OPTIMA INCO-MPC Project Kick-off Meeting, October 28/29 2004, Malta

1. OPTIMA INCO-MPCProject Kick-off Meeting,October 28/29 2004, Malta DDr. Kurt Fedra ESS GmbH, Austria kurt@ess.co.at http://www.ess.co.at Environmental Software & Services A-2352 Gumpoldskirchen

2. Thursday, October 28 09:00-09:15 Welcome & logistics (IRMCo) 09:15-10:00 Project Overview (ESS) 10:00-10:45 WP01 requirements and constraints 10:45-11:30 WP02 socio-economics, DSP 11:30-12:00 Lunch break 12:00-13:00 WP03 modeling tools 13:00-13:45 WP04, techno economic data

3. Thursday, October 28 13:45-14:15WP05 LUC,GIS, RS (LUC model) 14:15-15:00 WP06 System integration 15:00-16:00 WP16, Dissemination Welcome Dinner

4. Friday, October 29 09:00-11:30 WP07 -13 7 Case studies, 20 minutes each, : CY, TR, LB, JO, Pal, TN, MO 11:30-12:00lunch break 12:00-12:30 WP 14 decision analysis 12:30-13:00 WP 15 comparative analysis 13:00-15:00 Meetings, ANY OTHER BUSINESS Excursion and dinner Saturday, October 30 (morning): SMART ad hoc informal project meeting

5. MEETING OBJECTIVES • Getting to know each other (better) • Discuss background, basic philosophy strategy, approach for OPTIMA • Review Work Plan, step by step, with emphasis on the first project phase • Decide tasks for the immediate future to next meeting, first Report/Deliverable • Agree to technical work/communication details

6. OPTIMA CONSORTIUM SHORT introduction by each team: C01, FEEM, IT C07 SUMER, TURKEY C02, ESS GmbH, AT C08, NCRS, LEBANON C03, COR.0, IT C09 ELARD, LEBANON C04, INTERGEO, HE C10, UOJ, JORDAN C05, ATLANTIS, CY C11, IPCRI, PALESTINE C06, IRMCO, ML C12, CNT, TUNISIA C13, UH2M, MOROCCO

7. SMART, OPTIMA, and ??? SMART: uses scenario analysis for ICZM with emphasis on water resources; WHAT IF - ? What is possible ? OPTIMA: uses optimisation to design/select efficient solution HOW TO - ? What is best, do we want ? ?? : analyses strategies and methodology to IMPLEMENT optimal solutions HOW TO GET THERE (in the real world ?)

8. Philosophy and approach Rationalist, routed in the natural sciences, basic laws (conservation, continuity, TD, first order logic) Hypothetico-deductive with a strong empirical base (Popper with a touch of Feyerabend for fun) Keywords: structured (data bases rather than stories, model based), reasoned, reproducible, consistent, documented (ISO 9000 ?), plausible …..

9. Basic philosophy: Quantify (if you can’t count it, forget it). Measure what can be measured; make measurable what can not be measured. G.G.

10. OPTIMA OBJECTIVE is to develop, implement, test, critically evaluate, an innovative, scientifically rigorous yet practical approach to water resources management intended to • increase efficiencies and to • reconcile conflicting demands based on OPTMISATION

11. OPTIMA OBJECTIVE Develop a common structured approach to water resources management in several parallel case studies: Common approach and method for • Identifying issues • Involve end users • Describe the systems • Model/optimize them

12. OPTIMA OBJECTIVE common structured and quantitative approach to water resources management in several parallel case studies: Common approach and method for • Identifying issues • Involving end users • Describing the systems/problems • Analyze (model/optimize) them • DSS for end users

13. OPTIMA OBJECTIVE • Meet the Commission Objectives with Deliverables, Reports, Cost Statements ON TIME and ON BUDGET: THIS IS ESSENTIAL !!! • Meet individual objectives (??) for methodological development and the case studies ( end users ?); • Produce results together: comparative analysis, dissemination, going beyond the individual pieces.

14. OPTIMA: Project Overview • 3 year duration to JUNE 2007 • Started: July 2004 • Current PM: 4 of 36 Or more than 10% already over !!!!!

15. OPTIMA: time table

16. OPTIMA: Work Plan Phases • Requirements and constraints, DSS processes (end users) • Data compilation, tool development • Parallel case studies, shared tools, methods, approach • Comparative evaluation, dissemination (end users).

17. OPTIMA: Milestones

18. Work Plan (simple version) • Structure the cases (WP 1) using a COMMON framework, terminology, MC, thesaurus • Physical and institutional setting (actors), • Problems/issues • Data availability

19. Work Plan (simple version) • WP 1 and 2 Basic philosophy should be: Measure what can be measured; make measurable what can not be measured. G.G.

