DSS for Integrated Water Resources Management (IWRM) Simulation based MC optimization DDr. Kurt Fedra ESS GmbH, Austria Environmental Software & Services A-2352 Gumpoldskirchen DDr. Kurt Fedra ESS GmbH, Austria Environmental Software & Services A-2352 Gumpoldskirchen

2 River basin scale perspective EU Directive 2000/60/EC Basic principle: Conservation laws (mass, energy) are used to describe dynamic water budgets. Basic unit: hydrographic catchment or river basin, naturally bounded, well defined. Complications: inter-basin transfersinter-basin transfers aquifer across catchment boundariesaquifer across catchment boundaries mismatch with administrative unitsmismatch with administrative units

3 Water resource MC optimization Design or select policies to Maximize the benefits Minimize the costs Using multiple criteria in parallel: 1.physical/hydrological 2.monetary (socio-economic) 3.environmental Economic (participatory) approach: Assumes that (rational) individuals maximize welfare (individual and collective utility) as they conceive it, forward looking and consistently. G.Becker, 1993 Design or select policies to Maximize the benefits Minimize the costs Using multiple criteria in parallel: 1.physical/hydrological 2.monetary (socio-economic) 3.environmental Economic (participatory) approach: Assumes that (rational) individuals maximize welfare (individual and collective utility) as they conceive it, forward looking and consistently. G.Becker, 1993

4 In summary: Simulation-based optimization can identify possibilities for considerable INCREASES OF NET BENEFITS (improvements in several criteria) Globally (entire basin) Sectorally (e.g., irrigated agriculture) Geographically (administrative units or hydrographically by sub-basin) Mechanisms to distribute benefits equitably lead to win-win solutions Simulation-based optimization can identify possibilities for considerable INCREASES OF NET BENEFITS (improvements in several criteria) Globally (entire basin) Sectorally (e.g., irrigated agriculture) Geographically (administrative units or hydrographically by sub-basin) Mechanisms to distribute benefits equitably lead to win-win solutions

5 Multi criteria optimization: 1.Model the behavior of the system (river basin) in sufficient detail (distributed, dynamic, non-linear) to generate meaningful criteria: dynamic topological (network) water resources model with daily time- step, coupled water quality model 1.Model the behavior of the system (river basin) in sufficient detail (distributed, dynamic, non-linear) to generate meaningful criteria: dynamic topological (network) water resources model with daily time- step, coupled water quality model

6 Multi criteria optimization: 1.sufficient detail: all major actors or stakeholder find themselves represented 2.meaningful criteria: all criteria are relevant for the decision, measurable (quantified, scalar or at least ordinal) 1.sufficient detail: all major actors or stakeholder find themselves represented 2.meaningful criteria: all criteria are relevant for the decision, measurable (quantified, scalar or at least ordinal)

7 A topological model: nodes and reaches A river basin is represented as a set of nodes and reaches connecting them. NODES produce, consume, store, and change water quality; REACHES transport it between nodes AQUIFERS underlying the network Costs to supply water, damages, shortfall Benefits from satisfied demand, compliance A river basin is represented as a set of nodes and reaches connecting them. NODES produce, consume, store, and change water quality; REACHES transport it between nodes AQUIFERS underlying the network Costs to supply water, damages, shortfall Benefits from satisfied demand, compliance

8 Gediz River basin, Turkey: Semi-arid, 18,000 km2 1,600,000 people Rapid demographic and economic growth, supports the city of Izmir, drains into the Bay of Izmir, shallow, enclosed, vulnerable Recurrent droughts High level of pollution Dominant agricultural water use Water fully allocated Overexploitation of groundwater Semi-arid, 18,000 km2 1,600,000 people Rapid demographic and economic growth, supports the city of Izmir, drains into the Bay of Izmir, shallow, enclosed, vulnerable Recurrent droughts High level of pollution Dominant agricultural water use Water fully allocated Overexploitation of groundwater

