SMART INCO-MED kick-off meeting, January 5/ CEDARE, CAIRO DDr. Kurt Fedra ESS GmbH, Austria Environmental Software & Services A-2352 Gumpoldskirchen DDr. Kurt Fedra ESS GmbH, Austria Environmental Software & Services A-2352 Gumpoldskirchen

SMART: Project Overview 3 year duration to August 2005 Started: September 2002 Current PM: 5 9 partners and countries 12 work packages 5 case studies: TR,LB,JO,EG,TU 3 year duration to August 2005 Started: September 2002 Current PM: 5 9 partners and countries 12 work packages 5 case studies: TR,LB,JO,EG,TU

SMART: Objectives Develop policy guidelines for ICZM, emphasis on water resources Conflicting water use Resource economics Quantitative analysis using indicators, models, and expert systems Public information, Internet Case studies, collaborative network within and between countries Develop policy guidelines for ICZM, emphasis on water resources Conflicting water use Resource economics Quantitative analysis using indicators, models, and expert systems Public information, Internet Case studies, collaborative network within and between countries

SMART: Technical Objectives 1.Model integration, linkage through expert systems technology 2.Linkage of models and aggregate policy level indicators 3.Linkage of models and public information (Internet) 1.Model integration, linkage through expert systems technology 2.Linkage of models and aggregate policy level indicators 3.Linkage of models and public information (Internet)

SMART: Work Plan Phases 1.Requirements analysis, data availability, specifications 2.Data compilation, tool development 3.Parallel case studies 4.Comparative evaluation, dissemination. 1.Requirements analysis, data availability, specifications 2.Data compilation, tool development 3.Parallel case studies 4.Comparative evaluation, dissemination.

SMART: Milestones 1 PM 09 End of preparatory phase, first workshop 2 PM 12 Methods and tools prototypes ready, start of operational phase 3 PM 18 Case studies implemented, first results of scenario analysis 4 PM 24 Analysis and assessment phase initiated 5 PM 30 Case studies completed, final comparative analysis 6 PM36 Project and reporting completed 1 PM 09 End of preparatory phase, first workshop 2 PM 12 Methods and tools prototypes ready, start of operational phase 3 PM 18 Case studies implemented, first results of scenario analysis 4 PM 24 Analysis and assessment phase initiated 5 PM 30 Case studies completed, final comparative analysis 6 PM36 Project and reporting completed

SMART: work packages WP 0: Coordination and Administration ESS, PM 1-36 Communication: Mailing list: Web server Discussion board: Meetings: Output: Reports: Deliverables: Cost statements: Project Review: WP 0: Coordination and Administration ESS, PM 1-36 Communication: Mailing list: Web server Discussion board: Meetings: Output: Reports: Deliverables: Cost statements: Project Review:

SMART: work packages WP 01: Requirements and constraints analysis FEEM, PM 1-6 Deliverable due by February 2003 ! WP 01: Requirements and constraints analysis FEEM, PM 1-6 Deliverable due by February 2003 !

SMART: work packages WP 02: Socio-economic framework and guidelines UATLA, PM 3-12 WP 02: Socio-economic framework and guidelines UATLA, PM 3-12

SMART: work packages WP 03: Analytical tools, models SOGREAH, PM 3-18 Subtasks for TELEMAC WaterWare, XPS WP 03: Analytical tools, models SOGREAH, PM 3-18 Subtasks for TELEMAC WaterWare, XPS

SMART: work packages WP 04: Data compilation and analysis TR, PM 6-24 Includes parallel sub-tasks, one for each case study/country WP 04: Data compilation and analysis TR, PM 6-24 Includes parallel sub-tasks, one for each case study/country

SMART: WP04 1.Develop meta-data structure 2.Formats, technical specifications, 3.Coverage and resolution (space and time) 4.Develop checklists 5.Monitor compilation 6.Comparative analysis (completeness, consistency, plausibility) 1.Develop meta-data structure 2.Formats, technical specifications, 3.Coverage and resolution (space and time) 4.Develop checklists 5.Monitor compilation 6.Comparative analysis (completeness, consistency, plausibility)

