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Dr. Alan F. Hamlet Climate Impacts Group Dept. of Civil and Environmental Engineering

Effects of Observed Climate Variability and Climate Change on Flooding i n the Pacific Northwest. Dr. Alan F. Hamlet Climate Impacts Group Dept. of Civil and Environmental Engineering University of Washington. Climate Impacts Group Research Team Lara Whitely Binder Pablo Carrasco

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Dr. Alan F. Hamlet Climate Impacts Group Dept. of Civil and Environmental Engineering

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  1. Effects of Observed Climate Variability and Climate Change on Flooding in the Pacific Northwest • Dr. Alan F. Hamlet • Climate Impacts Group • Dept. of Civil and Environmental Engineering • University of Washington

  2. Climate Impacts Group Research Team Lara Whitely Binder Pablo Carrasco Jeff Deems Marketa McGuire Elsner Alan F. Hamlet Carrie Lee Se-Yeun Lee Dennis P. Lettenmaier Jeremy Littell Guillaume Mauger Nate Mantua Ed Miles Kristian Mickelson Philip W. Mote Rob Norheim Erin Rogers Eric Salathé Amy Snover Ingrid Tohver Andy Wood http://www.hydro.washington.edu/2860/products/sites/r7climate/study_report/CBCCSP_chap1_intro_final.pdf

  3. Overview of Research Interests: • Land surface hydrology and modeling (Elsner et al. 2010; Hamlet and Lettenmaier 2005; Hamlet et al. 2005, 2007; Leung et al. 1999; Mote et al. 2005; Painter et al. 2010) • Integrated hydrological and water resources modeling (Hamlet and Lettenmaier 1999a; Miles et al. 2000; Payne et al. 2004; Vano et al. 2010) • Water resources planning and management (Hamlet 2003; Lee et al. 2009, 2011a,b; Miles et al. 2000; Payne et al. 2004; ) • Flooding and assessment of hydrologic extremes (Hamlet and Lettenmaier 2007; Mantua et al. 2010; Lee et al. 2009, 2011a,b) • Impacts of climate variability and climate change on hydrology and water resources (Hamlet and Lettenmaier 1999a; Hamlet and Lettenmaier 1999b; Miles et al. 2000; Mote et al. 2003; Adam et al. 2009; Elsner et al. 2010) • Sustainable water resources management and climate change adaptation strategies (Miles et al. 2000; Hamlet 2003; Snover et al. 2003; Slaughter et al. 2010; Whitely Binder et al. 2010; Hamlet 2010 )

  4. Research Interests (cont): • Long-lead climate and streamflow forecasts and related water resources applications (Hamlet and Lettenmaier 1999b; Hamlet et al. 2002; Voisin et al. 2006; Lee et al. 2011b) • Modeling of freshwater, and estuarine ecosystems (Crozier et al. 2008; Wenger et al. 2010, 2011; Mantua et al. 2010) • Forest hydrology and impacts to terrestrial ecosystems (Littell et al. 2010) • Paleoclimaticprecipitation and streamflow reconstruction (Lutz et al. 2012) • Climate impacts on hydropower and energy systems (Hamlet and Lettenmaier 1999a, Hamlet et al. 2002; Voisin et al. 2006; Hamlet et al. 2010) • Climate services (Gamble et al. 2002; Snover et al. 2003)

  5. Overview of Research Interests: • Land surface hydrology and modeling (Elsner et al. 2010; Hamlet and Lettenmaier 2005; Hamlet et al. 2005, 2007; Leung et al. 1999; Mote et al. 2005; Painter et al. 2010) • Integrated hydrological and water resources modeling (Hamlet and Lettenmaier 1999a; Miles et al. 2000; Payne et al. 2004; Vano et al. 2010) • Water resources planning and management (Hamlet 2003; Lee et al. 2009, 2011a,b; Miles et al. 2000; Payne et al. 2004; ) • Flooding and assessment of hydrologic extremes (Hamlet and Lettenmaier 2007; Mantua et al. 2010; Lee et al. 2009, 2011a,b) • Impacts of climate variability and climate change on hydrology and water resources (Hamlet and Lettenmaier 1999a; Hamlet and Lettenmaier 1999b; Miles et al. 2000; Mote et al. 2003; Adam et al. 2009; Elsner et al. 2010) • Sustainable water resources management and climate change adaptation strategies (Miles et al. 2000; Hamlet 2003; Snover et al. 2003; Slaughter et al. 2010; Whitely Binder et al. 2010; Hamlet 2010 )

  6. The Myth of Stationarity: 1) Climate Risks are stationary in time. 2) Observed streamflow records are the best estimate of future variability. 3) Systems and operational paradigms that are robust to past variability are robust to future variability.