9 Gediz River Basin:

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11 Model structure: NODES have type specific attributes and complex, dynamic behavior Different simulation models describe: Behavior of individual nodes Behavior of the network Makes it possible to cascade models: rainfall-runoff  water resources  water quality irrigation  NODES have type specific attributes and complex, dynamic behavior Different simulation models describe: Behavior of individual nodes Behavior of the network Makes it possible to cascade models: rainfall-runoff  water resources  water quality irrigation 

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13 A topological model: nodes and reaches START water input, required start point generic, well, sping, subcatchment, transfer, desalination ENDexport from the network, required endpoint for a model CONFLUENCE combines two inflows, passive GEOMETRYauxiliar node, no hydraulic function CONTROLmonitors and records flow, compares with targets passiv, MINtarget, MAXtarget, combined, calibration START water input, required start point generic, well, sping, subcatchment, transfer, desalination ENDexport from the network, required endpoint for a model CONFLUENCE combines two inflows, passive GEOMETRYauxiliar node, no hydraulic function CONTROLmonitors and records flow, compares with targets passiv, MINtarget, MAXtarget, combined, calibration

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15 A topological model: nodes and reaches DEMANDwater demand and use, losses and consumptive use generic, municipal, touristic, industrial, light industry, commercial, services, irrigation, agriculture RESERVOIRreservoirs with dams, and natural lakes DIVERSIONdiversion or bifurcation node, splits a reach into two branches OR extracts water from the main stream RECHARGEadds water to an aquifer TREATMENT affects only water quality DEMANDwater demand and use, losses and consumptive use generic, municipal, touristic, industrial, light industry, commercial, services, irrigation, agriculture RESERVOIRreservoirs with dams, and natural lakes DIVERSIONdiversion or bifurcation node, splits a reach into two branches OR extracts water from the main stream RECHARGEadds water to an aquifer TREATMENT affects only water quality

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17 A topological model: nodes and reaches AQUIFERS one or more linked groundwater bodies underlying NODES and REACHES, connected through: Sources (springs, wells) Sinks (losses, seepage) Interaction with REACHES Recharge: –Natural (rainfall, temperature, land cover) –Artificial (recharge wells) AQUIFERS one or more linked groundwater bodies underlying NODES and REACHES, connected through: Sources (springs, wells) Sinks (losses, seepage) Interaction with REACHES Recharge: –Natural (rainfall, temperature, land cover) –Artificial (recharge wells)

18 Benefits and Costs Nodes are described by cost functions: –Investment –Operating cost (OMR) –Life time of project/structure –Discount rates Benefits per unit water supplied and used. Computation of NPV (net present value) for comparison of scenarios

19 Benefits and Costs Direct monetary: Investment, operations, damage, producer benefits (irrigation)Investment, operations, damage, producer benefits (irrigation) Non-monetary: based on (contingent) valuation (hypothetical markets): Shortfall costs, penalties, benefits of compliance (in stream use, environmental use)Shortfall costs, penalties, benefits of compliance (in stream use, environmental use)

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23 Process representation: Sources of water, inputs: START NODES –Tributaries (simulated by the rainfall-runoff model), –Wells and well fields, –Inter basin transfer, –Desalination, –Water harvesting, –Direct rainfall (reservoirs, reaches) –Lateral inflow to reaches –Groundwater recharge Sources of water, inputs: START NODES –Tributaries (simulated by the rainfall-runoff model), –Wells and well fields, –Inter basin transfer, –Desalination, –Water harvesting, –Direct rainfall (reservoirs, reaches) –Lateral inflow to reaches –Groundwater recharge

24 Process representation: Water use, DEMAND NODES Irrigation districts, settlements, industries, wetlands Conveiance losses Consumptive use Evaporation and seepage Bypass or spill Return flow losses Water use, DEMAND NODES Irrigation districts, settlements, industries, wetlands Conveiance losses Consumptive use Evaporation and seepage Bypass or spill Return flow losses

