Is water scarcity L. Boithias, V. Acuña, scale-dependent ... Boithias.pdfEbro basin case study...
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L. Boithias, V. Acuña, L. Vergoñós, R. Marcé, S. Sabater 3rd SCARCE International Conference 26-27 November 2012, Valencia, Spain Is water scarcity scale-dependent? 1
Transcript of Is water scarcity L. Boithias, V. Acuña, scale-dependent ... Boithias.pdfEbro basin case study...
L. Boithias, V. Acuña, L. Vergoñós, R. Marcé, S. Sabater
3rd SCARCE International Conference 26-27 November 2012, Valencia, Spain
Is water scarcity scale-dependent?
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Water supply as an ecosystem service
Policy What policy mechanisms are available to protect and promote ecosystem services?
Valuation How valuable are
ecosystem services?
Policy formation
Economic and social value
Ecological value
Protection and management
Service use
Biophysical generation of ecosystem services
How can ecosystem service production be defined and
measured? Beneficiaries and producers
What is the spatial relationship between ecosystem service supply and consumption?
Water supply by terrestrial surface water: 42x1012 US$.yr-1 (≈ GDP EU, US, China, Japan) (Costanza et al., 1997)
In 2030: water scarcity in half of the EU river basins (EC, 2012).
Spatial mismatch between service production and consumption (e.g. Hein et al., 2006; Fisher et al., 2009)
Policy-relevant questions for understanding, assessing, and managing ecosystem services (Brauman et al., 2007)
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Water supply as an ecosystem service
Boithias et al. SCARCE 2012
Policy EU WFD asks for full cost recovery
Valuation Purpose of the study
= water provision service valuation
Policy formation
Economic and social value
Ecological value
Protection and management
Service use
Biophysical generation of ecosystem services Choice of a metric
Beneficiaries and producers Few attempts were yet made to quantify the spatial and temporal mismatches between
service production and consumption + Environmental flow as environmental demand
→ What spatial scale would be optimal for water provision management ? → What would be the impact of global change on spatial dependencies ?
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The supply-to-demand S:D ratio
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S:D
S = SPCP - ETpristine - EF D = Dagr + Durb + Dind
Calculated at 5 spatial scales :
Basin
Region
Province
Irrigation community
Sub-basin
Supply of water = water yield for a given precipitation falling within a given time period on a pristine land cover, with or without consideration of environmental flow. Climate dependent.
Demand for water = water provision currently consumed over a given time period. Policy dependent.
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Ebro basin case study
Boithias et al. SCARCE 2012
InVEST : catchment-scale hydrological model, computing water balance at annual time step
DEM : 200x200 m for subbasin generation Climate data : Rainfall, temperatures max, min from 197 AEMET stations (1991-2010) + Solar radiation from 26 stations (Ministerio de Fomento 2011) Water discharge : daily discharge from 18 gauging stations (Confederación Hidrográfica del Ebro, 1991-2010)
85 530 km2, from 0 to 3404 m Rainfall : from 261 to 2188 mm 234 dams (total water storage was 8 360 hm3 ± 2 000 hm3 in 2009) Irrigated agriculture : 1 293 656 ha (15% - total agriculture = 52%)
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Additional data
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Environmental flow : Confederación Hidrográfica del Ebro (2012) Water price : Industrial and domestic uses (Asociación Española de Abastecimientos de Agua y Saneamiento, 2010)
Environmental Flow
Land use: Corine Land Cover (2006) Soil type and soil depth : INIA (2008) + European Soil Database (2006) Water demand : Industrial and domestic (Ministerio del Agricultura, Alimentación y Medio Ambiente, 2000) + Agricultural (from modelling, water consumption difference between pristine land cover and agricultural land use)
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9 scenarios
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Calibration
+23% -17%
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9 scenarios
Boithias et al. SCARCE 2012
Calibration
Sensitivity of S:D to climate extremes
+23% -17%
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9 scenarios
Boithias et al. SCARCE 2012
Calibration
Sensitivity of S:D to climate extremes
Sensitivity of S:D to land use change
+23% -17%
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9 scenarios
Boithias et al. SCARCE 2012
Calibration
Sensitivity of S:D to climate extremes
Sensitivity of S:D to land use change
Spatial dependencies and global change
+23% -17%
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Model calibration
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Water yield : Calibrated for 18 gauging stations Water demand : Simulated D : 9 530 hm3.yr-1 Observed D : 8 185 (CHE, 2011) – 10 378 (MMA, 2000) hm3.yr-1
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Supply and demand calculation
S = -22% S = +57%
D = -17% D = +16%
S = -23% S = -43% S = +33%
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Water scarcity and spatial scale
Boithias et al. SCARCE 2012
S:D < 1 -> water scarcity
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Water scarcity and spatial scale
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Water scarcity ↘ when spatial scale ↗
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Impact of precipitation change
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Temporal scale
= most likely to happen scenario, by 2050 (Iglesias et al., 2007) Can we mitigate the impact of precipitation change ?
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Impact of land use change
Mitigation scenario
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Synthesis of S:D ratios at basin scale
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PCP PCPwet PCPdry
No EF With EF No EF With EF No EF With EF
Actual 2.1 1.6 3.3 2.8 1.6 1.2
-20% 2.5 2.0 4.0 3.4 2.0 1.4
+20% 1.8 1.4 2.8 2.4 1.4 1.0 Irri
gate
d a
rea
Precipitation (PCP)
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S:D = 1
Water price vs. S:D ratio
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S:D = 1
Outline of a monetary valuation of the S:D ratio (actual land use, 1991-2010 PCP average), based on water price for industrial and domestic uses :
→ Prices vary between 0.7 and 2.1 €.m-3, f(use and taxes) 18
Conclusions
• S:D : spatial and temporal mismatches of provision vs. consumption – Water scarcity is a local issue
– Issues may rise from global changes
• First step to achieve part of the objectives of the WFD – Water allocation is based on environmental flow (EC, 2012)
– Actual prices of water provision could be indexed on S:D
• Apply the method to other ecosystem services (ex. for energy supply see Burkhard et al., 2012) – Service delivery and trade-offs assessment based on biophysical
metric
– E.g. Water provision vs. environmental flow (nutrient retention, chemical degradation, etc.)
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Agricultural water demand
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With InVEST :
RUN 1
RUN 2
Irrigated and non irrigated agriculture
replaced by a pristine land cover (shrubland)
Supply 1
Supply 2
+
+
Supply 2 – Supply 1 = Dagr Actual
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Boithias et al. SCARCE 2012
Revoir avec Vicenç : insister sur pricing ou sur spatial / temporal dependencies ? Pour eviter considerations politiques (note que je démarre sur le prix, comment boucler avec la ccl?) -> bien axer SCALE (temp -+ spat) intro/ccl Garder le prix ?sensitivity of S:D to climate extremes -> vulnerability to climate change. 22