  7. The Myth of Stationarity Meets the Death of Stationarity Muir Glacier in Alaska Aug, 13, 1941 Aug, 31, 2004 Image Credit: National Snow and Ice Data Center, W. O. Field, B. F. Molnia http://nsidc.org/data/glacier_photo/special_high_res.html

  8. Why a Focus on Hydrologic Extremes? Many human and natural systems are quite robust under “normal” conditions, but have the potential to be profoundly impacted by hydrologic extreme events.

  9. Public Safety and Economic Impacts

  10. Damage to Infrastructure Nisqually River at Sunshine Point (Nov, 2006) http://www.nps.gov/mora/parknews/upload/flooddamagev3.pdf

  11. Sediment Transport and Mudslides

  12. Nuts and Bolts: Traditional Methods for Estimating Hydrologic Extremes

  13. Step 1: Select Extreme Event from Each Historical Year Streamflow (cfs) Day of the Water Year (1 = Oct 1)

  14. Step 2: Rank Extreme Events for All Years and Estimate Quantiles 1999 Streamflow (cfs) Probability of Exceedance

  15. Step 3: Fit a Probability Distribution to the Data • Examples of Commonly Used Probability Distributions: • Extreme Value Type 1 (EV 1) • Log Normal (LN) • Log Pearson • Generalized Extreme Value (GEV) • For climate change experiments, GEV is a good choice since the true nature of the future probability distributions is essentially unknown. However it turns out that the choice of distribution is not very critical in terms of the evaluating the sensitivity to warming and/or precipitation change.

  16. Step 4: Estimate Extremes Associated with Return Intervals Site Name Ret. Int. Flow (cfs) SNOMO : 20 68660 SNOMO : 50 81332 SNOMO : 100 91145 Note that any return interval can be estimated. E.g. one could provide an estimate of the “5000 year flood”, albeit with large uncertainty.

  17. Historical Perspectives: Changing Flood Risk in the 20th Century

  18. References: Neiman, P.J., L.J. Schick, F.M. Ralph, M. Hughes, and G.A. Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers. J. of Hydrometeorology, 12, 1337–1358 Hamlet A.F., D.P. Lettenmaier, 2007:Effects of 20th century warming and climatevariability on flood risk in the western U.S. Water Resour Res, 43:W06427.doi:10.1029/2006WR005099

  19. Observed Characteristics of Extreme Precipitation Events

  20. Evidence of Changing Flood Statistics

  21. Role of Atmospheric Rivers in Flooding (Nov 7, 2006) Neiman, P.J., L.J. Schick, F.M. Ralph, M. Hughes, and G.A. Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers. J. of Hydrometeorology, 12, 1337–1358

  22. Role of Atmospheric Rivers in Flooding (Oct 20, 2003) Neiman, P.J., L.J. Schick, F.M. Ralph, M. Hughes, and G.A. Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers. J. of Hydrometeorology, 12, 1337–1358

  23. Modeling Studies of Changing 20th Century Flood Risk in the West

  24. Schematic of VIC Hydrologic Model Sophisticated, fully distributed, physically based hydrologic model Widely used globally in climate change applications 1/8th Degree Resolution (~50 km2) General Model Schematic Snow Model

  25. Evaluating the Hydrologic Model Simulations in the Context of Reproducing Flood Characteristics Ln (X100 / Xmean) OBS Avg WY Date of Flooding OBS Avg WY Date of Flooding VIC Ln (X100 / Xmean) VIC Red = PNW, Blue = CA, Green = Colo, Black = GB

  26. 100-yr Red = VIC Blue = OBS 50-yr X100 GEV flood/mean flood 20-yr 10-yr 5-yr Zp

