k.fedra ‘05 1 water resources simulation and optimization: a web based approach mso august 2005,...

K.Fedra ‘051

Water Resources Simulation Water Resources Simulation and Optimization: a web and Optimization: a web

based approachbased approach

MSO August 2005, ArubaMSO August 2005, Aruba

Water Resources Simulation Water Resources Simulation and Optimization: a web and Optimization: a web

based approachbased approach

MSO August 2005, ArubaMSO August 2005, Aruba

DDr. Kurt Fedra ESS GmbH, Austriakurt@ess.co.at http://www.ess.co.at DDr. Kurt Fedra ESS GmbH, Austriakurt@ess.co.at http://www.ess.co.at

K.Fedra ‘052

Water resources management:Water resources management:Water resources management:Water resources management:

From principles to procedures and tools

How to define optimality ?

How to explore, compare options ?

How to agree on solutions ?

Optimality is not an operational principle easily implemented

From principles to procedures and tools

How to define optimality ?

How to explore, compare options ?

How to agree on solutions ?

Optimality is not an operational principle easily implemented

K.Fedra ‘053

Water resources management:Water resources management:Water resources management:Water resources management:

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

K.Fedra ‘054

OPTIMA: OPTIMA: INCO-MPCINCO-MPC

Ongoing applications, EU supported:

• INCO-MED SMART (2002-2005)– Turkey, Lebanon, Jordan, Egypt, Tunisia;

Italy, France, Portugal, Austria

• INCO-MPC OPTIMA (2004-2007)– Turkey, Lebanon, Jordan, Palestine,

Tunisia, Morocco, Cyprus; Italy, Greece, Malta, Austria

Ongoing applications, EU supported:

• INCO-MED SMART (2002-2005)– Turkey, Lebanon, Jordan, Egypt, Tunisia;

Italy, France, Portugal, Austria

• INCO-MPC OPTIMA (2004-2007)– Turkey, Lebanon, Jordan, Palestine,

Tunisia, Morocco, Cyprus; Italy, Greece, Malta, Austria

K.Fedra ‘055

OPTIMA:OPTIMA:OPTIMA:OPTIMA:

Project Project started July 2004 (3 years):started July 2004 (3 years):The various data sets and scenarios form the The various data sets and scenarios form the

basis for the optimization/basin master plans:basis for the optimization/basin master plans:METHODMETHOD::Monte-Carlo, genetic programming, discrete Monte-Carlo, genetic programming, discrete

multi-criteria (reference point) optimization;multi-criteria (reference point) optimization;OBJECTIVESOBJECTIVES include: include:

maximize demand satisfied;maximize demand satisfied;maximize reliability;maximize reliability;maximize water based net revenues;maximize water based net revenues;minimize environmental impacts (env. water minimize environmental impacts (env. water

demand or minimal flow, WQ standarddemand or minimal flow, WQ standard violations) violations)

Project Project started July 2004 (3 years):started July 2004 (3 years):The various data sets and scenarios form the The various data sets and scenarios form the

basis for the optimization/basin master plans:basis for the optimization/basin master plans:METHODMETHOD::Monte-Carlo, genetic programming, discrete Monte-Carlo, genetic programming, discrete

multi-criteria (reference point) optimization;multi-criteria (reference point) optimization;OBJECTIVESOBJECTIVES include: include:

maximize demand satisfied;maximize demand satisfied;maximize reliability;maximize reliability;maximize water based net revenues;maximize water based net revenues;minimize environmental impacts (env. water minimize environmental impacts (env. water

demand or minimal flow, WQ standarddemand or minimal flow, WQ standard violations) violations)

K.Fedra ‘056

Methodology:Methodology:• Analyze socio-economic and regulatory

framework, multiple objectives (issues questionnaire)

• WaterWare (river basin) model including economic assessment

• 7 parallel case studies, end user involvement for optimization objectives and criteria (reference point analysis)

• Comparative analysis, best practice

• Analyze socio-economic and regulatory framework, multiple objectives (issues questionnaire)

• WaterWare (river basin) model including economic assessment

• 7 parallel case studies, end user involvement for optimization objectives and criteria (reference point analysis)

• Comparative analysis, best practice

K.Fedra ‘057

Project web site:Project web site:Project web site:Project web site:

