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Carlo Giupponi1,2 and Gretel Gambarelli2,3 1Università degli Studi di Milano 2FEEM 3 PhD, Università Ca’ Foscari di Venezia SMART Workshop Tunis September 2004 Towards the comparative analysis of the case studies: operative steps “Cooking” a comparative analysis The ingredients 5 very different CS 3 scenarios Models inputs Metadata (WP04) Models outputs Policy responses The dish COMPARATIVE ANALYSIS The receipt DPSIR framework Sustainability indicators 2 How to cook this dish? Option 1 Option 2 - more rigorous - less rigorous - more ambitious - less ambitious The difference between option 1 and 2 is about the relationship between scenarios and responses and the number of necessary models runnings 3 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. 4 OPTION 1: 5 OPERATIVE STEPS 1) Definition of scenarios 2) Definition of responses (E,F) 3) Definition of sustainability indicators 4) We run the 3 scenarios with existing responses 5) We run the 3 scenarios with desirable future responses CA on existing policies for each scenario CA on proposed policies for each scenario 5 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. TYPE CLIMATE (D) POPULATION (D) LAND-USE (D) INDICATOR Precipitation Temperature Population growth rate Urban population Rural population Population density PROPOSED PROPOSED BY UNIT (2) SOURCE EEA D04.01 SMART D04.01 UNEP/MAP D04.01 UNEP/MAP D04.01 UNEP/MAP D04.01 D04.01 UNEP/MAP % of total area Share of Urban area Share of irrigated agricultural land SMART Share of Industrial area SMART Share of Portual area Share of Tourism development area or: Number of turists per km of coastline SMART % of total area % of total area % of total area SMART % of total area LUC MODEL turists/km2 national statistics UNEP/MAP UNEP/MAP LUC MODEL LUC MODEL LUC MODEL LUC MODEL 6 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). TYPE RESPONSE Water demand management Water prices (domestic, agriculture, industry, tourism) Water subventions Water distribution and use systems investments Change in irrigation systems Change in cropping patterns Rising awareness for limiting abstraction Minimum flow for environmental purposes Water supply management Water quality management PROPOSED BY EEA SMART SMART SMART SMART SMART SMART Efficiency of water use Efficiency in irrigation Efficiency in urban network Water leakage EEA UNEP_MAP UNEP_MAP EEA Water harvesting (lakes, reservoirs, small dams) SMART Reservoir storage investments SMART Groundwater exploitation Mobilization of surface water Basin-out water supply (groundwater) Water imports Recycling of wastewater Desalination Limits to groundwater exploitation SMART SMART SMART SMART SMART SMART SMART Share of industrial wastewater treated on site Solid waste management for avoiding illegal discharge in waterflows Urban waste water treatment Water treatment investments Share of collected and treated wastewater by the public sewerage system Rising awareness for limiting fertilization UNEP-MAP SMART EEA SMART UNEP-MAP SMART Limit salinization through drainage systems SMART Existence of monitoring programs concerning pollutants inputs National regulations on wastewater UNEP-MAP SMART 7 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 TYPE INDICATOR PROPOSED BY: PROPOSED UNIT SOURCE IMPACT INDICATORS: ECONOMIC D/S ratio for agriculture SMART or: GDP from agriculture SMART D/S ratio for industry SMART or: GDP from industry SMART D/S ratio for tourism SMART or: GDP from turistic sector SMART Economic efficiency of the system IMPACT INDICATORS: D/S ratio for domestic uses or: number of days without drinking water IMPACT INDICATOR: D/S ratio for environmental uses STATE INDICATORS: Nutrients in coastal waters ENVIRONMENTAL Hazardous substances in transitional, coastal and marine waters or: Global quality of coastal waters or: Bathing water quality PRESSURE INDICATOR: Water exploitation index (WEI) SOCIAL CROSSCUTTING % thousands euros WaterWare % thousands euros WaterWare WaterWare SMART % thousands euros euros/ mc H2O SMART % WaterWare SMART days/year WaterWare SMART % EEA EEA UNEP - MAP EEA EEA and UNEP-MAP: Mean annual total abstraction of freshwater / long-term average freshwater WaterWare Telemac class (I-IV) class (I-IV) Telemac Telemac Telemac % 8 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? 9 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? 10 OPTION 1: MODELS RUNNING Hence, for each CS: 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 11 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 12 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) 13 PESSIMISTIC SCENARIO DF: Increased share of irrigated agricultural land INDICATOR Share of irrigated area LUC MODEL BASELINE 50% BAU 0% OPT -3% PESS +5% 14 DF: Increased share of irrigated agricultural land P: Increase in water demand for agriculture P Water demand for agriculture Current irrigation methods, crops etc. 