1. Applying probabilistic scenarios to environmental management and resource assessment Rob Wilby Climate Change Science Manager rob.wilby@environment-agency.gov.uk

2. Adaptation can involve costly and difficult decisions...

3. …involving development of major assets

4. Climate model uncertainty and adaptation response... Downscaled precipitation scenarios for the River Thames under A2 emissions in the 2050s

5. Wider policy drivers Shaping adaptation in the UK EU Directives (e.g., Groundwater, Landfill, Water Framework) UK Government Adaptation Policy Framework Planning (e.g., CFMPs, SMPs, AMP, BAPs, PPS25) Guidance (e.g., Defra flood factor) Land use issues are identified as a priority area for embedding climate change in Agency policy and process. Photo: Philip Owen

6. Talk outline Derwent reservoir during the 1995 UK drought. Photo courtesy of Nick Jackoby The plan Using a multi-model ensemble to evaluate adaptation options Components of uncertainty affecting river flow projections Future plans and challenges of using probabilistic information Concluding remarks

7. Using multi-model ensembles: Appraisal of adaptation options for the River Kennet

8. Long-term nutrient enrichment of the River Thames, 1930-2000

9. ‘Luxuriant’ macrophyte growth

11. Statistical DownScaling Model (SDSM) and predictor variable archive http://www.sdsm.org.uk/

12. Downscaled daily precipitation for the River Kennet under A2 emissions by the 2080s illustrating the relative aridity of the HadCM3 GCM Changes in daily precipitation downscaled from each GCM

13. CATCHMOD daily river flow changes under A2 emissions Daily precipitation and PE downscaled for the River Kennet using three GCMs for the 2080s

14. INCA-N model of soil and instream nutrient concentrations

15. INCA-N simulation of Nitrate-N under A2 emissions: headwater Concentrations exceeded 5% of the time

16. Appraisal of adaptation options Five scenarios Baseline conditions under HadCM3 A2 emissions Fertiliser use reduced by 50% Deposition of atmospheric pollutants reduced by 50% Water meadow creation (4 x surface area of river) Combined approach with 25% reduction in fertiliser and deposition, water meadow creation (2 x surface area)

17. Simulation of adaptation outcomes under HadCM3 A2 emissions Concentrations exceeded 5% of the time

18. Summary (part 1) Large uncertainty in projected (summer) climate due to GCM HadCM3 : lower river flows, deployable yield, nutrient flushing following prolonged drought, and general decline in water quality CGCM2 : wetter summers, more deployable yield, greater reliability, stabilising water quality beyond 2050s Differences between A2 and B2 emissions relatively small Effectiveness of strategies: reduce fertiliser (or land use) > water meadow creation > reduced atmospheric deposition Combined approach sustains water quality at 1950s level even under climate change projected by HadCM3

19. Probabilistic framework: Assessing uncertainties in low flows for the River Thames

20. The ‘cascade’ of uncertainty affecting low flow projections Future society Emissions pathway Climate model Regional scenario Impact model Impact

21. Uncertainties due to GCM/ downscaling pair

22. An Impacts Relevant Climate Prediction Index This IR-CPI is based on the skill of the GCM/downscaling pair for effective rainfall in the Thames basin

23. Uncertainty due to low flow model structure Derived from observed daily rainfall and PE

24. Uncertainty due to water resource model parameters Identifiability - high

25. 4x GCMs, 2x emissions, 2x downscaling methods, 2x low flows models, 100x parameter sets Weight GCMs by modified Climate Prediction Index Weight low flow model structures by r adj statistic Weight low flow model parameters by N-S score Emissions and downscaling method unweighted Monte Carlo simulation (2000+ runs) Evaluate using (Q95) low-flow index for River Thames An experimental framework for assessing uncertainties

26. Uncertainties due to emission scenario

27. Uncertainties due to GCM

28. Uncertainties due to downscaling method

29. Uncertainties due to low flow model structure

30. Uncertainties due to low flow model parameters (HadCM3, A2)

31. Combining all sources of uncertainty

32. Summary (part 2) Conditional probabilities of lower summer river flows in the Thames by the 2080s

33. Next steps: Preparing the way for the UKCIPnext probabilistic scenarios

34. Impacts assessment using ClimatePrediction.net archive Frequency distribution of global mean temperature response to doubled CO 2 produced by CP.net, compared with IPCC (2001) range.

35. Reviewing Defra’s 20% allowance for future flood risk Variations in the 20-year flood by the 2050s under the UKCIP02 Medium-High emissions scenario Source: Reynard et al. (2004)

36. Incorporating probabilities in flood maps & planning guidance Changes in the extent of the 0.5% tidal flood between 2000s (green) and 2050s (red line). Source: Tim Hunt

37. Probabilistic climate change information is increasingly becoming available Planning and asset management will need to make best use of new forms of climate change information Risk-based modelling frameworks must be developed to inform adaptations responses Developing guidance on the use of conditional probabilities will be a critical part of this process Concluding remarks

38. A few words of wisdom “ If there is even a small risk that your house will burn down, you will take care to install smoke alarms and buy insurance. We can scarcely do less for the well-being of our society and the planet’s ecosystems ” Spencer Weart (2003: 199 )