimize Multiple objectives refer to more than one such goal addressed simultaneously in a given decision making situation (see also: multiple criteria) Something towards which effort is directed An aim or end of action Criteria we want to maximize or minimize Multiple objectives refer to more than one such goal addressed simultaneously in a given decision making situation (see also: multiple criteria)

31. © K.Fedra 2007 31 Objectives:Objectives: OBJECTIVES are concepts we wish to maximize or minimize, measured by CRITERIA; several CRITERIA can contribute to the same OBJECTIVE, ( e.g., to “maximize net benefit”, various costs and benefits contribute); Criteria can be (hierarchically) structured and thus closely related/correlated (bias ?)Criteria can be (hierarchically) structured and thus closely related/correlated (bias ?) OBJECTIVES are concepts we wish to maximize or minimize, measured by CRITERIA; several CRITERIA can contribute to the same OBJECTIVE, ( e.g., to “maximize net benefit”, various costs and benefits contribute); Criteria can be (hierarchically) structured and thus closely related/correlated (bias ?)Criteria can be (hierarchically) structured and thus closely related/correlated (bias ?)

32. © K.Fedra 2007 32 Objectives, example: Criterion : net benefitCriterion : net benefit Objective : maximize net benefitObjective : maximize net benefit Constraint : at least a net benefit of XConstraint : at least a net benefit of X DSS output: the values (settings) of the decision variables (instruments applied) to reach some targets; the problem may be feasible (can be solved) or infeasible (no possible solution). Criterion : net benefitCriterion : net benefit Objective : maximize net benefitObjective : maximize net benefit Constraint : at least a net benefit of XConstraint : at least a net benefit of X DSS output: the values (settings) of the decision variables (instruments applied) to reach some targets; the problem may be feasible (can be solved) or infeasible (no possible solution).

33. © K.Fedra 2007 33 Optimization:Optimization: Mathematical procedure to find the MAXIMUM or MINIMUM of an OBJECTIVE FUNCTION that may consist of one or more criteria subject to a set of CONSTRAINTS e.g.: Maximize NET BENEFIT = f(X) subject to meeting maximum investment cost limits where f(X) is a model of the system that yields net benefit. Mathematical procedure to find the MAXIMUM or MINIMUM of an OBJECTIVE FUNCTION that may consist of one or more criteria subject to a set of CONSTRAINTS e.g.: Maximize NET BENEFIT = f(X) subject to meeting maximum investment cost limits where f(X) is a model of the system that yields net benefit.

34. © K.Fedra 2007 34 Optimization:Optimization: Given: a transfer function (model) f : D ecision A lternative  R esponse from some set of decision alternatives DA Sought: an element x0 in DA such that f(x0) ≤ f(x) for all x in DA ("minimization") or such that f(x0) ≥ f(x) for all x in A ("maximization"). Given: a transfer function (model) f : D ecision A lternative  R esponse from some set of decision alternatives DA Sought: an element x0 in DA such that f(x0) ≤ f(x) for all x in DA ("minimization") or such that f(x0) ≥ f(x) for all x in A ("maximization").

35. © K.Fedra 2007 35 Pareto set or frontier: the set of all non-dominated alternatives (final selection requires trade-off between criteria, explicit or implicit weights)

36. © K.Fedra 2007 36 Preference structure: Expresses (one or more) decision makers’ preferences, expectation, aspirations quantitatively. Consists of: 1.A set of Criteria with an indication of the optimization direction (minimize, maximize) 2.Constraints (minimal or maximal acceptable values for some criteria; 3.Objectives, all other (unconstrained) criteria (several criteria could contribute to the same objective). Expresses (one or more) decision makers’ preferences, expectation, aspirations quantitatively. Consists of: 1.A set of Criteria with an indication of the optimization direction (minimize, maximize) 2.Constraints (minimal or maximal acceptable values for some criteria; 3.Objectives, all other (unconstrained) criteria (several criteria could contribute to the same objective).

37. © K.Fedra 2007 37 Price elasticity: Micro-economic theory, assumes that the consumption (purchase) of a commodity decreases with increasing price or cost. High elasticity: commercial use; Inelastic: consumption is independent of price, e.g., water for vital needs. Micro-economic theory, assumes that the consumption (purchase) of a commodity decreases with increasing price or cost. High elasticity: commercial use; Inelastic: consumption is independent of price, e.g., water for vital needs.

38. © K.Fedra 2007 38 Problem structure: Inputs (initial and boundary conditions) Driving conditions (uncontrollable) Decision variables (controlled) Outputs (measures of performance): Objectives (minimize or maximize, continuous, distance measure) Constraints (minimal or maximal levels, binary: feasible or not) Inputs (initial and boundary conditions) Driving conditions (uncontrollable) Decision variables (controlled) Outputs (measures of performance): Objectives (minimize or maximize, continuous, distance measure) Constraints (minimal or maximal levels, binary: feasible or not)

39. © K.Fedra 2007 39 Pugh method: MCA method, syn. for Decision Matrix: A matrix is used to summarize alternatives and (multiple) criteria; Scoring is based on subjective weights defined for (normalized) criteria Ranking and selection is based on maximum or minimum score MCA method, syn. for Decision Matrix: A matrix is used to summarize alternatives and (multiple) criteria; Scoring is based on subjective weights defined for (normalized) criteria Ranking and selection is based on maximum or minimum score