25 Process representation: Water storage, RESERVOIR NODES Evaporation and seepage Direct precipitation Local catchment Dynamic storage Release Spillage Water storage, RESERVOIR NODES Evaporation and seepage Direct precipitation Local catchment Dynamic storage Release Spillage

26 Process representation: Water allocation, DIVERSION NODES Constant ratio (fixed weir) or controlled diversion (target) flow, possibly demand driven (real-time control) Allocation priorities (downstream requirements) Water allocation, DIVERSION NODES Constant ratio (fixed weir) or controlled diversion (target) flow, possibly demand driven (real-time control) Allocation priorities (downstream requirements)

27 Process representation: Flow constraints, CONTROL NODES Constant or dynamic constraints: Minimum flow requirements Maximum flow: flooding (non-linear damage) Flow constraints, CONTROL NODES Constant or dynamic constraints: Minimum flow requirements Maximum flow: flooding (non-linear damage)

28 Process representation: Groundwater, AQUIFERS Natural recharge, evaporative (through soil moisture) losses, deep percolation Artificial recharge (recharge nodes) Recharge from all seepage losses Provide input to start nodes:wells (pumped) or natural springs Groundwater, AQUIFERS Natural recharge, evaporative (through soil moisture) losses, deep percolation Artificial recharge (recharge nodes) Recharge from all seepage losses Provide input to start nodes:wells (pumped) or natural springs

29 Process representation: Water flow, REACHES Simple routing (Muskingum, variable time step) Lateral inflow Direct precipitation Evaporation Seepage (groundwater exchange) Water flow, REACHES Simple routing (Muskingum, variable time step) Lateral inflow Direct precipitation Evaporation Seepage (groundwater exchange)

30 Optimization: STEP 1 CONSTRAINTS: Specify an acceptable system performance in terms of lower and upper bounds of criteria: Minimum amount of water available Maximum costs acceptable Minimum Benefits expected CONSTRAINTS: Specify an acceptable system performance in terms of lower and upper bounds of criteria: Minimum amount of water available Maximum costs acceptable Minimum Benefits expected

31 Water resources systems optimization: Definition of optimality: Acceptability, satisficing Requires a participatory approach: –Identification and involvement of major actors, stakeholders –Shared information basis –Easy access, intuitive understanding – Web based, local workshops Definition of optimality: Acceptability, satisficing Requires a participatory approach: –Identification and involvement of major actors, stakeholders –Shared information basis –Easy access, intuitive understanding – Web based, local workshops

32 Water resources systems optimization: Acceptability, satisficing: Easier for stakeholders to define several fixed targets as constraints than multiple objectives and trade offs, weights, preferences, etc. Acceptability, satisficing: Easier for stakeholders to define several fixed targets as constraints than multiple objectives and trade offs, weights, preferences, etc.

33 System performance criteria: Supply/Demand, availability Reliability of Supply (%) Efficiencies (water, economic) Sustainability (content change) Water quality Costs and benefits Supply/Demand, availability Reliability of Supply (%) Efficiencies (water, economic) Sustainability (content change) Water quality Costs and benefits

34 System performance criteria: Diversion performance (%): the percentage of all "events" (summed over all diversion nodes and days) where the diversion target can be met; Allocation efficiency (%): the percentage of supply diverted to supply nodes that matches demands; all supply beyond demand is "wasted" and decreases allocation efficiency, Diversion performance (%): the percentage of all "events" (summed over all diversion nodes and days) where the diversion target can be met; Allocation efficiency (%): the percentage of supply diverted to supply nodes that matches demands; all supply beyond demand is "wasted" and decreases allocation efficiency,

35 System performance criteria: Unallocated (%): the total amount of water that is unallocated at reservoirs (spilled), diversions (beyond diversion and downstream targets), control nodes (exceeding a minimum flow constraint), expressed as a percentage of the total amount of water the passes through these nodes. Water Shortfall: the total amount of water "missing" from the total demand, summed overall all reservoir, demand, diversion, recharge and control nodes, over all days, expressed as a percentage of all stated "demands" including releases, diversions, and in-stream flow constraints. Unallocated (%): the total amount of water that is unallocated at reservoirs (spilled), diversions (beyond diversion and downstream targets), control nodes (exceeding a minimum flow constraint), expressed as a percentage of the total amount of water the passes through these nodes. Water Shortfall: the total amount of water "missing" from the total demand, summed overall all reservoir, demand, diversion, recharge and control nodes, over all days, expressed as a percentage of all stated "demands" including releases, diversions, and in-stream flow constraints.

