Water in de EU: wat doet “Brussel”?
Prof. Dr. Ad de Roo
(1) European Commission – Joint Research Centre (2) Faculteit Geowetenschappen- Univ Utrecht
Wie zijn ‘Brussel’? • de Europese Commissie heeft net zoveel ambtenaren als de stad Parijs, die minder dan 3% van budget opslokken • Die behappen vervolgens veel water/milieu beleid, o.a. Water Framework Directive, Floods Directive, Marine Strategy Framework Directive (MSFD) naast core issues als Landbouw (AGRI) en Regionale Ontwikkeling (REGIO) (zo’n 94% van budget gaat weer terug naar lidstaten)
• 9% van de EC-staf doet onderzoek: Joint Research Centre (JRC), naast het uitbesteden van onderzoek (RTD)
Wat doet ‘Brussel’ op het gebied water? • Voorbereiding en uitvoering van EU wetgeving: • Water Framework Directive • Floods Directive • Marine Strategy Framework Directive
• Andere beleidsdocumenten: • Blueprint to Safeguard Europe’s Waters • Strategy on Water Scarcity and Droughts
• Klimaatverandering: • "20-20-20" targets - key objectives for 2020: A 20% reduction in EU greenhouse gas emissions from 1990 levels Raising share of EU energy consumption prod. from renewable resources to 20% A 20% improvement in the EU's energy efficiency
• mainstreaming climate policies (for mitigation) • adaptation strategies in existing policies • 2030 policy framework for climate and energy
Wat doet EC-Joint Research Centre? • Onderzoek op alle EC policy velden, om te kunnen adviseren in het opstellen, monitoring and handhaving van EU-wetgeving • Bv Water Framework Directive, Blueprint Water • Controle op landbouwsubsidies, Solidarity Fund
• Directe ondersteuning van lidstaten met bepaalde diensten • Bv EFAS: European Flood Awareness System, EFFIS-bosbranden, EDO-droogte, GDACSaardbevingen/tsunamis
JRC water modelling activities: LISFLOOD
P
EWint Int
Dint
topsoil
ESact
subsoil
Tact Dus,ls Dls,ugw
upper groundwater zone lower groundwater zone
INFact
Qsr
surface runoff routing
Dpref,gw Qugw
Dugw,lgw
Qlgw Qloss
river channel
Gebruikt voor: • Monitoring droughts (EDO) • Voorspellen overstromingen (EFAS, GloFAS) • Water resources modellering • Impact van maatregelen in WFD, FD Europa • Case-studies Africa & Latin America • Incl hydro-economic optimalisation • Effecten klimaatverandering en landgebruiksverandering • Europese en Globale schaal
Effecten van klimaat-verandering op Europese water resources
Changes in flood hazard in Europe 10°
20°
30°
40°
50°
-30°
-20°
-10°
0°
10°
20°
30°
40°
-30°
50°
-20° -10°
0°
10°
20°
30°
40°
50°
p-value 60°
60°
60°
60°
10-12
0.05 0.1 0.2
50°
50°
50°
50°
60°
60°
8-10 6-8 4-6 2-4
50°
50°
0-2 2-4
0.2 40°
40°
0°
10°
40°
40°
20°
0°
Relative change in 100-yr flood event between 19611990 and 2080s
10°
20°
Significance of change in 100-yr event
1980s
0.1 0.05
4-6 40°
40°
decrease
0°
increase
>+60 +40 +20 +10 +5 -5 -10 -20 -40 <-60
-10°
decrease
change (%)
-20°
6-8
increase
-30°
SRES A1B
8-10 0°
10°
20°
10-12
Number of model runs (out of 12) showing consistent increase
2080s
Flood magnitude
Rojas et al., JGR, 2012
Return period
Return period
7
Changes in flood risk in Europe 2000s
2050s
2020s
2080s
SRES A1B
Relative change in direct flood damages between 1961-1990 and future period (ensemble averaged results for SRES A1B scenario)
Rojas et al., Global Environmental Change, 2013 8
Flood risk reduction options
Jongman et al., Nature Climate Change, 2014
9
Changes in low-flow in Europe 10°
20°
30°
40°
50°
-30°
-20°
-10°
0°
10°
20°
30°
40°
50°
p-value 60°
60°
60°
60°
10-12
0.05 0.1 0.2
50°
50°
50°
50°
8-10 6-8 4-6 2-4 0-2 2-4
0.2 40°
40°
0°
10°
20°
0°
Relative change in 20-yr low-flow event between 1961-1990 and 2080s
Forzieri et al., HESS, 2014
40°
40°
10°
20°
Significance of change in 20-yr event
decrease
0°
decrease
>+60 +40 +20 +10 +5 -5 -10 -20 -40 <-60
-10°
0.1 0.05
increase
change (%)
-20°
4-6 6-8
increase
-30°
SRES A1B
8-10 10-12
Number of model runs (out of 12) showing consistent decrease
Inter-annual dynamics in simulated 7-day streamflow for the 1980s (blue) and the 2080s (red)
10
Klimaatverandering, wat te doen?