SMART: WP04 Common data base or data repository; Extensive documentation ! Accessible from ftp server at project web site Selected data available with interactive on-line tools (e.g., hydro- meteorological time series data) Map server at CEDARE Common data base or data repository; Extensive documentation ! Accessible from ftp server at project web site Selected data available with interactive on-line tools (e.g., hydro- meteorological time series data) Map server at CEDARE

SMART: work packages WP 05 – 09 Case Studies Respective partner, PM 12-30, Overlaps with data compilation WP 05 – 09 Case Studies Respective partner, PM 12-30, Overlaps with data compilation

SMART: work packages WP 10: Comparative analysis FEEM, PM Requires input from all case studies WP 10: Comparative analysis FEEM, PM Requires input from all case studies

SMART: work packages WP 11: Dissemination and exploitation ESS, PM 3-36 WP 11: Dissemination and exploitation ESS, PM 3-36

SMART: time table

SMART

Water management must be analyzed in a broad systems context: – Socio-economic aspects (costs and benefits, jobs, institutions, regulations) – Environmental aspects (water quality, water allocation, alternative use) – Technological aspects (constraints,BAT, clean technologies, water efficiency, reuse and recycling) must be analyzed in a broad systems context: – Socio-economic aspects (costs and benefits, jobs, institutions, regulations) – Environmental aspects (water quality, water allocation, alternative use) – Technological aspects (constraints,BAT, clean technologies, water efficiency, reuse and recycling)

Water management Conflicting water use and changing, stochastic constraints Multiple criteria, conflicting objectivesMultiple criteria, conflicting objectives Industrial water management:Industrial water management: –Water demand Consumptive useConsumptive use Water pollutionWater pollution Conflicting water use and changing, stochastic constraints Multiple criteria, conflicting objectivesMultiple criteria, conflicting objectives Industrial water management:Industrial water management: –Water demand Consumptive useConsumptive use Water pollutionWater pollution

Environmental problems Water Management problems: –Not enough –Too much –At the wrong place –At the wrong time –Insufficient quality Problems of distribution of resources (clean air, water, land, biodiversity, …) Water Management problems: –Not enough –Too much –At the wrong place –At the wrong time –Insufficient quality Problems of distribution of resources (clean air, water, land, biodiversity, …)

Environmental problems result from the local or short-term optimization of resource management strategies, ignoring some externalities (side effects, costs to others). All life degrades its environment. All living systems have self-regulatory capabilities – within usually unknown limits. result from the local or short-term optimization of resource management strategies, ignoring some externalities (side effects, costs to others). All life degrades its environment. All living systems have self-regulatory capabilities – within usually unknown limits.

Environmental problems Increasing human population Increasing resource consumption – Energy – Materials – Space And potentially irreversible destruction of information (biodiversity) Increasing human population Increasing resource consumption – Energy – Materials – Space And potentially irreversible destruction of information (biodiversity)

Environmental problems Three laws of ecology: 1.Everything is connected to everything else; 2.Everything must go somewhere; 3.Nature knows best. Barry Commoner, Barry Commoner, The Closing Cycle. The Closing Cycle. Three laws of ecology: 1.Everything is connected to everything else; 2.Everything must go somewhere; 3.Nature knows best. Barry Commoner, Barry Commoner, The Closing Cycle. The Closing Cycle.