36 System performance criteria: Content Change: change of water value, expressed as a percentage from the initial state at the beginning of the current (water) simulation year: measure of sustainability Flooding days: days of flooding; a flood occurs if at any control node the flow exceeds a maximum flow constraint. Flooding extent: the percentage of all "floods" (summed over all control nodes with a maximum flow constraint and days) as a percentage of all "events"; Content Change: change of water value, expressed as a percentage from the initial state at the beginning of the current (water) simulation year: measure of sustainability Flooding days: days of flooding; a flood occurs if at any control node the flow exceeds a maximum flow constraint. Flooding extent: the percentage of all "floods" (summed over all control nodes with a maximum flow constraint and days) as a percentage of all "events";

37 System performance criteria: Economic efficiency: the total benefit per water available/supplied in €/m3 Economic efficiency, direct: the direct, monetary benefit per unit water available/supplied Economic efficiency: the total benefit per water available/supplied in €/m3 Economic efficiency, direct: the direct, monetary benefit per unit water available/supplied

38 System performance criteria: Benefit/Cost: ratio of all benefits divided by all costs accounted, including non- tangible elements and penalties. Benefit/Cost, direct: ratio of all direct monetary benefits over all direct monetary costs. Net benefit: Total benefit minus total cost, per capita. Total Benefit: Sum of all benefits, per capita. Benefit/Cost: ratio of all benefits divided by all costs accounted, including non- tangible elements and penalties. Benefit/Cost, direct: ratio of all direct monetary benefits over all direct monetary costs. Net benefit: Total benefit minus total cost, per capita. Total Benefit: Sum of all benefits, per capita.

39 System performance criteria: Total Cost: Sum of all costs, per capita. Direct net benefits: Sum of all direct monetary benefits minus sum of all direct monetary costs, per capita. Direct benefit: Sum of all direct monetary benefits, per capita. Total Cost, direct.: Sum of all direct monetary costs, per capita. Total Cost: Sum of all costs, per capita. Direct net benefits: Sum of all direct monetary benefits minus sum of all direct monetary costs, per capita. Direct benefit: Sum of all direct monetary benefits, per capita. Total Cost, direct.: Sum of all direct monetary costs, per capita.

40 System performance criteria: Water Cost: Total cost of water, per m3: Sum of all costs divided by the total amount of water supplied against demands at demand nodes, (diversions, control nodes) Water Cost, direct: Total direct monetary costs of water: as above, but considering only direct monetary costs. Water Cost: Total cost of water, per m3: Sum of all costs divided by the total amount of water supplied against demands at demand nodes, (diversions, control nodes) Water Cost, direct: Total direct monetary costs of water: as above, but considering only direct monetary costs.

41 Optimization STEP 1: CONSTRAINTS: GLOBAL: apply to some general, aggregate measure for the entire basin SECTORAL: apply to a sector like agriculture industry, domestic, environment only LOCAL (node specific): At LOCATION node FROM day – TO day CONCEPT (flow, cost, benefit, ratio) Must be between MIN – MAX CONSTRAINTS: GLOBAL: apply to some general, aggregate measure for the entire basin SECTORAL: apply to a sector like agriculture industry, domestic, environment only LOCAL (node specific): At LOCATION node FROM day – TO day CONCEPT (flow, cost, benefit, ratio) Must be between MIN – MAX