•
Mitigation (emissie beperkingen)
•
Betere informatie basis (nationaal, europees, globaal) Betere monitoring en early warning systemen Onderzoek naar maatregelen die problemen reduceren
• •
Betere early warning systemen: voorbeelden EFAS & GloFAS
European Flood Awareness System (EFAS) •
10-day early warning system based on ECMWF ensemble forecasts
•
EFAS started in research model in 1999 (EFFS project)
•
Following 2002 floods, EFAS went pre-operational with additional financing through European Parliament, IDABC, ECHO/MIC and GMES/Copernicus
•
EFAS fully operational since September 2012 under the Copernicus Emergency Management Service.
•
EFAS partners: EFAS has now more than 30 partner authorities • New EFAS 2014 features: Improved model Improved visualization of end products on www.efas.eu Publication of forecast verification skills in the EFAS bulletins
Find out more on www.efas.eu
EFAS 2006 Voorspelling Praag (Elbe): 12 dagen leadtime
March 2006
April 2006
EFAS : European Flood Awareness System
developed since 1999, operational in 2012 with Copernicus and MIC/ECHO budget
Warnings sent out to Member State authorities and MIC on 12 May 2010 MIC activated 19 May 2010 ; within 12 hours team on-site in Poland!
Sava flood 2014
Global Flood Awareness System (GloFAS)
Flood early warnings for large river basins around the world Developed by: Joint Research Center of the European Commission & European Center for Medium Range Weather Forecasting
Forecast lead time: Up to 20 days Minimum river basin size: 10.000 km2 Forecast frequency: Daily Forecast type: Probabilistic
New developments in EFAS: From EPIC to ERIC: from Precipitation to Runoff EPIC indicator (European Precipitation Index based on Climatology) : Only based on precipitation Introduction of the Runoff Coefficient to weight the different contributions of rainfall Functioning: I.
Separation rain and snow
II. Introduction coefficient III. Computing runoff Daily initial moisture
soil
Daily runoff map
of the runoff the
upstream
IV. Assessing the probability of exceedance of different return period events
Paper in publication(Raynaud et al.) operational implementation foreseen during 2014
Global Water Resources: Climate change, possible measures & possible conflict areas
Estimated current annual freshwater ‘production’
JRC’s Global Hydrological Model LISFLOOD Global spatial data
Freshwater “production”
River network, land cover, elevation etc.
