Flooding and Climate Change

Stephan Harrison

Associate Professor in Quaternary Science University of Exeter

Director: Climate Change Risk Management www.ccrm.co.uk

Thanks to:

• Professor Mark Macklin

• Professor Ian Foster

• Dr Matt Wilson

Structure

• Climate Change

• Flooding and Flash flooding

• Some problems with assessing flood and frequency (e.g. short term data)

• Will floods get worse?

• UKCP09 Projections

• Model uncertainty

Climate Change: Detection

Bottom: estimate of uncertainty for one dataset (black). Anomalies are relative to the mean of 1961-1990.

Maps of CMIP5 multi-model mean results for the scenarios RCP2.6 and RCP8.5 in 2081– 2100 of: (a) annual mean surface temperature change; (b) average percent change in annual mean Precipitation; (c) Northern Hemisphere September sea ice extent and (d) change in ocean surface pH. For panels (a) and (b) hatching indicates regions where the multi-model mean is small compared to internal variability. In panel (c), the lines are the modelled means for 1986-2005; the filled areas are for the end of the century.

Flood risk and climate change

Anthropogenic factors: Increasing population; More building in flood prone areas; Insufficient flood protection

Flooding predicted to become more severe under climate change: flood prone areas will increase in size (especially in deep valleys?)

Change in magnitude and frequency

Changes in location of flood-prone areas (city centres etc)

Flooding: What makes them worse?

• Basic Catchment Hydrology (Shape / steepness, degree of urbanisation, soil permeability, land use and management etc.).

• River Network Characteristics (Stability, length, existence of land drains etc).

• Channel characteristics (Stability, gradient, roughness, existence of flood control works, washland schemes etc.).

Has The Dominant Input (Rainfall) Changed?

Modelling cannot tell us precisely what will happen, but an analysis of existing rainfall data might help us to understand what has happened and what changes we might see in the future. It may also help us to test climate change models.

Trends in Annual Rainfall Central London

1900 1925 1950 1975 2000

300

350

400

450

500

550

600

650

700

750

800

850

900

Calendar Year

An

nu

al

Rain

fall

(m

m)

Cornwall

1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

400

500

600

700

800

900

1000

1100

1200

1300

1400

1500

Petworth Annual

Ann

AnnMovAv

Year

Rain

fall

(m

m)

Petworth Park, Sussex

y = 4.0467x - 6671.5

R = 0.4

y = 4.2568x - 7523.7

R = 0.5

y = 0.6613x - 735.43

R = 0.1

300

600

900

1200

1500

1800

1930 1940 1950 1960 1970 1980 1990 2000 2010

YearR

ain

fall (

mm

)

Annual

Summer

Winter

Linear (Annual)

Linear (Winter)

Linear (Summer)

(Source: Dr David Watkins)

London Monthly & Seasonal Rainfall

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

0

10

20

30

40

50

60

70

80

90

100

1961-2006

1905-1960

Month

Ra

infa

ll (

mm

) (+

/- 1

SD

)

Winter(NDJ) Spring(FMA) Summer(MJJ) Autumn (ASO)

0

20

40

60

80

100

120

140

160

1801961-2006

1905-1960

Season

Seaso

nal

Rain

fall

(m

m)

Monthly

Seasonal

Frequency of High Magnitude Daily Rainfalls in Central London

0 0.25 0.5 0.75 1 1.25 1.5 1.75 2

0

10

20

30

40

50

60

B. 1961-2006

Log(10) Return Period (yr)

Dail

y R

ain

fall

(m

m)

0 0.25 0.5 0.75 1 1.25 1.5 1.75 2

0

5

10

15

20

25

30

35

40

45

50

55

A. 1905-1960

Log(10) Return Period (yr)

Dail

y R

ain

fall

(m

m) Daily rainfall with return period of

1 yr has increased from ca. 25mm to ca. 29 mm.

Daily rainfall with a return period of 10 yr has increased from ca. 40 mm to ca. 44 mm

London > 20 mm Days

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

A. Days > 20 mm rainfall

1961-2006

1901-1960

Month

An

nu

al

Fre

qu

en

cy E

xceed

ed

(d

ays/y

r)

1961-2006 1901-1960

0

1

2

3

A. Average Number of Days per year > 20mmN

o.

