Multidecadal climate oscillations and climate scenarios for impact analysis climate scenarios for impact analysis on hydrological extremes in Belgium

Patrick WillemsKU Leuven – Hydraulics Division

Does the river Meuse change,

due to climate change ?

Is our climate changing?

Historical climate trends

Historical trend analysisWinter rainfall extreme quantiles Uccle (KMI/IRM, 10 min -> seasonal) 1898 –2007:

10

20

30

s [%

]

Global warming Global warming impactimpact1910s-1920s 1950s-1960s

1990s

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

year [-]

-50

-40

-30

-20

-10

0

10

anom

aly

in e

xtre

mes

winter, 10-year windowwinter, 15-year windowlong-term averageapproximate cyclic variationscyclic variations plus climate changeclimate change effect

Multidecadal Multidecadal climate oscillationclimate oscillation

Historical trend analysisWinter monthly river flow quantiles Meuse at Monsin since 1925, moving window of 15 years length:

20

25

30

Precipitation, Uccle

River flow, Meuse at Monsin

Multidecadal climate oscillations

1990s

-15

-10

-5

0

5

10

15

20

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

An

om

aly

[%

]

River flow, Meuse at Monsin

1910s-1920s 1950s-1960s

Multidecadal climate oscillations

(Anti-)correlations of climate oscillations across EuropeDaily rainfall ECA&D database:

-40

-20

0

20

40

60

80

1880 1900 1920 1940 1960 1980 2000

An

om

aly

[%

]

precipitation, Uccle

precipitation, Bologna

Multidecadal climate oscillations

Link with large-scale atmospheric circulation:

0

10

20

30

40

50

60

0

5

10

15

Pre

c. a

no

ma

ly [

%]

SLP

an

om

aly

[-]

SLP, Gibraltar - SLP, Haparanda(Sweden)

SLP, Gilbraltar - SLP, Vestervig(Denmark)

precipitation, Uccle

-40

-30

-20

-10

0

-15

-10

-5

Pre

c. a

no

ma

ly [

%]

SLP

an

om

aly

[

-40

-30

-20

-10

0

10

20

30

40

50

SLP

an

om

aly

[%

]

SLP, Reykjavik

SLP, Gibraltar

NAO+ NAO-

NAO+

10

20

30

mes

[%]

Multidecadal climate oscillations

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

year [-]

-50

-40

-30

-20

-10

0

anom

aly

in e

xtre

m

winter, 10-year windowwinter, 15-year windowlong-term averageapproximate cyclic variationscyclic variations plus climate changeclimate change effect

Future climate ?

?

10

20

30

mes

[%]

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

year [-]

-50

-40

-30

-20

-10

0

anom

aly

in e

xtre

m

winter, 10-year windowwinter, 15-year windowlong-term averageapproximate cyclic variationscyclic variations plus climate changeclimate change effect

Global climate models (GCMs)

European regional climate models (RCMs)

CCI-HYDR project

Belgian Science Policy Office

: climate change scenarios for impact

Climate models

Results for Belgium

: climate change scenarios for impact

analysis on hydrological extremes

in Belgium

• 44 runs with 21 global climate models

• 57 runs with 10 regional climate models

Control period: 1961-1990

Scenario period: 2071-2100

Statistical downscaling

Large Scale

Dynamical

General Circulation Models

(GCMs)150 – 300 km; seasonally – monthly

Hydrological scale

downscaling

Statistical downscaling

Regional Climate Models

(RCMs)

± 50 km; weekly - daily

± 25 km; daily

river catchment; hourly

Climate model results

Uccle, mean monthly temperature (1961-1990):

Climate model projections

Uccle, mean monthly temperature (1961-1990 -> 2071-2100):

summer:+2 to +7°C

winter:+1.5 to +4°C

Climate change

Temperature rise

Increase in greenhouse gases in the atmosphere

Air moisture at saturation point increases

Climate model projections

Uccle, monthly mean rainfall (1961-1990 -> 2071-2100):

winter:up to +60%

summer:up to -70%

no. rainy summer days:

up to -50%

Climate model projections

Uccle, extreme daily rainfall (summer, 1961-1990 -> 2071-2100):

Highest event in 10 years: up to +50%

Climate scenarios

Uccle, extreme daily rainfall (summer, 1961-1990 -> 2071-2100):

High

Fac

tor

rain

fall

chan

ge [-

]

Mean

Low

Return period [years]

Fac

tor

rain

fall

chan

ge [

1.25

1.3

1.35

SHMI-MPI-A2

SHMI-MPI-B2

CNRM-DE6DMI-ECC-A2

Regional climate model simulations

Consistency check with historical trend analysisExample: Uccle, winter daily rainfall extremes:

High = Wet

Climate scenarios

0.95

1

1.05

1.1

1.15

1.2

1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Per

turb

atio

n fa

ctor

DMI-ECC-A2

DMI-ECC-B2CNRM-DE5

ICTP-A2HS2 / HS3 / CNRM-DC9

SHMI-HC-B2ETH / HS1

CNRM-DE7 / SHMI-HC22GKSS-A2

GKSS-sn-A2 / METNO-A2SHMI-HC-A2

ICTP-B2DMI25 / KNMI

METNO-B2

Control period(1960-1990)

Scenario period(2070-2100)

Historical trend 30 years blocksize

Historical trend 30 years blocksize: part c.c. increase

Mean = Mild

Low = DryCurrent

Climate scenarios

Regional differences:Strong north – south variations Europa

minder droog in zomer:

Impact climate scenarios

Period from 1961-1990 to 2071-2100:• Winter:

� rainfall increase: 0 -> +60%� temperature & evaporation increase:

+1.5 -> 4°C• Summer:

� rainfall decrease: 0 -> -70%� rainfall decrease: 0 -> -70%� number of rainy days: 0 -> -50%� temperature & evaporation increase:

+2 -> 7°C� extreme intensities increase:

2-year event: 0 -> +30%10-year event: 0 -> +50%

• Coastal – polder area:rainfall change +10% higher

• Sea level rise Belgian Coast:20cm -> 2m

Comparison of downscaling methods

• Two completely different methods/assumptions lead to similar downscaling results!

High

Mean

Low

Direct precipitation results + quantile based climate factors

Extended weather typing technique (28 Jenkinson-Collison weather types + effect temperature rise)

1 day10 min 1 day10 min

• Day -> hour (river), 10-min (sewer system)• Based on quantile perturbations:

– change in rain storm frequency and rain storm intensity– dependent on return period rainfall intensity, season, weather type, …

• Time horizons till 2030, 2050, …, 2100

CCI-HYDR Perturbation Tool

Month i Month i Month i

Wet day frequencyperturbation

Wet day intensityperturbation

Combined perturbation

Time series

Time series

High = Wet

Mean = Mild

Low = Dry

DailyHourly10min

CCI-HYDR Perturbation Tool

• Preserves physical consistency (dependency) between seasons and variables (precipitation, temperature and ETo)

Day-Winter1.4

Day-Summer1.4Winter Summer

0.4

0.6

0.8

1

1.2

0.8 1 1.2 1.4 1.6 1.8

Eto Perturbation [-]

Rai

nfal

l Per

turb

atio

n [-

]

High Mean Low

0.4

0.6

0.8

1

1.2

0.8 1 1.2 1.4 1.6 1.8

Eto Perturbation [-]

Rai

nfal

l Per

turb

atio

n [-

]

ETo change factor ETo change factor

Pre

cip.

cha

nge

fact

or

Pre

cip.

cha

nge

fact

or

High Mean Low

Hydrological impact modelling

Rainfall, ETo

Rainfall-runoffNAM, PDM: conceptual

Spatially distributed:SCHEME (KMI/IRM), MIKE-SHEWetSpa (VUB)

River hydrodynamics

Physico-chemical riverwater quality

WetSpa (VUB)

MIKE11InfoWorks-RS+ quasi 2D overstromingen

Spills

Calculation nodesnumerical scheme

Right floodplainLeft floodplain

Bridge over tributary(culvert + weir)

MAIN RIVER

TRIBUTARY

MIKE11 EcoLab

• New method for testing the accuracy of the rainfall-runoff models in making extrapolations to more extreme rainfall conditions:

Hydrological model testing

• Data-based checking of the model structure:

Hydrological model testing

• Data-based checkingof the shape of the tail of the extreme value distribution:

Hydrological model testing

• Data-based checkingof the shape of the tail of the extreme value distribution:

Hydrological model testing

Impact of climate scenarios on hourly runoff peaks:

Hydrological impact

40

60

80

varia

tie p

ieka

favo

eren

(%))

)

High Mean Low

Cha

nge

in r

iver

pea

k flo

ws

[%]

High Mean Low

-40

-20

0

20

0.1 1 10 100

Terugkeerperiode (jaar)

varia

tie p

ieka

favo

eren

(%))

)

Return period [years]

Cha

nge

in r

iver

pea

k flo

ws

[%]

precip.increase ETo

increase

• Impact of climate scenarios on hourly runoff peaks:

Hydrological impacts

(-70%) - (-50%)(-49%) - (-30%)(-29%) - (-22%)(-21%) - (-13%)(-12%) - 0

Low scenario, Runoff peaks RUNOFF PEAKS

01% - 22%23 %- 24%25 %- 32%33% - 37%

High scenario, Runoff peaks

Climate 2100, Flanders

→ Change in flood risks is highly uncertain→ Runoff peaks due to rainfall/ETo change decrease in low

scenario and increase in high scenario (up to 35%)→ Major influence due to sea level rise (Scheldt tidal river)

• Impact of climate scenarios on low flows extremes:

Hydrological impacts

Low scenario, Runoff peaks LOW FLOW PEAKS

(-88%)(-87%) - (-68%)(-67%) - (-63%)(-62%) - (-55%)(-54%) - (-48%)