  27. Regionally Averaged Temperature Trends Over the Western U.S. 1916-2003 Tmax PNW GB Tmin CA CRB

  28. Detrended Temperature Driving Data for Flood Risk Experiments “Pivot 2003” Data Set Temperature Historic temperature trend in each calendar month “Pivot 1915” Data Set 2003 1915

  29. Simulated Changes in the 20-year Flood Associated with 20th Century Warming DJF Avg Temp (C) X20 2003 / X20 1915 X20 2003 / X20 1915

  30. Schematic of a Cool Climate Flood Precipitation Produces Runoff Precipitation Produces Snow Precipitation Produces Snow Snow Snow Freezing Level Snow Melt

  31. Schematic of a Warm Climate Flood Precipitation Produces Runoff Precipitation Produces Snow Precipitation Produces Snow Snow Snow Snow Melt Freezing Level

  32. Regionally Averaged Cool Season Precipitation Anomalies PRECIP ftp://ftp.hydro.washington.edu/pub/jhamman/PNWCSC_2011/Poster2%20final.pdf

  33. 20-year Flood for “1973-2003” Compared to “1916-2003” for a Constant Late 20th Century Temperature Regime DJF Avg Temp (C) X20 ’73-’03 / X20 ’16-’03 X20 ’73-’03 / X20 ’16-’03

  34. Hypotheses Regarding 21st Century Flooding Impacts Rain Dominant Basins: Potential increases in flooding due to increased precipitation intensity, but no significant change from warming alone. Mixed Rain and Snow Basins Along the Coast: Strong increases in flooding due to warming and increased precipitation intensity (both effects increase flood risk) Inland Snowmelt Dominant Basins: Relatively small overall changes because effects of warming (decreased risks) and increased precipitation intensity (increased risks) are in the opposite directions. T P T P T P

  35. Effects of ENSO and PDO on Flood Risk

  36. X100 wENSO / X100 2003 X100 nENSO / X100 2003 X100 cENSO / X100 2003 DJF Avg Temp (C) DJF Avg Temp (C) DJF Avg Temp (C) X100 wENSO / X100 2003 X100 nENSO / X100 2003 X100 cENSO / X100 2003

  37. X100 wPDO / X100 2003 X100 nPDO / X100 2003 X100 cPDO / X100 2003 DJF Avg Temp (C) DJF Avg Temp (C) DJF Avg Temp (C) X100 wPDO / X100 2003 X100 nPDO / X100 2003 X100 cPDO / X100 2003

  38. Scenarios of Flood Risk in the 21th Century

  39. Consensus Forecasts of Temperature and Precipitation Changes from IPCC AR4 GCMs

  40. 21st Century Climate Impacts for the Pacific Northwest Region Mote, P.W. and E. P. Salathe Jr., 2010: Future climate in the Pacific Northwest, Climatic Change, DOI: 10.1007/s10584-010-9848-z

  41. Seasonal Precipitation Changes for the Pacific Northwest Mote, P.W. and E. P. Salathe Jr., 2010: Future climate in the Pacific Northwest, Climatic Change, DOI: 10.1007/s10584-010-9848-z

  42. http://www.hydro.washington.edu/2860/

  43. Columbia Basin Climate Change Scenarios Project 297 Sites • Smaller basins down to • ~500 km2 • Monthly and daily streamflow time series • Assessment of hydrologic extremes • (e.g. Q100 and 7Q10)

  44. Available PNW Scenarios 2020s – mean 2010-2039; 2040s – mean 2030-2059; 2080s – mean 2070-2099

  45. Hybrid Downscaling Method • Performed for each VIC grid cell: Bias Corrected Future Monthly CDF Hist. Daily Timeseries 30 yr window 1916-2006 Projected Daily Timeseries Historic Monthly CDF Hist. Monthly Timeseries 1916-2006 1970-1999 1916-2006 “Base Case”

  46. Spatial Variability of Temperature and Precipitation Changes

  47. Monthly to Daily Precipitation Scaling SeaTac. Feb, 1996, hypothetical 30% Increase Daily Precipitation (mm) Day of Month

  48. Schematic of VIC Hydrologic Model • Sophisticated, fully distributed, physically based hydrologic model • Widely used globally in climate change applications • 1/16th Degree Resolution (~5km x 6km or ~ 3mi x 4mi) General Model Schematic Snow Model

  49. Watershed Classifications: Transformation From Snow to Rain Map: Rob Norheim

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