• http://www.ess.co.at/SMART/

• http://www.ess.co.at/OPTIMA/

• http://www.ess.co.at/WATERWARE/

Including on-line GIS, data bases and interactive modeling tools

• http://www.ess.co.at/SMART/

• http://www.ess.co.at/OPTIMA/

• http://www.ess.co.at/WATERWARE/

Including on-line GIS, data bases and interactive modeling tools

K.Fedra ‘058

Components and toolsComponents and toolsComponents and toolsComponents and tools

Related on-line tools:Related on-line tools:•Stakeholders data base: Stakeholders data base:

register your institution!register your institution!•Water Issues questionnaire Water Issues questionnaire

(benchmarking for river basins)(benchmarking for river basins)

describe your basin !describe your basin !

Related on-line tools:Related on-line tools:•Stakeholders data base: Stakeholders data base:

register your institution!register your institution!•Water Issues questionnaire Water Issues questionnaire

(benchmarking for river basins)(benchmarking for river basins)

describe your basin !describe your basin !

K.Fedra ‘059

Purpose and objectives:Purpose and objectives:Purpose and objectives:Purpose and objectives:

Scientifically based contributions to

• Water Resources Management through improved efficiency and performance

• the policy and decision making processes (participatory, empowerment of stakeholders)

Scientifically based contributions to

• Water Resources Management through improved efficiency and performance

• the policy and decision making processes (participatory, empowerment of stakeholders)

K.Fedra ‘0510

Optimality and Sustainability :Optimality and Sustainability :Optimality and Sustainability :Optimality and Sustainability :

1. Economic efficiency (“true cost”, maximize economic benefits, minimize costs)

2. Environmental compatibility (meeting standards, protect wetlands, sensitive areas, minimize env. costs)

3. Equity (intra- and intergenerational)

MEET THE CONSTRAINTSMEET THE CONSTRAINTS

1. Economic efficiency (“true cost”, maximize economic benefits, minimize costs)

2. Environmental compatibility (meeting standards, protect wetlands, sensitive areas, minimize env. costs)

3. Equity (intra- and intergenerational)

MEET THE CONSTRAINTSMEET THE CONSTRAINTS

K.Fedra ‘0511

Mediterranean region:Mediterranean region:Mediterranean region:Mediterranean region:

The projections of water available per person are dropping steeply for most countries:

Average values (Wagner, 2001) are moving to 1,000 m3/person and year or below (Southern and Eastern Mediterranean)

- based on demographic projections

- assumptions on per capita use

The projections of water available per person are dropping steeply for most countries:

Average values (Wagner, 2001) are moving to 1,000 m3/person and year or below (Southern and Eastern Mediterranean)

- based on demographic projections

- assumptions on per capita use

K.Fedra ‘0512

Mediterranean region:Mediterranean region:Mediterranean region:Mediterranean region:Coastal zone development and

urbanization increase demand for high-quality drinking water;

Tourism with very high per capita demands generates unfavorable demand patterns (summer peak)

But agriculture is still the major consumer of water (largely due to inefficient irrigation technologies)

Coastal zone development and urbanization increase demand for high-quality drinking water;

Tourism with very high per capita demands generates unfavorable demand patterns (summer peak)

But agriculture is still the major consumer of water (largely due to inefficient irrigation technologies)

K.Fedra ‘0513

Development Scenarios:Development Scenarios:Development Scenarios:Development Scenarios:1. Baseline (status quo for calibration)

2. Business as usual (naïve trend extrapolation)

3. Pessimistic (everything “bad” will happen)

4. Optimistic (all the good things …)

5. Specific existing plans of structural change, legislation, etc.

1. Baseline (status quo for calibration)

2. Business as usual (naïve trend extrapolation)

3. Pessimistic (everything “bad” will happen)

4. Optimistic (all the good things …)

5. Specific existing plans of structural change, legislation, etc.

K.Fedra ‘0514

Scenario analysis:Scenario analysis:Scenario analysis:Scenario analysis:

Objective is NOT to forecast a most likely future,

but to explore the range of possibilities (bound solutions, define nadir and utopia to normalize results as % achievements, relative change)

Objective is NOT to forecast a most likely future,

but to explore the range of possibilities (bound solutions, define nadir and utopia to normalize results as % achievements, relative change)