Days/Y

ear

Frequency of Days > 20 mm by Month

Frequency of Days > 20 mm by Year

London > 30 mm Days

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

0.00

0.03

0.05

0.08

0.10

0.13

0.15

0.18

0.20

B. Days > 30 mm rainfall

1961-2006

1905-1960

Month

An

nu

al

Fre

qu

en

cy E

xceed

ed

(d

ays/y

r)

1961-2006 1905-1960

0.0

0.2

0.4

0.6

0.8

1.0

B. Average Number of Days per year > 30mm

Nu

mb

er

of

Days/y

ear

Frequency of Days > 30 mm by Month

Frequency of Days > 30 mm by Year

London > 40 mm Days

Jan Feb Mar Apr May Jun Jul Aug Sept

Oct Nov Dec

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

C. Days > 40 mm rainfall

1961-2006

1905-1960

Month

Sta

nd

ard

ised

Ev

en

t F

req

uen

cy

1961-2006 1905-1960

0.00

0.03

0.05

0.08

0.10

0.13

0.15

0.18

0.20

0.23

0.25

0.28

0.30

C. Average Number of Days per year > 40 mmS

tan

dard

ised

Ev

en

t F

req

uen

cy

Frequency of Days > 40 mm by Month

Frequency of Days > 40 mm by Year

Flash flood characteristics

• Occur suddenly – little time for warning

• Fast-moving and generally violent – threat to life and severe damage to infrastructure

• Generally small in scale regarding area of impact

• Frequently associated with other events – riverine floods and mudslides

• They are rare but will probably increase in magnitude and frequency

Flash flooding in Boscastle, UK

Boscastle: Introduction and vulnerability

• River Jordan flows into R. Valency in center of Boscastle.

• Small catchment : 7.7 square miles

• But Steeply sloping – rises over 300 meters in 6km.

• Thin soils • Impermeable Bedrock: high

amounts of runoff. • High sediment supply:

reduces channel capacity • Human Impact

– Arched bridges over river collect debris

– Sewer pipe reduces channel capacity

Boscastle: A History of Flooding • 28th October 1827 “the whole street was

filled with a body of water rolling down & carrying all materials with -devastation & ruin were its concomitants”

• 6th September 1950: Whole trees uprooted, block river and cause flood

• 3rd June 1958: River Valency rose 4.5m in 20 minutes. 1 fatality.

• 6th Feb 1963. Flood caused by melting snow.

• 24th August 2004: worst floods in recent history. – 6 buildings washed away ( many more

reported unsafe) – 100 cars washed away – 75 people rescued by helicopter – Infrastructure (roads, bridges & sewers

damaged

Boscastle: August 2004 Flood

• Floods caused by a “train” of slow moving thunderstorms travelling up the north Cornwall coast.

• Storms dropped 181mm of rain in Trevalec, and 200mm in Otterham.

• Caused an estimated 440 million gallons of water to flow through Boscastle

3.45pm: 15mm rain in 5 minutes

Flood risk in Boscastle

• Risk to People: Short return period, deep, fast flowing and rapidly rising

• Risk to Property: Structural damage, and deposition of silt

• Risk of Blight: Tourists stay away

• Risk to the Environment: Damage to Conservation area and historic buildings.

Recent river flooding in the UK: are floods becoming more frequent and larger? Scientific challenges for long-term river flood risk assessment: (i) extending the flood record and establishing its relationship to climate change (ii) developing geomorphological scenarios of river channel and floodplain responses to climate change. Adapting to Climate Change - EA’s advice for river flood risk management authorities: provision of change factors & H++ scenarios. Expert in this is Professor Mark Macklin

Problems with assessing flood risk: short term records

York: Millennium Floods, Autumn 2000

Boscastle: August 2004 Tewkesbury: July 2007 Cumbria: November 2009

Over the last decade a series of major floods in the UK have lead many environmental protection agencies, politicians and members of the general public to believe that floods are becoming more frequent and larger. Recent floods are viewed as unprecedented and are attributed by many to anthropogenically caused climate change. Is this really true?

