Regional assessments of sea level rise and river floods by computer based expert systems: Dealing with uncertainty

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 How to deal with uncertainty in the adaptation discussion? Adaptation to sea level rise: Regional assessments via DIVA River floods assessment, limitations and Chances: The Vistula example Consequences for local adaptation policies Conclusion kropp@pik-potsdam.de

2. kropp@pik-potsdam.de Where are our „Achilles heels“: in the economic, natural, and social sense?

3. kropp@pik-potsdam.de Coast Lines Lower Saxony0-2000AD Source: Behre 1999

4. kropp@pik-potsdam.de „Miserable Waterflood in Lower-Germany 1717“ At the North sea coast dyke construction since 1100AD Reasons: Maladaptation! mainly landuse

5. kropp@pik-potsdam.de Back to Reality: River Elbe Flood 2002/Pärnu Storm Surge 2005

6. kropp@pik-potsdam.de 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?…..

7. kropp@pik-potsdam.de The DIVA Expert System

8. kropp@pik-potsdam.de Initial Settings for DIVA Runs Protection level: 1000yr/return level, storm surge/river flood Dike failure (breach) mode: wave overflow Tidal basin, nourishment: CBA Migration allowed due to changing env. conditions: yes Time steps of calculation: 5 yrs Simulation time: 2000-2100 Input SRES scenarios: A1FI („worst case“), B2 („best case“); regionalized SLR scenarios based on PIK‘s CLIMBER model (for each SRES family, low/medium/high-uniform/regionalized)

9. kropp@pik-potsdam.de Worst case: A1FI Best case: B2 Regional Sealevel Rise: 1995-2100SRES-A1FI/B2 How large the adaptation costs will be?

10. kropp@pik-potsdam.de Adaptation Costs: Sea Level Rise(dike construction & preservation, beach nourishment, etc.) Year 2000 Year: 2100

11. kropp@pik-potsdam.de A1FI: Most relevant for Estonia due to sandy beaches and no dikes Start-up investments to guarantee 1000yr protection level needed.... Total Adaptation Costs (Mio US$)

12. kropp@pik-potsdam.de River impact length (1000yr flood) A1FI B2

13. kropp@pik-potsdam.de Other Possible Things..... Salinity intrusion costs Sea dike costs River dike costs People actually flooded per storm surge Sand loss Loss of flats Beach nourishment costs Area influenced by salinization due to slr Tidal basin demand for sand nourishment .... Typical expert system which means that usage by stakeholders Needs involvement of experts for simulation runs and interpretation

14. kropp@pik-potsdam.de 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 worldwide Standard statistics is unsuitable for assessment tasks Adequate 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?

15. kropp@pik-potsdam.de Extremes? Trends and Extremes in Time Series Definition: A trend is a long-term movement which can be distinguished from oscillation and noise. x(t) = Trend(t) + Oscillations(t) + Noise(t)

16. kropp@pik-potsdam.de PRUDENCE Comparison1961/90 – 2075/2100, A2 Hadley Boundary

17. kropp@pik-potsdam.de Gauge: Daugava/Daugavapils (JJA) Linear trend in mean and variance (1,1,0 - obtained via model fit routines) Design flood values differ significantly! More torrential rain in summer: regime shift! Kallache/Rust/Kropp 2005: Nonlinear Processes in Geophysics

18. kropp@pik-potsdam.de Bootstrapping for Confining Uncertainty Gauge: Vistula/Tczew: Catchment: ~200.000 km2 Length: 1900-1994 Problem: data series too short! Huge model library (more than 50) Define model selection criteria Select best fitting model Generate bootstrap ensemble Perform statistics 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 Water Resources Res., under review

19. kropp@pik-potsdam.de My demand:Inclusion of these procedure into the daily practice

20. kropp@pik-potsdam.de Conclusion - Main Findings with Respect to Adaptation 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

21. kropp@pik-potsdam.de Climate Disruptions, Heart Attacks and Market Crashes We need a new science and planning for disasters.... Bunde/Kropp/Schellnhuber, Springer 2002