DSS for Integrated Water Resources Management (IWRM)

1. DSS for Integrated Water Resources Management (IWRM) Success and failure DDr. Kurt Fedra ESS GmbH, Austria kurt@ess.co.at http://www.ess.co.at Environmental Software & Services A-2352 Gumpoldskirchen

2. SUCCESS AND FAILURE OF DECISION SUPPORT SYSTEMSFOR INTEGRATED WATER RESOURCE MANAGEMENT Presented at: Palazzo Zorzi, Venice, Italy5-7 October 2005

3. DSS for water resources management DSS success measure and end user satisfaction Apparent assumptions: • We can measure the success of a DSS • We can measure user satisfaction • Success and user satisfaction is not necessarily the same.

4. Degree of consensus on actions Level of information on consequences of actions Framework for water management (after Verbeek & Wind, 2001)

5. DSS for water resources management Some experiences : 1. Nature of application unclear: • Policy/DM process to be supported unclear • most DSS provide “only” scenarios • assumption of chronology design-implementation incorrect • “work-flow” users not involved in design • no continuous involvement of users

6. DSS for water resources management 2. Conflict science vs policy • DSS built on “state-of-the-art” science models, research oriented Resulting problems: • Lack of system consistency • Lack of flexibility to change • Little room for uncertainty • Models/data limiting factors • Technology driven design • Lack of long-term support

7. DSS for water resources management Possible solutions: - embedding in policy process - continuous user involvement - science  engineering - science of integration, both : Technological: alternative tools, hierarchical structure, uncertainty propagation Institutional: actor analysis, participation

8. DSS for water resources management DSS success measure and end user satisfaction Apparent assumptions: • We can measure the success of a DSS • We can measure user satisfaction • Success and user satisfaction is not necessarily the same.

9. DSS for water resources management Proposition: • We can NOT measure the success of a DSS in terms of making “better” decisions; • We can measure user satisfaction by traditional psychometric methods (uncertain) OR measure it in quantitative terms of frequency and extent of use; • Therefore, success and user satisfaction is the same: success is being used.

10. DSS for water resources management Lemmata: • Basic objective of a DSS is to influence decision making processes, educate and empower participants • Education needs a happy and attentive audience (satisfied users)

11. DSS for water resources management Corollary: Users are happy if they get what they want which is NOT ONLY a better decision in some (naïve neopositivist) objective sense meeting expressed aspirations but includes diverse, usually hidden agenda.

12. Measuring success Lemma: Success is difficult to measure: Compared to WHAT ?? Only one decision gets implemented – there is nothing to compare the outcome with.

13. Measuring success Success is difficult to measure: It may be easier to establish failure cases: • Mismatch of expectations and resources • Mismatch of expectations and product • Institutional change, priorities shift • People change (retire, get promoted, leave) Indication of failure: to be ignored

14. Success: building consensus How to motivate a group to cooperate: • Demonstrate the potential for an increase in overall net benefit (through optimization) • Demonstrate allocation of the net benefit in a “win-win game” • Use a DSS for that …..

15. IWRM Decision Problems Problems: • Too much, not enough • Wrong time and place • Insufficient quality • Prohibitive costs ?

16. Overall objective: Every use including the environment gets the water needed (in terms of quantity and quality) wherever, whenever, at an affordable price or cost to the public, sustainably.

17. Overall objective: • Supply meets demands • Demands (expectations) are well balanced with all supplies • Benefits exceed costs • System is sustainable, equitable (everybody happy) ELSE THERE IS CONFLICT

18. Overall objective: More formally: • Maximise a social utility function subject to some equity constraint

19. If there is conflict: Which decisions ?? • Supply management incl. quality • Alternative sources, water allocation, • Structures, technologies • Investment, OMR, economic incentives • Demand management • Pricing, economic incentives • Technologies (economics, efficiency, reuse) • Regulatory framework (affects all) • Policy and decision making process • Market mechanisms

20. Thesis: Water resources problems require a new approach to decision support and decision making because: • it is impossible to solve the inverse problem (HOW TO) unambiguously due to the complexities of systems;

21. Thesis: As a consequence, any practical DSS approach has to be • iterative(multi tiered) • adaptive(learning) • interactive(end user involvement)

22. Conclusions Paradigm change: • more complex problems (increasing pressures, demands) • participatory processes, civic society, diverse audience • increasing demand for information

23. Conclusions Paradigm change: • information technology promises instantaneous and ubiquitous access to information • research results and tools are directly accessible beyond the academic community

24. Conclusions Paradigm change: • changed nature of discourse from scientific correctness, precision, verification, formal proof to political feasibility, acceptability, Mehrheitsfähigkeit; • from abstract optimality to an evolutionary: good enough.

25. Conclusions Paradigm change: DSS do not offer optimal solutions (given a set of preferences) but a mechanism to make the process open, accessible, and the solution acceptable to a majority.

26. Concluding assumption: • improvements to the DM process will lead to • improvements of the DM results. (an ISO 9000 approach).