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. 15 DF: Increase in irrigated surface Allocation strategies & other inputs P: Water demand for agriculture S: Total water availability for agriculture WATER RESOURCES MANAGEMENT MODEL Aggregation of daily data S Total water availability for agriculture m3/y 16 DF: Increase in irrigated surface P: Water demand for agriculture Water demand for agriculture P S Total water availability MC/y WATER RESOURCES MANAGEMENT MODEL I S: Total water availability for agriculture MC/Y D/S ratio in agriculture % I: D/S ratio in agriculture Input for CA of existing responses 17 DF: Increase in irrigated surface P: in Water Water P: Decrease Increase in demand demand for for agriculture agriculture Total water S:S:total water availabilityfor for availability agriculture unchanged agriculture R: Sprinkler use I:I:D/S D/Sratio ratioinin agriculture agriculture improves decreases Input for CA of future WDM responses 18 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) 19 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 20 Discussion…. For both option 1 and option 2 we have to agree on - scenarios - responses (included or not in scenarios) - sustainability indicators 21 1) SCENARIOS TYPE CLIMATE (D) POPULATION (D) INDICATOR Precipitation Temperature Population growth rate Urban population Rural population Population density TELEMAC: Share of Urban area - sources of pollution Share of irrigated D04.01 SMART D04.01 UNEP/MAP D04.01 UNEP/MAP D04.01 UNEP/MAP D04.01 D04.01 UNEP/MAP SMART LUC MODEL SMART SMART % of total area LUC MODEL turists/km2 national statistics Share of Industrial area SMART Share of Portual area WATERWARE: Share Metadata (WP04)? of Tourism development area - Income increase sector or:per Number of turists per km of coastline % of total area % of total area % of total area % of total area UNEP/MAP - concentration of pollution (D) SOURCE EEA agricultural land - type of pollution LAND-USE PROPOSED PROPOSED BY UNIT (2) UNEP/MAP - Per capita water consumption by sector, etc. LUC MODEL LUC MODEL LUC MODEL 22 2) RESPONSES TYPE RESPONSE Water demand management Water prices (domestic, agriculture, industry, tourism) Water subventions Water distribution and use systems investments Change in irrigation systems Change in cropping patterns Rising awareness for limiting abstraction Minimum flow for environmental purposes Water supply management Water quality management PROPOSED BY EEA SMART SMART SMART SMART SMART SMART Efficiency of water use Efficiency in irrigation Efficiency in urban network Water leakage EEA UNEP_MAP UNEP_MAP EEA Water harvesting (lakes, reservoirs, small dams) SMART Reservoir storage investments SMART Groundwater exploitation Mobilization of surface water Basin-out water supply (groundwater) Water imports Recycling of wastewater Desalination Limits to groundwater exploitation SMART SMART SMART SMART SMART SMART SMART Share of industrial wastewater treated on site Solid waste management for avoiding illegal discharge in waterflows Urban waste water treatment Water treatment investments Share of collected and treated wastewater by the public sewerage system Rising awareness for limiting fertilization UNEP-MAP SMART EEA SMART UNEP-MAP SMART Limit salinization through drainage systems SMART Existence of monitoring programs concerning pollutants inputs National regulations on wastewater UNEP-MAP SMART 23 3) SUSTAINABILITY INDICATORS TYPE INDICATOR PROPOSED BY: PROPOSED UNIT SOURCE IMPACT INDICATORS: ECONOMIC D/S ratio for agriculture SMART or: GDP from agriculture SMART D/S ratio for industry SMART or: GDP from industry SMART D/S ratio for tourism SMART or: GDP from turistic sector SMART Economic efficiency of the system IMPACT INDICATORS: D/S ratio for domestic uses or: number of days without drinking water IMPACT INDICATOR: D/S ratio for environmental uses STATE INDICATORS: Nutrients in coastal waters ENVIRONMENTAL Hazardous substances in transitional, coastal and marine waters or: Global quality of coastal waters or: Bathing water quality PRESSURE INDICATOR: Water exploitation index (WEI) SOCIAL CROSSCUTTING % thousands euros WaterWare UATLA presentation % thousands euros WaterWare WaterWare SMART % thousands euros euros/ mc H2O SMART % WaterWare SMART days/year WaterWare SMART % EEA EEA UNEP - MAP EEA EEA and UNEP-MAP: Mean annual total abstraction of freshwater / long-term average freshwater WaterWare SOGREAH presentation Telemac class (I-IV) class (I-IV) Telemac Telemac Telemac % 24