40. © K.Fedra 2007 40 Ranking, order: Establishing a sequence of alternatives; Ranking or order requires cardinal or ordinal criteria. Complete order requires a single, common criterion (most frequently: monetary cost) Multiple criteria or attributes only allow a partial order (ranking) that separates dominated from non-dominated (pareto optimal) alternatives. Establishing a sequence of alternatives; Ranking or order requires cardinal or ordinal criteria. Complete order requires a single, common criterion (most frequently: monetary cost) Multiple criteria or attributes only allow a partial order (ranking) that separates dominated from non-dominated (pareto optimal) alternatives.

41. © K.Fedra 2007 41 Rational choice Is a theory, hypothesis, paradigm, model … based on micro-economics: The DM is assumed to choose a set of actions (decisions) that MAXIMIZE his/her UTILITY given the DM preferences and expected outcome of the actions. Is a theory, hypothesis, paradigm, model … based on micro-economics: The DM is assumed to choose a set of actions (decisions) that MAXIMIZE his/her UTILITY given the DM preferences and expected outcome of the actions.

42. © K.Fedra 2007 42 Rational choice Assumes that (rational) individuals maximize welfare (individual and collective utility) as they conceive it, forward looking and consistently. G.Becker, 1993 Rational: based on reason Ratio (L.): computation, reason Reason: sufficient ground, explanation, logical defense; something (principle, law) that supports a conclusion; drawing of (logical) inferences Assumes that (rational) individuals maximize welfare (individual and collective utility) as they conceive it, forward looking and consistently. G.Becker, 1993 Rational: based on reason Ratio (L.): computation, reason Reason: sufficient ground, explanation, logical defense; something (principle, law) that supports a conclusion; drawing of (logical) inferences

43. © K.Fedra 2007 43 Reference point: A point in N dimensional decision space (one value for each of the criteria/dimensions), defined by the DM’s preference structure (default: UTOPIA) that defines scaling and measures of distance for individual (feasible) alternatives. The feasible alternative closest to the reference point (by some measure of distance) is the optimal (efficient) solution. A point in N dimensional decision space (one value for each of the criteria/dimensions), defined by the DM’s preference structure (default: UTOPIA) that defines scaling and measures of distance for individual (feasible) alternatives. The feasible alternative closest to the reference point (by some measure of distance) is the optimal (efficient) solution.

44. © K.Fedra 2007 44 Robustness, resilience: Robustness: low sensitivity of a system (or decision) to changes (uncertainty) in the inputs; implies stabilizing or buffer capacity. Resilience: the ability of a system to return to “normal” function after a (major) disturbance; implies self repair mechanisms. Robustness: low sensitivity of a system (or decision) to changes (uncertainty) in the inputs; implies stabilizing or buffer capacity. Resilience: the ability of a system to return to “normal” function after a (major) disturbance; implies self repair mechanisms.

45. © K.Fedra 2007 45 Simulation, modeling: The imitative representation of the functioning of one system by process by another. Mathemtical modeling: representation of a physical system by systems of equations to describe the system’s evolution in time and space. The imitative representation of the functioning of one system by process by another. Mathemtical modeling: representation of a physical system by systems of equations to describe the system’s evolution in time and space.

46. © K.Fedra 2007 46 Scenario analysis explores the reaction of a system to changes in the boundary conditions (uncontrolled inputs and control or decision variables) on the performance variables (criteria) in terms of the objectives and constraints of the decision problem: WHAT … IF ?

47. © K.Fedra 2007 47 Uncertainty:Uncertainty: Uncertainty: inability to measure or forecast with some (specified) precision Measurement uncertainty: Principle element (Heisenberg) Practical element (methodological, measurement and sampling error) Uncertainty: inability to measure or forecast with some (specified) precision Measurement uncertainty: Principle element (Heisenberg) Practical element (methodological, measurement and sampling error)

48. © K.Fedra 2007 48 Valuation:Valuation: Provides an economic or monetary value for criteria (e.g., as the basis for cost-benefit analysis). Economic assessment or monetization of the costs and benefits of the supply and use of water, water quality, and all instruments and measures. Can be based on: Market prices (may include subsidies)Market prices (may include subsidies) Indirect estimates (contingent valuation, travel cost method).Indirect estimates (contingent valuation, travel cost method). Provides an economic or monetary value for criteria (e.g., as the basis for cost-benefit analysis). Economic assessment or monetization of the costs and benefits of the supply and use of water, water quality, and all instruments and measures. Can be based on: Market prices (may include subsidies)Market prices (may include subsidies) Indirect estimates (contingent valuation, travel cost method).Indirect estimates (contingent valuation, travel cost method).

49. © K.Fedra 2007 49 Zero-sum games: Assumes finite resources independent of strategies Game only allocates resources between players Sum of all players gains is zero Zero sum games describe HOW TO DIVIDE THE CAKE Assumes finite resources independent of strategies Game only allocates resources between players Sum of all players gains is zero Zero sum games describe HOW TO DIVIDE THE CAKE