Environmental problems Root problem: Uncoupling of feedback loops (to obtain local or short-term benefits) Tragedy of the Commons (Hardin, 1968) Social costs (Kapp, 1979) Limits to Growth (Meadows et al., 1971) Malthus (1830) Root problem: Uncoupling of feedback loops (to obtain local or short-term benefits) Tragedy of the Commons (Hardin, 1968) Social costs (Kapp, 1979) Limits to Growth (Meadows et al., 1971) Malthus (1830)

Environmental problems IF: quantity or quality, spatial or temporal distribution of environmental resources do not match our needs or expectations: – Environment(objective reality) – Needs (objective-subjective reality) – Expectations(subjective reality) IF: quantity or quality, spatial or temporal distribution of environmental resources do not match our needs or expectations: – Environment(objective reality) – Needs (objective-subjective reality) – Expectations(subjective reality)

Regulatory response Laws and regulations: Emission control (water, air)Emission control (water, air) Product standards (fuel, engines, BAT)Product standards (fuel, engines, BAT) Permitting, zoningPermitting, zoning Monetary instruments:Monetary instruments: –Taxes (waste tax) –Subsidies (for mitigation) Laws and regulations: Emission control (water, air)Emission control (water, air) Product standards (fuel, engines, BAT)Product standards (fuel, engines, BAT) Permitting, zoningPermitting, zoning Monetary instruments:Monetary instruments: –Taxes (waste tax) –Subsidies (for mitigation)

Regulatory response Planning requirements: –Environmental impact assessment –Risk assessment Self-regulation: –ISO 14000, 9000 –EMAS, Eco-Audit –Responsible Care –Labeling (“biological” food) Planning requirements: –Environmental impact assessment –Risk assessment Self-regulation: –ISO 14000, 9000 –EMAS, Eco-Audit –Responsible Care –Labeling (“biological” food)

Water management problems are inherently multi-disciplinary: Hydrology, geology, climatology, geographyHydrology, geology, climatology, geography (Geo)physics, chemistry(Geo)physics, chemistry Biology, ecology, toxicologyBiology, ecology, toxicology Engineering, economicsEngineering, economics Psychology, sociologyPsychology, sociology Law, political sciencesLaw, political sciences are inherently multi-disciplinary: Hydrology, geology, climatology, geographyHydrology, geology, climatology, geography (Geo)physics, chemistry(Geo)physics, chemistry Biology, ecology, toxicologyBiology, ecology, toxicology Engineering, economicsEngineering, economics Psychology, sociologyPsychology, sociology Law, political sciencesLaw, political sciences

Water management problems are complex (many elements and interactions) dynamic (including delay, memory) dynamic (including delay, memory) spatially distributed (1, 1.5, 2 and 3D) spatially distributed (1, 1.5, 2 and 3D) non-linear (feedback, bifurcation, etc.) non-linear (feedback, bifurcation, etc.) involve large uncertainties in involve large uncertainties in - the physical domain - the physical domain - the socio-economic domain - the socio-economic domain involve multiple actors and stake holders involve multiple actors and stake holders are always multi-criteria, multi-objective are always multi-criteria, multi-objective are complex (many elements and interactions) dynamic (including delay, memory) dynamic (including delay, memory) spatially distributed (1, 1.5, 2 and 3D) spatially distributed (1, 1.5, 2 and 3D) non-linear (feedback, bifurcation, etc.) non-linear (feedback, bifurcation, etc.) involve large uncertainties in involve large uncertainties in - the physical domain - the physical domain - the socio-economic domain - the socio-economic domain involve multiple actors and stake holders involve multiple actors and stake holders are always multi-criteria, multi-objective are always multi-criteria, multi-objective

A river basin perspective: Water can easily be accounted for, a mass budget approach is feasible; The hydrographic unit of the catchment or river basin provides a naturally bounded well defined system; Conservation laws (mass, momentum) are used to describe dynamic water budgets.