K.Fedra ‘0515

Scenarios:Scenarios:Scenarios:Scenarios:1. Demographic development (population growth,

migration, urbanization <== land use change)

2. Economic development (sectoral growth, tourism)

3. Technological development (specific water use efficiencies)

4. Institutional change (regulations, enforcement)

5. Climate change (decreased means, increased variability of precipitation, temperature increase)

1. Demographic development (population growth, migration, urbanization <== land use change)

2. Economic development (sectoral growth, tourism)

3. Technological development (specific water use efficiencies)

4. Institutional change (regulations, enforcement)

5. Climate change (decreased means, increased variability of precipitation, temperature increase)

K.Fedra ‘0516

From scenarios to optimizationFrom scenarios to optimizationFrom scenarios to optimizationFrom scenarios to optimization1. Define a most likely scenario

2. Define a set of alternative options:• Structurally (reservoirs)

• Supply management (alternative sources)

• Demand management (pricing)

• Water technologies (efficiencies)

with their investment operating costs,

3. Find efficient combinations (heuristics, genetic algorithms)

4. Calculate system performance:

find feasible solutions

1. Define a most likely scenario

2. Define a set of alternative options:• Structurally (reservoirs)

• Supply management (alternative sources)

• Demand management (pricing)

• Water technologies (efficiencies)

with their investment operating costs,

3. Find efficient combinations (heuristics, genetic algorithms)

4. Calculate system performance:

find feasible solutions

K.Fedra ‘0517

System performance:System performance:System performance:System performance:Derived from the model results:• Demand/Supply balance (by sector

incl. environmental water use)• Reliability of Supply (% mass, time)• Efficiency (benefits/unit water used)• Cost/benefit ratios (NPV), penalties

• Water quality (in stream)

Derived from the model results:• Demand/Supply balance (by sector

incl. environmental water use)• Reliability of Supply (% mass, time)• Efficiency (benefits/unit water used)• Cost/benefit ratios (NPV), penalties

• Water quality (in stream)

K.Fedra ‘0518

WATERWARE WATERWARE (EUREKA 486)(EUREKA 486)WATERWARE WATERWARE (EUREKA 486)(EUREKA 486)

Water resources management Water resources management information system:information system:

• River basin orientedRiver basin oriented• Integrated data managementIntegrated data management• Cascading models for supply-demand Cascading models for supply-demand

pattern simulation incl. qualitypattern simulation incl. quality• Management oriented (allocation, Management oriented (allocation,

efficiency)efficiency)• Use of economic criteriaUse of economic criteriahttp://www.ess.co.at/WATERWARE/http://www.ess.co.at/WATERWARE/

Water resources management Water resources management information system:information system:

• River basin orientedRiver basin oriented• Integrated data managementIntegrated data management• Cascading models for supply-demand Cascading models for supply-demand

pattern simulation incl. qualitypattern simulation incl. quality• Management oriented (allocation, Management oriented (allocation,

efficiency)efficiency)• Use of economic criteriaUse of economic criteriahttp://www.ess.co.at/WATERWARE/http://www.ess.co.at/WATERWARE/

K.Fedra ‘0519

Simulation models:Simulation models:Linked set of models:• Rainfall-runoff for ungaged

catchments• Irrigation water demand• Water resources (daily water

budgets)• Water quality (basin wide)• Water quality (local, near field)• Groundwater flow and transport (2D)

Linked set of models:• Rainfall-runoff for ungaged

catchments• Irrigation water demand• Water resources (daily water

budgets)• Water quality (basin wide)• Water quality (local, near field)• Groundwater flow and transport (2D)

K.Fedra ‘0520

Object types:Object types:

Monitoring stationMonitoring station

K.Fedra ‘0521

Object types:Object types:

Monitoring stationMonitoring station

K.Fedra ‘0522

Object types:Object types:

K.Fedra ‘0523

Object type:Object type:

ReservoirReservoir

K.Fedra ‘0524

Simulation models:Simulation models:

K.Fedra ‘0525

Crop data base:Crop data base:Crop data base:Crop data base:

K.Fedra ‘0526

Crop data base:Crop data base:Crop data base:Crop data base:

K.Fedra ‘0527

Simulation models:Simulation models:

K.Fedra ‘0528

Simulation models:Simulation models:

