Download FEEM PPT Template

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