A river basin perspective: Industrial water use is one of the demand nodes in a river basin network/graph: –Input nodes (sub-catchment, wells) –Domestic demand nodes –Agricultural demand nodes –Industrial demand nodes –Reservoirs, lakes –Structural components (confluence) connected by river reaches, canals

Water demand Depends on: Production volumeProduction volume Production technologyProduction technology Recycling strategiesRecycling strategies Demand has quantitative and qualitative elements, usually involves water treatment For a given cost of water, an optimal strategy can be computed based on investment cost, discount rate, and project lifetime (NPV)

Water demand intake Consumptive use recycling return flow Productionprocess

Consumptive use Water demand consists of: Consumptive useConsumptive use –Process water (integrated in the product) –Cooling (evaporation) Temporary use (return flow)Temporary use (return flow) But pollution can make the return flow unfit for subsequent use

Conflicting use More than 70% of water is generally used for agriculture (irrigation); Added value per unit water used in industry is usually between 50 to 100 times higher than in agriculture; Domestic use of water is comparatively small, but with high quality requirements and low elasticity. Environmental use (low flow, quality constraints).

Water Pollution 1.Industrial effluents incl.spills 2.Domestic sewage 3.Irrigation return flow Reduces potential utility for other down- stream usersReduces potential utility for other down- stream users Endangers biological systems (fish kill)Endangers biological systems (fish kill) May accumulate over long periods (chemical time bombs in sediments)May accumulate over long periods (chemical time bombs in sediments)

Waste management Waste allocation: Utilizes the self-purification potential of natural water bodies (BOD, biodegradable substances); But many toxics and heavy metals are persistent (long term cumulative damage, bioaccumulation, sediments).

WP 10: Comparative Analysis OBJECTIVES: The comparative analysis of the set of scenarios for each case/scenario.The comparative analysis of the set of scenarios for each case/scenario. The multi-criteria comparative analysis and selection of a non-dominated set of (Pareto optimal) alternatives The identification of the most promising scenario or small set of candidate scenarios from each test siteThe identification of the most promising scenario or small set of candidate scenarios from each test siteOBJECTIVES: The comparative analysis of the set of scenarios for each case/scenario.The comparative analysis of the set of scenarios for each case/scenario. The multi-criteria comparative analysis and selection of a non-dominated set of (Pareto optimal) alternatives The identification of the most promising scenario or small set of candidate scenarios from each test siteThe identification of the most promising scenario or small set of candidate scenarios from each test site

WP 10: Comparative Analysis Scenario comparison and multi-criteria analysis 1.Baseline Scenarios 2.Common Scenarios 3.Specific Scenarios ANY EXTERNAL CASES ? Scenario comparison and multi-criteria analysis 1.Baseline Scenarios 2.Common Scenarios 3.Specific Scenarios ANY EXTERNAL CASES ?

WP 10: Comparative Analysis METHOD: Discrete MCDiscrete MC Pareto set (half ordering)Pareto set (half ordering) Reference point approachReference point approach Set of criteria; define constraints and optimization direction for each; Optimum solution is the one nearest to reference point (utopia). Reference point location scales (criteria) dimensions. METHOD: Discrete MCDiscrete MC Pareto set (half ordering)Pareto set (half ordering) Reference point approachReference point approach Set of criteria; define constraints and optimization direction for each; Optimum solution is the one nearest to reference point (utopia). Reference point location scales (criteria) dimensions.

WP 10: Comparative Analysis SCENARIO: INPUT: Set of assumptions Decision and Policy variables Exogeneous variables OUTPUT: Set of indicators or criteria SCENARIO: INPUT: Set of assumptions Decision and Policy variables Exogeneous variables OUTPUT: Set of indicators or criteria

Decision Support Methodology Reference point approach: nadirnadir utopiautopia A1 A2 A3 A4 better efficientpoint criterion 1 criterion 2 A5 dominated A6

WP 10: Comparative Analysis METHOD: Modify the set of alternativesModify the set of alternatives Select criteriaSelect criteria Modify constraintsModify constraints Introduce reference pointIntroduce reference point Reduce dimensionalityReduce dimensionalityMETHOD: Modify the set of alternativesModify the set of alternatives Select criteriaSelect criteria Modify constraintsModify constraints Introduce reference pointIntroduce reference point Reduce dimensionalityReduce dimensionality

