Towards the comparative analysis of the case studies: operative steps

1. Carlo Giupponi1,2 and Gretel Gambarelli2,3 1Università degli Studi di Milano 2FEEM 3 PhD,Università Ca’ Foscari di Venezia Towards the comparative analysis of the case studies: operative steps SMART Workshop Tunis September 2004

2. “Cooking” a comparative analysis The ingredients 5 very different CS 3 scenarios Metadata (WP04) Models inputs Models outputs Policy responses The dish COMPARATIVE ANALYSIS The receipt Sustainability indicators DPSIR framework

3. How to cook this dish? Option 1 - more rigorous - more ambitious Option 2 - less rigorous - less ambitious The difference between option 1 and 2 is about the relationship between scenarios and responses and the number of necessary models runnings

4. WP10 objectives • To identify commonalities and differences and relate them to the specific regional setting; • To identify more generally applicable results that are invariant across the case studies; • To organize these finding in terms of a comparative policy assessment (existing and desirable, future ones) and best practice examples – contribution to sustainability.

5. OPTION 1: 5 OPERATIVE STEPS 1) Definition of scenarios 3) Definition of sustainability indicators 2) Definition of responses (E,F) 4) We run the 3 scenarios with existing responses CA on existing policies for each scenario 5) We run the 3 scenarios with desirable future responses CA on proposed policies for each scenario

6. OPTION 1: step 1 1) Scenarios are defined by COMMON VARIABLES representing DRIVING FORCES of all CS (Climate, Population, Land Use), NOT INCLUDING WATER POLICY RESPONSES.

7. OPTION 1: STEP 2 2) Responses are organized in COMMON CATEGORIES for all CS (Water Demand, Water Supply, Water Quality), but single responses are SPECIFIC per CS (PARTICIPATION OF STAKEHOLDERS).

8. OPTION 1: STEP 3 3) Indicators for the CA are COMMON to all CS and address the 3 pillars of sustainability (Economy, Society, Environment) + cross-cutting themes

9. OPTION 1: STEP 4 4) Models are first run for the 3 scenarios, with the CURRENT RESPONSES for all CS. Values of sustainability indicators are derived. The COMPARATIVE ANALYSIS assesses how current responses perform in different case studies in each scenario. Policy questions to be answered: How effective are existing water policies with respect to the management of water supply, water demand and water quality? What are the current effects of existing water policies on economic performances, the quality of life, the environmental quality? Are the abstractions from our water resources sustainable over the long term? What are the differences and communalities in current practices of the 5 CS?

10. WP10: STEP 5 5) Models are run PER EACH SCENARIO, PER EACH CATEGORY OF RESPONSES. Each response impacts on a pressure or a state indicator, thus modifying models’ inputs. Values of sustainability indicators are derived. The COMPARATIVE ANALYSIS assesses how common types of future responses perform in different case studies in each scenario. Policy questions to be answered: How effective are proposed water policies with respect to the current practices in improving the management of water supply, water demand and water quality? How effective are proposed water policies with respect to the current practices in improving economic performances, the quality of life, the ecological quality? Are the abstractions from our water resources sustainable over the long term if the proposed policies are implemented? What are the differences and communalities in proposed practices of the 5 CS?

11. OPTION 1: MODELS RUNNING 3 scenarios, 1 Existing +3 Future Responses (WD, WS, WQ) 3x4 = 12 runnings of models per each CS 12 different results registered by sustainability indicators Hence, for each CS:

12. OPTION 1: pros and cons PROS: - there is a LOGICAL DISTINCTION between external variables (i.e. climate conditions, population growth, etc.) and decision variables (i.e. water policies). - more consistent with DPSIR: D define scenarios, for each scenario we have different effects on P,S,I indicators and R try to improve P, S, I indicators CONS: - rather complex - many models runnings

13. WP10: EXAMPLE • EXAMPLE: • Evaluation of one sustainability indicator (D/S ratio for agriculture): • 1 scenario (pessimistic) • 1 variable defining scenario (share of irrigated agricultural land) • 1 type of response (water demand management. In particular: sprinkler irrigation)

14. PESSIMISTIC SCENARIO DF: Increased share of irrigated agricultural land LUC MODEL INDICATOR BASELINE BAU OPT PESS Share of irrigated area 50% 0% -3% +5%

15. DF: Increased share of irrigated agricultural land P: Increase in water demand for agriculture Current irrigation methods, crops etc. P Water demand for agriculture m3/year Possibilities for the derivation of sectoral water demand: - water demand derived through a decision table having land use and population growth as inputs - direct derivation of water demands (coherent with land-use). In both cases the sum of sectoral water demands should be equal to the regional water demand for each scenario, as calculated by the LUC model.

16. Allocation strategies & other inputs DF: Increase in irrigated surface P: Water demand for agriculture WATER RESOURCES MANAGEMENT MODEL S: Total water availability for agriculture Aggregation of daily data S Total water availability for agriculture m3/y

17. Water demand for agriculture P MC/Y DF: Increase in irrigated surface S Total water availability MC/y WATER RESOURCES MANAGEMENT MODEL P: Water demand for agriculture I D/S ratio in agriculture % S: Total water availability for agriculture I: D/S ratio in agriculture Input for CA of existing responses

18. DF: Increase in irrigated surface R: Sprinkler use P: Increase in Water demand for agriculture P: Increase in Water demand for agriculture P: Decrease in Water demand for agriculture I: D/S ratio in agriculture improves S: Total water availability for agriculture unchanged I: D/S ratio in agriculture decreases S: total water availability for agriculture Input for CA of future WDM responses

19. OPTION 2: OPERATIVE STEPS 1) Definition of scenarios, including responses 2) Definition of sustainability indicators 4) BAU scenario (including existing responses) 6) Optimistic scenario (including desirable future responses) Answer to policy questions 6) Pessimistic scenario (including undesirable future responses)

20. OPTION 2: pros and cons CONS: - NO LOGICAL DISTINCTION between external variables (i.e. climate conditions, population growth, etc.) and decision variables (i.e. water policies). - less consistent with DPSIR: D and R are mixed in defining scenarios, so the effect of R on P,S.I indicators is less transparent because other variables (climate, population, etc.) change at the same time PROS: - less complex - less models runnings

21. Discussion…. For both option 1 and option 2 we have to agree on - scenarios - responses (included or not in scenarios) - sustainability indicators

22. 1) SCENARIOS TELEMAC:- sources of pollution - type of pollution - concentration of pollution WATERWARE: Metadata (WP04)? - Income increase per sector - Per capita water consumption by sector, etc.

23. 2) RESPONSES

24. 3) SUSTAINABILITY INDICATORS UATLA presentation SOGREAH presentation