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

Boithias et al. SCARCE 2012

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

Boithias et al. SCARCE 2012

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

Boithias et al. SCARCE 2012

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

Boithias et al. SCARCE 2012

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

Boithias et al. SCARCE 2012

Water scarcity ↘ when spatial scale ↗

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Impact of precipitation change

Boithias et al. SCARCE 2012

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

Boithias et al. SCARCE 2012

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

Boithias et al. SCARCE 2012

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.)

Boithias et al. SCARCE 2012 19

Contact: lboithias@icra.cat

Thank you !

River Ebro at Amposta. Source : AGOM

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Agricultural water demand

Boithias et al. SCARCE 2012

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