Low scenarioLow scenario, Runoff peaks LOW FLOW PEAKS

(-88%)(-87%) - (-68%)(-67%) - (-63%)(-62%) - (-55%)(-54%) - (-48%)

Low scenario

High scenario, Runoff peaks

Climate 2100, Flanders

(-35%) - (-32%)(-31%) - (-24%)(-23%) - (-21%)(-20%) - (-15%)(-14%) - (-10%)

High scenarioHigh scenario, Runoff peaks

Climate 2100, Flanders

(-35%) - (-32%)(-31%) - (-24%)(-23%) - (-21%)(-20%) - (-15%)(-14%) - (-10%)

High scenario

→ Low flow risks increase significantly in all scenarios→ May increase problems rel. water quality, navigation, drinking water production,

irrigation, industrial cooling water availability, groundwater table decreases, groundwaterquality decreases (oxygen reactions), ecological state river valley changes, ...

(-54%) - (-48%)(-54%) - (-48%)

Hydrological model testing

MIKE-SHE

• Impact on peak flow extremes 2071-2100:

Model intercomparison

HighMeanLow

30 to 70% increase

• Impact on low flow extremes 2071-2100:

Model intercomparison

HighMeanLow

40 to 70% decrease40 to 70% decrease

Some papers

• Ntegeka V., Willems P. (2008), ‘Trends and multidecadal oscillations in rainfall e xtremes, based on a more than 100 years time series of 10 minutes rainf all intensities at Uccle, Belgium ’, Water Resources Research, 44, W07402

• Baguis P., Roulin E., Willems P., Ntegeka V. (2009), ‘Climate change scenarios for precipitation and potential evapotranspiration over central Belgium ’, Theoretical and Applied Climatology, 99(3-4), 273-286

• Baguis P., Roulin E., Willems P., Ntegeka V. (2010), ‘Climate change and hydrological extremes in Belgian catchments ’, Hydrol. Earth Syst. Sci. Discuss., 7, 5033-5078

• Willems P., Vrac M. (2011), ‘Statistical precipitation downscaling for small-sca le hydrological impact investigations of climate change ’, J. Hydrol., 402, 193–205

• Van Steenbergen, N., Willems, P. (2012), ‘Method for testing the accuracy of rainfall -runoff models in • Van Steenbergen, N., Willems, P. (2012), ‘Method for testing the accuracy of rainfall -runoff models in predicting peak flow changes due to rainfall change s, in a climate changing context ’, Journal of Hydrology, 414-415, 425-434

• Dams, J., Salvadore, E., Van Daele, T., Ntegeka, V., Willems, P., Batelaan, O. (2012). ‘Spatio-temporal impact of climate change on the groundwater system ’, Hydrol. Earth Syst. Sci., 16, 1517-1531

• Vanuytrecht, E., Raes, D. Willems, P. (2011), ‘Considering sink strength to model crop production under elevated atmospheric CO2 ’, Agricultural and Forest Meteorology, 151(12), 1753-1762

• Vanuytrecht, E., Raes, D., Willems, P., Geerts, S. (2012), ‘Quantifying field-scale effects of elevated carbon dioxide concentration on crops ’, Climate Research, 54, 35-47

• Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Willems, P., De Smedt, F., Batelaan, O. (in press), ‘Climate change impact on river flows and catchment hydrolog y: a comparison of two spatially distributed models ’, Hydrological Processes; doi: 10.1002/hyp.9480

• Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012), ‘Impacts of climate change on rainfall extremes and urban drainage ’, IWA Publishing, 252p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263

More floods?

More low flow problems !

• Drier summers may have severe impact• Mean water availability in Flanders and Brussels is very

limited: 1480 m3/(person.year)– International standards:

Water availability

Study prof. K. Walravens U.Gent:

On some locations in Flanders the deep groundwater reduced with more than 140 m below the natural levels

Topography, isolines of aquifer piezometric level and piezometric level –

area in the “Sokkel” Aquifer in Southwest Flanders (view from the South)

“Sokkel” systemIn the main depression area of Southwest Flanders the groundwater abstraction needs to be reduced to about 25% of the current abstraction permission (anno 2000), in order to improve the situation and to avoid that the aquifer levels will further reduce on the long term (next 50 years)

Water quality

More info

Research project CCI-HYDR on“Impact of climate change on hydrological extremes (peak and low flows) along rivers (Scheldt and Meuse basins) and urban drainage systems in Belgium”(for Belgian Science Policy Office):

http://www.kuleuven.be/hydr/CCI-HYDR

Impact studies:Instituut voor Natuur- en Bosonderzoek (INBO):http://http://www.inbo.be

Vlaamse Overheid:Waterbouwkundig Laboratorium: http://www.watlab.beVlaamse Milieumaatschappij:http://www.milieurapport.behttp://www.watertoets.be/publicaties