Gdansk Conference October 26-27th, 2006

kropp@pik-potsdam.de 1

Regional assessments of sea level rise and river floods by computer based expert

systems: Dealing with uncertainty

J. Kropp, M. Kallache, H. Rust, K. EisenackPotsdam Institute for Climate Impact Research

Structure

1. How to deal with uncertainty in the adaptation discussion?

2. Adaptation to sea level rise: Regional assessments via DIVA

3. River floods assessment, limitations and Chances: The Vistula example

4. Consequences for local adaptation policies

5. Conclusion

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Where are our „Achilles heels“: in the economic, natural,Where are our „Achilles heels“: in the economic, natural,and social sense? and social sense?

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Coast Lines Lower Saxony0-2000AD

Source: Behre 1999

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„Miserable Waterflood in Lower-Germany 1717“

At the North sea coastdyke construction since 1100AD

Reasons:Maladaptation!mainly landuse

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Back to Reality:

River Elbe Flood 2002/Pärnu Storm Surge 2005

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How to assess “protection level”

Wave overflow: Return level right Weser bank for current dyke heights (3900yr)Climate change scenario: average high tide + 70cm +3.8% increase of wind speed(return level 1000yrs).

(after Liedermann & Zimmermann 2003) COSTS? Secondary effects?…..

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The DIVA Expert System

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Initial Settings for DIVA RunsProtection levelProtection level: 1000yr/return level, storm surge/river flood: 1000yr/return level, storm surge/river floodDike failure (breach) modeDike failure (breach) mode: wave overflow: wave overflowTidal basin, nourishmentTidal basin, nourishment: CBA: CBAMigrationMigration allowed due to changing env. conditions: yes allowed due to changing env. conditions: yesTime steps of calculationTime steps of calculation: 5 yrs: 5 yrsSimulation timeSimulation time: 2000-2100: 2000-2100Input SRES scenariosInput SRES scenarios: A1FI („worst case“), B2 („best case“); : A1FI („worst case“), B2 („best case“); regionalized SLR scenarios based on PIK‘s CLIMBER modelregionalized SLR scenarios based on PIK‘s CLIMBER model(for each SRES family, low/medium/high-uniform/regionalized)(for each SRES family, low/medium/high-uniform/regionalized)

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Regional Sealevel Rise: 1995-2100SRES-A1FI/B2

How large the adaptationHow large the adaptationcosts will be?costs will be?

Best case: B2

Worst case: A1FI

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Adaptation Costs: Sea Level Rise(dike construction & preservation, beach nourishment, etc.)

Year 2000

Year: 2100

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Total Adaptation Costs (Mio US$)

A1FI: Most relevant for Estonia due to sandy beaches and no dikes

Start-up investmentsto guarantee 1000yrprotection levelneeded....

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River impact length (1000yr flood)

A1FI

B2

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Other Possible Things.....

Salinity intrusion costsSea dike costsRiver dike costsPeople actually flooded per storm surgeSand lossLoss of flatsBeach nourishment costsArea influenced by salinization due to slrTidal basin demand for sand nourishment....

Typical expert system which means that usage by stakeholders Typical expert system which means that usage by stakeholders Needs involvement of experts for simulation runs and interpretationNeeds involvement of experts for simulation runs and interpretation

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Improved Flood Risk Assessment

Retrospective on river run-offs: assumptions needed, e.g. climate change signal can be found in run-off data (trend = nonstationarity)

Main results:No uniform behaviour for rivers worldwideStandard statistics is unsuitable for assessment tasksAdequate analytical procedures can confine uncertainty

Examples (annual – stationary, implies no trends!): Odra/Gozdowice (109729 km2, Poland)Vistula/Tczew (194376 km2, Poland)Daugava/Daugavpils (64500 km2Latvia)Nemunas/Smalininkai (81200 km2 Lithuania)

But is this the end of the story?

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TrendTrendss and Extremes in and Extremes in Time SeriesTime Series

Extremes?

-2

-1

0

1

2

0 1 2 3 4 5

t

Definition:Definition: A trend is a long-term movement which can be A trend is a long-term movement which can be distinguished from oscillation and noise.distinguished from oscillation and noise.

x(t) = Trend(t) + Oscillations(t) + Noise(t)x(t) = Trend(t) + Oscillations(t) + Noise(t)

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PRUDENCE ComparisonPRUDENCE Comparison1961/90 – 2075/2100, A2 Hadley Boundary1961/90 – 2075/2100, A2 Hadley Boundary

T (°C)T (°C) P (%)P (%)

BSR Countries*BSR Countries*

(model mean)(model mean)

TTaa T (DJF)T (DJF) T(JJA)T(JJA) PPaa P(DJF)P(DJF) P(JJA)P(JJA)

DenmarkDenmark 1.11.1 1.01.0 1.11.1 2.42.4 9.89.8 -6.4-6.4

EstoniaEstonia 1.41.4 1.61.6 1.21.2 4.24.2 10.210.2 4.54.5

FinlandFinland 1.41.4 1.71.7 1.01.0 5.85.8 10.910.9 4.64.6

Germany NorthGermany North 1.21.2 1.11.1 1.31.3 0.10.1 6.06.0 -7.3-7.3

LatviaLatvia 1.41.4 1.61.6 1.21.2 3.23.2 9.79.7 1.81.8

LithuaniaLithuania 1.41.4 1.51.5 1.21.2 2.02.0 8.88.8 -1.1-1.1

PolandPoland 1.31.3 1.31.3 1.31.3 0.70.7 6.06.0 -4.0-4.0

Sweden NorthSweden North 1.31.3 1.51.5 1.01.0 5.35.3 9.09.0 2.72.7

Sweden SouthSweden South 1.21.2 1.31.3 1.11.1 3.53.5 11.411.4 -2.1-2.1

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Gauge: Daugava/Daugavapils (JJA)

Linear trend in meanand variance (1,1,0 - obtained via model fitroutines)

Design flood valuesdiffer significantly!

More torrential rainin summer: regime shift!

Kallache/Rust/Kropp 2005: Nonlinear Processes in Geophysics

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Bootstrapping for Confining Uncertainty

Results:Red: theory, asymptotic fit

Grey: bootstrap ensemble

100yr return level9

Estimates for „design flood values“ are too small (6-15% difference!)

Rust/Kallache/Kropp 2006: Advances in WaterResources Res., under review

Gauge: Vistula/Tczew:Catchment: ~200.000 km2

Length: 1900-1994

Problem: data series too short!1. Huge model library (more than 50)2. Define model selection criteria3. Select best fitting model4. Generate bootstrap ensemble5. Perform statistics

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My demand:Inclusion of these procedure into the daily

practice

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1. Improved technique integrated and views can reduce adverse impacts

2. Communities can adapt autonomously only partly, they need help

of scientists

4. Planned (anticipated )adaptation measures usually have immediate benefits

6. Adaptive capacity varies considerably among countries, regions and socio-economic groups

8. Enhancement of adaptive capacity is necessary to reduce vulnerability, especially for the most vulnerable (people,

regions…)

9. Current knowledge of adaptation & adaptive capacity is insufficient

10. Technical progress is essential for suitable adaptation

Conclusion - Main Findings with Respect to Adaptation

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Climate Disruptions,Heart Attacks and Market Crashes

We need a new scienceand planning for disasters....

Bunde/Kropp/Schellnhuber, Springer 2002