K.Fedra ‘0529

Simulation models:Simulation models:

K.Fedra ‘0530

Simulation models:Simulation models:

K.Fedra ‘0531

Simulation models:Simulation models:

K.Fedra ‘0532

K.Fedra ‘0533

Simulation models:Simulation models:

K.Fedra ‘0534

Simulation models:Simulation models:

K.Fedra ‘0535

Simulation models:Simulation models:

K.Fedra ‘0536

Simulation models:Simulation models:

K.Fedra ‘0537

Simulation models:Simulation models:

K.Fedra ‘0538

Simulation models:Simulation models:

K.Fedra ‘0539

Simulation models:Simulation models:

K.Fedra ‘0540

Simulation models:Simulation models:

K.Fedra ‘0541

Simulation models:Simulation models:

K.Fedra ‘0542

Evaluation:Evaluation:Evaluation:Evaluation:

Aggregated into Sustainability Indicators

1. Economic efficiency

2. Environmental compatibility

3. Equity (intra- and intergenerational)

Aggregated into Sustainability Indicators

1. Economic efficiency

2. Environmental compatibility

3. Equity (intra- and intergenerational)

K.Fedra ‘0543

Scenario Evaluation:Scenario Evaluation:Scenario Evaluation:Scenario Evaluation:

Aggregated into Aggregate Sustainability Indicators with RULES:

IF Sup/Dem >= 0.99

AND Reliability >> 85%

AND …….. == high/medium/low

THEN EEF = HIGH

Aggregated into Aggregate Sustainability Indicators with RULES:

IF Sup/Dem >= 0.99

AND Reliability >> 85%

AND …….. == high/medium/low

THEN EEF = HIGH

K.Fedra ‘0544

Evaluation:Evaluation:Evaluation:Evaluation:

Aggregated into Sustainability Index with RULES:

IF EEF == high (medium, low)

AND ENC == high (medium, low)

AND SEQ == high (medium, low)

THEN SUSTAINABILITY = HIGH

Aggregated into Sustainability Index with RULES:

IF EEF == high (medium, low)

AND ENC == high (medium, low)

AND SEQ == high (medium, low)

THEN SUSTAINABILITY = HIGH

K.Fedra ‘0545

Evaluation:Evaluation:Evaluation:Evaluation:

Evaluation process is open for inspection and participation: easy to understand and change RULES

OBJECTIVE: not to offer the ultimate assessment for SUSTAINABILITY, but a framework for structured discourse and user participation

Evaluation process is open for inspection and participation: easy to understand and change RULES

OBJECTIVE: not to offer the ultimate assessment for SUSTAINABILITY, but a framework for structured discourse and user participation

K.Fedra ‘0546

Decision Support:Decision Support:Decision Support:Decision Support:

Comparative analysis of feasible, non-dominated solutions in terms of the performance indicators;

Participatory approach:

Stake holders define criteria, objectives, constraints, and expectations

– DSS tool finds the nearest feasible solution in the set of alternatives.

Comparative analysis of feasible, non-dominated solutions in terms of the performance indicators;

Participatory approach:

Stake holders define criteria, objectives, constraints, and expectations

– DSS tool finds the nearest feasible solution in the set of alternatives.

K.Fedra ‘05

Decision Support Decision Support (multi-attribute)(multi-attribute)Decision Support Decision Support (multi-attribute)(multi-attribute)

Reference point approach:Reference point approach:

nadirnadirnadirnadir

utopiautopiautopiautopia

A1A1

A2A2

A3A3

A4A4

betterbetter

efficient efficient pointpoint

criterion 1criterion 1

crite

rion

2cr

iterio

n 2 A5A5

dominateddominated

A6A6

K.Fedra ‘0548

In summary:In summary:In summary:In summary:Problems are largely man made

Solutions involve valuation, trade off: subjective – political – choices;

NOT optimal, but acceptable to a majority

Democratic decision making processes

No single method, solutions need a well balanced combination of strategies and tools, based on preferences, believes, fears, and a little science.

Problems are largely man made

Solutions involve valuation, trade off: subjective – political – choices;

NOT optimal, but acceptable to a majority

Democratic decision making processes

No single method, solutions need a well balanced combination of strategies and tools, based on preferences, believes, fears, and a little science.