WP 10: Comparative Analysis METHOD: Combination of indicators by RULES or simple algorithms Quality, Quantity  STATUS Dynamically generated combined indicators can be used for the benchmarking METHOD: Combination of indicators by RULES or simple algorithms Quality, Quantity  STATUS Dynamically generated combined indicators can be used for the benchmarking

WP 10: Comparative Analysis RESULT: Ranking order of alternativesRanking order of alternatives Dominated/Pareto subsetsDominated/Pareto subsets Distance from reference point: nearest = bestDistance from reference point: nearest = bestRESULT: Ranking order of alternativesRanking order of alternatives Dominated/Pareto subsetsDominated/Pareto subsets Distance from reference point: nearest = bestDistance from reference point: nearest = best

WP 10: Comparative Analysis The vocabulary: List of indicatorsList of indicators Derived indicators (rule-based)Derived indicators (rule-based) Constraints based on: –Standards (WQ, reliability, ?) –Distributions (e.g., drop one SD) –Preferences The vocabulary: List of indicatorsList of indicators Derived indicators (rule-based)Derived indicators (rule-based) Constraints based on: –Standards (WQ, reliability, ?) –Distributions (e.g., drop one SD) –Preferences

WP 10: Comparative Analysis Inidicator definitions: 1.Name, alias 2.Unit 3.Allowable range with symbolic labels 4.Question/definition 5.Inference Rules Inidicator definitions: 1.Name, alias 2.Unit 3.Allowable range with symbolic labels 4.Question/definition 5.Inference Rules

WP 10: Comparative Analysis Reliability A: REL U: % V: Low[ 0, 10, 20] V: Medium[21, 25, 40] V: High[41, 50,100] Q: What is average reliability of meeting water demands on a daily basis ? Reliability A: REL U: % V: Low[ 0, 10, 20] V: Medium[21, 25, 40] V: High[41, 50,100] Q: What is average reliability of meeting water demands on a daily basis ?

WP 10: Comparative Analysis RULES: IF condition AND/OR condition THEN conclusion Condition: Descriptor Operator Value Quality == high RULES: IF condition AND/OR condition THEN conclusion Condition: Descriptor Operator Value Quality == high

WP 10: Comparative Analysis RULES: IF condition AND/OR condition THEN conclusion Condition: Descriptor Operator Value Density ==,,!=,……. high Conclusion: Descriptor Assignment Value Density = high RULES: IF condition AND/OR condition THEN conclusion Condition: Descriptor Operator Value Density ==,,!=,……. high Conclusion: Descriptor Assignment Value Density = high

WP 10: Comparative Analysis RULES: IF quantity == sufficient AND quality == sufficient THEN status = very_good Condition: Descriptor Operator Value Reliability ==,,!=,……. high Conclusion: Descriptor Assignment Value Reliability = high Reliability = highRULES: IF quantity == sufficient AND quality == sufficient THEN status = very_good Condition: Descriptor Operator Value Reliability ==,,!=,……. high Conclusion: Descriptor Assignment Value Reliability = high Reliability = high

WP 11: Dissemination Web siteWeb site Meeting, conferences, scientific and technical literatureMeeting, conferences, scientific and technical literature Local workshopsLocal workshops Web siteWeb site Meeting, conferences, scientific and technical literatureMeeting, conferences, scientific and technical literature Local workshopsLocal workshops

WP 11: Dissemination Web site, other material ?Web site, other material ? Meeting, conferences, scientific and technical literatureMeeting, conferences, scientific and technical literature Local dissemination workshops (language)Local dissemination workshops (language) SMART: the book ?SMART: the book ? Web site, other material ?Web site, other material ? Meeting, conferences, scientific and technical literatureMeeting, conferences, scientific and technical literature Local dissemination workshops (language)Local dissemination workshops (language) SMART: the book ?SMART: the book ?