Mid-Wales floods June 8th and 9th 2012

Country Most recent data

submitted to

GRDC in

Average length

of daily flow

records (years)

Country Most recent data

submitted to

GRDC in

Average length

of daily flow

records (years)

Algeria 2003 20 Malaysia 2000 25

Australia 2002 43 Mali 2006 32

Austria 2001 41 Mexico 2003 42

Belarus 2002 8 Namibia 2007 39

Benin 2000 34 Netherlands 2006 36

Botswana 2001 12 New Zealand 2004 39

Canada 2006 41 Niger 2006 24

Central African

Republic 2005 10 Nigeria 2006 30

China 2004 13 Oman 2003 19

Cote D'Ivoire 2001 16 Panama 2003 36

Cyprus 2003 35 Puerto Rico 2003 29

Czech Republic 2000 61 Romania 2003 57

Denmark 2004 45 Russia 2004 24

Ecuador 2005 32 Serbia 2003 10

Finland 2004 60 Slovakia 2001 61

Germany 2004 75 Slovenia 2003 44

Ghana 2007 25 South Africa 2001 48

Guinea 2002 24 Sweden 2003 35

Iceland 2002 49 Switzerland 2003 74

Ireland 2007 38 Thailand 2000 13

Japan 2000 9

United

Kingdom 2004 45

Latvia 2006 23

United States of

America 2006 64

Lithuania 2004 53 Zambia 2005 35

Gauged river flow records in the UK are remarkably short (average length 45 yrs) and many catchments in upland and sparsely populated areas are un-gauged. Estimating the magnitude of a 1-in-100 (1%) annual probability flood event with 45 yrs of record is therefore problematic.

Shortest record!

Longest record!

UK

The longest gauged records (e.g. Wye & Thames) do not show consistent patterns. Statistical analysis employed is usually simplistic and fits ‘trends’ in terms of a straight line fit or smoothed sinusoidal curve.

But variations in flow regime are more usually in the form of a step shift, related to abrupt changes in atmospheric circulation (North Atlantic Oscillation, NAO) that control storm frequency and type.

(A) Documented extreme floods in Yorkshire Dales

(B) River Ouse flood record at York (gauge record in black, documentary record in grey)

Documentary sources

Can we extend the flood record: documentary sources and sediments?

Boulder Berms produced by extreme flood events that can dated using lichenometry. 400+ lichen-dated boulder berm flood units in upland England and Wales (AD 1630-present)

A 3700 year record of overbank flooding

Abrupt (decadal?) switches in extreme event frequency

Corresponds to climate signal

Flood sediment record captures century-

scale change

Upper Severn, Welshpool

Key assumptions underpinning this is that peak river flows in the pre-instrumental period have not been larger than the predicted H++ % changes. Recent research shows that this assumption may not hold especially in catchments that have upland headwaters.

H++ scenarios also do not take into consideration channel erosion, deposition and movement that significantly alter inundation extents and patterns, even if flood peaks remain constant.

Adapting to Climate Change - EA’s advice for river flood risk management authorities: provision of change factors & H++ scenarios.

Arbitrary dates (2039/40, 2069/70 and 2099/2100) have been used for when modelled changes in peak flows are predicted to occur. The timing of these will bear little or no resemblance to what is likely to happen as a result of shifts in atmospheric circulation, for example associated with the North Atlantic Oscillation that strongly influences flood frequency and magnitude in the UK.

Will floods get worse?

• YES. Clausius-Clapeyron: maximum

possible concentration of water vapour (absolute humidity) decreases exponentially with falling temperature and pressure

IVT in kg/m/s from 6 models

Other issues: Erosion and water quality

Soil erosion – long term deterioration in soil productivity; Muddy Floods – damage to properties and transport infrastructure; Deterioration in water quality; River Siltation (EUWFD); Reservoir Sedimentation.

Rother Catchment Erosion 2006 Photos courtesy of John Boardman, ECI, Oxford University

Under the Highways Act (1980) farmers can be

charged the cost of road clearance or required

to take action to prevent recurrence. This is

rarely enacted in Britain (Boardman, 1994).

York, autumn 2000

Flood sediments autumn 2000

Macklin 2010

Climate scenarios:

Climate model

Hydrological change:

Catchment hydrology model

Change in flood risk:

Flood inundation model:

Probability of flooding

+

Loss estimation

Risk map

Assessing future flood risk: uncertainties

Increasing uncertainty

CMIP uncertainty

Model uncertainty

Different climate models

will produce a different

climate response even

when forced by an

identical emissions

scenario

UKCIP02 scenarios are

“drier” over UK than

some other climate

models

2020s 50% probability level: central estimate High emissions

Do we believe this?

Conclusions

• Floods will get worse

• You will have to adapt

• There may be insurance consequences

• A risk management approach is needed.

• Models are poor at resolving precipitation