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44 Optimization STEP 2: INSTRUMENTS: 1.Select instruments for different NODE CLASSES (demand, supply, reservoir, diversion) from the data base; 2.Assign to specific NODES 3.Configure the specific techno-economic data (efficiency, economics) INSTRUMENTS: 1.Select instruments for different NODE CLASSES (demand, supply, reservoir, diversion) from the data base; 2.Assign to specific NODES 3.Configure the specific techno-economic data (efficiency, economics)

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46 Optimization STEP 3: How it works: the MC optimization 1.Selects COMBINATIONS of INSTRUMENTS, starting with the a priori weights/probabilities; 2.Applies them to the base scenario, as incremental changes 3.Evaluates the consequences (CRITERIA) 4.Compares with all the CONSTRAINTS How it works: the MC optimization 1.Selects COMBINATIONS of INSTRUMENTS, starting with the a priori weights/probabilities; 2.Applies them to the base scenario, as incremental changes 3.Evaluates the consequences (CRITERIA) 4.Compares with all the CONSTRAINTS

47 Optimization STEP 3: 5.Rejects INFEASIBLE solutions 6.Retains FEASIBLE solutions as the starting point for new trials, “learning” to improve the CRITERIA values (genetic algorithms, adaptive heuristics) 7.Continues the trials until: a.The maximum number of trials has been reached ( ,000,000); b.The required number of feasible solutions has been found 5.Rejects INFEASIBLE solutions 6.Retains FEASIBLE solutions as the starting point for new trials, “learning” to improve the CRITERIA values (genetic algorithms, adaptive heuristics) 7.Continues the trials until: a.The maximum number of trials has been reached ( ,000,000); b.The required number of feasible solutions has been found

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49 Optimization STEP 4: 1.Export the set of FEASIBLE solutions to the discrete multi-criteria DSS tool (DMC) 2.Rank solutions by individual criteria 3.Plot solutions on plains of two criteria 4.Manipulate PREFERENCES (set of criteria, constraints, reference point) to obtain a preferred (compromise) solution 5.Involve all stakeholders where feasible. 1.Export the set of FEASIBLE solutions to the discrete multi-criteria DSS tool (DMC) 2.Rank solutions by individual criteria 3.Plot solutions on plains of two criteria 4.Manipulate PREFERENCES (set of criteria, constraints, reference point) to obtain a preferred (compromise) solution 5.Involve all stakeholders where feasible.

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Decision Support (multi-attribute) Reference point approach: nadirnadir utopiautopia A1 A2 A3 A4 better efficientpoint criterion 1 criterion 2 A5 dominated A6

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56 Finding a compromise solution: Direct stakeholder involvement: Add or delete criteria Introduce (secondary) constraints Change the reference point: default is UTOPIA

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59 Optimization STEP 5: 1.Re-introduce the efficient solution to the simulation models, re-run 2.Test all details of the systems behaviour and performance to re-assure all stakeholders that THEIR specific requirements are being met; 3.Obtain agreement and consensus on the distribution/allocation of benefits: document the agreement, and have everybody sign on the dotted line…. 1.Re-introduce the efficient solution to the simulation models, re-run 2.Test all details of the systems behaviour and performance to re-assure all stakeholders that THEIR specific requirements are being met; 3.Obtain agreement and consensus on the distribution/allocation of benefits: document the agreement, and have everybody sign on the dotted line….

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63 In summary: Simulation-based optimization can identify possibilities for considerable INCREASES OF NET BENEFITS (improvements in several criteria) Globally (entire basin) Sectorally (e.g., irrigated agriculture) Geographically (administrative units or hydrographically by sub-basin) Mechanisms to distribute benefits equitably lead to win-win solutions Simulation-based optimization can identify possibilities for considerable INCREASES OF NET BENEFITS (improvements in several criteria) Globally (entire basin) Sectorally (e.g., irrigated agriculture) Geographically (administrative units or hydrographically by sub-basin) Mechanisms to distribute benefits equitably lead to win-win solutions