20. WP1 (objectives) • compile comprehensive lists of water management issues, problems, and respective information requirements • ensure early stakeholder participation • identify the major institutional structures, actors and stakeholders

21. WP1 (objectives) • compile comprehensive lists of water management issues: ONE COMMON MASTER LIST that the cases SELECT from ! Description: tuples of CONCEPT, VALUE(one of a predefined list or from a allowable range to facilitate normalisation)

22. WP1 (objectives) • list and document the data requirements of the proposed methods (on-line manuals) • analyse data availability against requirements; • analyse resulting constraints and alternative approaches where necessary.

23. Work Plan (simple version) • Structure the cases: WP 2socio-economics, decision making processes (end user incolvement) • Actors, institutions • Legal/regulatory framework • Socio-economic development

24. Work Plan (simple version) • WP 1 and 2 define: scope, common language/structure (criteria, objectives, constraints) but also realistic context (scenarios of development) for OPTIMISATION Arrange end user involvement

25. Work Plan (simple version) • WP 1 and 2 CONTRIBUTE to the model application configuration/scenarios: Supply STRUCTURED, quantitative or semi-quantitative data and information DATA, nor only stories

26. Work Plan (simple version) 2. Tools and data (WP 3) COMMON modeling framework: Dynamic water resources model estimates: • supply/demand, • reliability, efficiency • cost/benefit

28. Work Plan (simple version) 2. Tools and data (WP 3) Approach: Simulation of daily distributed water budget, optimization: brute forward MC plus heuristics, GP (multi-criteria, discrete reference point optimization).

29. Work Plan (simple version) 2. Tools and data (WP 4) techno-economic data define the variables for alternative scenarios (irrigation technologies, water saving, harvesting, recycling, desalination, plus costs of water services (supply, treatment) and benefits of water use.

30. Work Plan (WP 4) Techno-economic data: Organize in a data base of water technologies with: Costs versus Performance Demand and supply nodes in WaterWare incorporate water technologies affecting parameters for the optimization

31. Work Plan (simple version) 2. Tools and data (WP 5) • Land-use data (and development scenarios) provide context for: • Water demand (sectoral) • Runoff characteristics, infiltration/recharge

32. Work Plan (simple version) 2. Tools and data (WP 5) GIS, RS: • COMPATIBLE data and classification: CORINE L3, • Satellite imagery (good resolution, visual band for common source BG maps) • Basic GIS data: administrative, LU, infrastructure, DEM, hydro features

33. Work Plan (simple version) 2. Tools and data (WP 5) • Land-use data (and development scenarios) provide context for: • Water demand (sectoral) • Runoff characteristics, infiltration/recharge

34. Work Plan (simple version) 2. Tools and data (WP 6) WaterWare Model system and editors plus related models (LUC, RRM, IRWDM) available on-line for web access by partners and end users.

35. Work Plan (simple version) SIMULATION/OPTIMIZATION MODELS • Enforce a consistent structure/approach, discipline, require high-quality data • Generate directly comparable structurally equivalent results

36. Work Plan (simple version) OPTIMIZATION (multi-criteria) Maximize • Supply/demand ratio (by sector) • Reliability (% time, volume), • Efficiency (GRP/unit water), • Benefit/cost ratio meeting constraints (minimum or maximum allowable levels of selected criteria), minimizing non-linear penalty functions

37. Work Plan (simple version) OPTIMIZATION Maximize …. by • Choice of water technologies of different costs (investment, OMR) vs performance including structures • Different allocation strategies • Selecting criteria, setting constraints

38. Work Plan (simple version) 3. Case Studies (WP 7-13) • Run parallel • SHARE models • Use SAME structure for end user involvement, reporting

39. Work Plan (simple version) 4. Evaluation (WP 14) Post-optimal analysis: • Analyze model decision and behavior spaces (feasible set, pareto set, preference structures, trade-offs) • Cross-correlation, sensitivity analysis • Test for criteria independence

40. MC Decision Support Reference point approach: utopia A4 efficient point A5 A2 criterion 2 A6 A1 dominated A3 better nadir criterion 1

41. Work Plan (simple version) 4. Evaluation (WP 15) Comparative evaluation across case studies • Ranking by criteria, MC clustering • Discrete Multi-Criteria Optimization with end user involvement • Common patters and trends

42. Work Plan (simple version) 4. Evaluation (WP 16) Dissemination: • End user involvement • Web server, publications • Regional dissemination workshop

43. Gender issues: Nominateand select a gender issue coordinator Nominations ??