Local runoff
Model P
EWint Int
Dint
Daily data: Precipitation, temperature, wind speed etc.
topsoil
ESact
subsoil
Tact Dus,ls Dls,ugw
upper groundwater zone lower groundwater zone
INFact
Q sr
surface runoff routing
Discharge
Dpref,gw Qugw
Dugw,lgw
Q lgw Qloss
Water use:
Water demand: from industry, lifestock, irrigation etc.
river channel
depending on availability (local and upstream)
JRC’s Global Hydrological Model LISFLOOD Local freshwater “production”
Water exploitation index
Analysis Water use regions
Percentage of days: Water demand > water availability
Local water exploitation index
0.1 degree, daily
Water exploitation index (local)
Percentage of days: Water demand > water availability
Local water exploitation index
Average February
Water exploitation index
Local Water exploitation index
Average July
Water exploitation index
Local Water exploitation index
Euphrates
Ebro
Nile
Local Water exploitation index
Water exploitation index
Local water exploitation index
Percentage of days: Water demand > water availability
Local water exploitation index
Maatregelen & optimisalatie: Multi-criteria hydro-economic modelling
A
JRC LUMP Land Use Modelling Platform using the land use model Eu-ClueScanner (JRC) Land use / land cover change scenarios until 2030 Common Agricultural Policy (CAP) consistent (using CAPRI boundary conditions for 2030) Socio-Economic data used from Eurostat 100m spatial resolution Pan-European
© JRC
Water consumption 2006 and changes until 2030
LISQUAL output: Water Exploitation Index WEIcns= (Abstraction – ReturnFlow) / (Local runoff + Incoming runoff) WEIcns (WEI+, consumption only)
WEIabs (abstraction only)
© JRC
Cost of scenarios
Economic Loss model irrigation Damage per m3 0.12 0.1 0.08 0.06
Damage per m3
0.04 0.02 0 0
0.5
1
1.5
Assumptions: - Ratio delivered water <> value is taken as 0.1 - Quadratic function This results in that for every m3 water that is not available for irrigation, the damage is maximally the choke price (0.1 euro in this example) So, e.g, if the required amount of water for irrigation area is 1 Mm3, and Available water (Mm3) 1.0 0.5 0.1 0
Loss (MEuro) 0.0 MEuro 0.025 MEuro 0.081 MEuro 0.1 MEuro
Choke price:
0.35 Euro/m3 (low value crops) 1.25 Euro/m3 (high value crops)
Optimization InitProcessor
Optimizer optimal combination of percentage scenarios
new percentages of scenarios
PostProcessor CostFunction
Statistical comparison of scenarios and baseline
OptInterface
PreProcessor
(scenarios-baseline) *r OUTPUT N P Cost EnvFlow Wei_abs
Simplified Biophysical Model
INPUT ttoc srun pflow sgw nleach pleach nrunoff
A
C
B
1. Point A and B same investment but point B has better Env. quality – I chose B 2. Point C and B same Env. quality but C needs higher investment – I chose B Investment (€)
Investment (€)
Multicriteria Optimization
Max
Environmental quality
1. Point A is better choice compare with points B-C-D-E 2. The situation is less clear when you are looking to the point A and A’. A is lower Cost, but A’ is better ENVIRONMENTAL quality…both options are valid choices.
Restrictions
C B
A’
D E A
Environmental quality Min
Danube: scenario-combination C47
© JRC
Leakage reduction, Desalination (Black Sea), Urban Greening in Zagreb and Belgrade, Re-Use of Water in Industry in Bulgaria, irrigation water use efficiency, and water savings in households
Danube: scenario-combination C71
© JRC
No desalination, Leakage reduction only in Bucharest, Urban Greening only in Zagreb, no water-re-use in industry in Bulgaria
Conclusies • Brussel zit niet stil…. • JRC heeft een multi-criteria optimalisatie toolbox ontwikkeld om water beheers-maatregelen hydroeconomisch te evalueren • Is al gebruikt voor Blueprint en wordt verder gebruikt voor evaluatie maatregelen door lidstaten voorgesteld in Water Framework Directive en Floods Directive • De tool wordt verder ontwikkeld, verbeterd en getest, o.a in Donau, Sava Incl grondwater modelering Economische functions Link met SWAT/EPIC voor water kwaliteit
• contact:
[email protected]
