A Process-Based “Bottom-Up” Approach for Addressing Changing Flood-Climate Relationships

1. A Process-Based “Bottom-Up” Approach for Addressing Changing Flood-ClimateRelationships COHS Workshop National Academy of SciencesGlobal Change and Extreme Hydrology: Testing Conventional Wisdom January 5-6, 2010 Katie Hirschboeck

2. “GLOBAL CHANGE & EXTREME HYDROLOGY” How can water managers deal with events in the “tails” of streamflow probability distributions, both floods and droughts, . . .by moving beyond conventional wisdom and approaches . . . .

3. WESTERN WATER MANAGERS : are planning for future extreme LOW FLOW conditions using : -- tree-ring reconstructions -- simulations -- scenario-building -- climate projection modeling Water supply simulation based on extreme low flow sequences in the paleo-record STREAMFLOW RECONSTRUCTION for 1330-20052002 & 1996 = lowest annual flows in the entire record

4. In contrast . . . • FLOOD HAZARD MANAGERS: • have been more constrained in developing ways to incorporate climate change information operationally due to: • -- existing flood management policy and practices • -- the short-term, localized, and weather-based nature of the flooding process itself

5. What’s Needed: Information presented in an operationally useful formatfor flood managers which describes how changes in the large-scale climatic “drivers” of hydrometeorological extremes will affect flooding variability in SPECIFIC WATERSHEDS 

6. This presentation argues: • . . . that attention to some very basic elements at the local and regional watershed scale -- such as basin size, storm type, seasonality, atmospheric circulation patterns, and geographic setting • . . . can provide a basis for a cross-scale approach to linking GLOBALclimate variability with LOCALhydrologic variations . . .

7. In other words we will . . . . . . . let the rivers “speak for themselves” about how they respond to climate ! Santa Cruz River at Tucson, Arizona

8. OUTLINE • RE-EXAMINING CONVENTIONAL WISDOM & ASSUMPTIONS:The Standard iid Assumption for FFA • RE-THINKINGNew Insights from “Flood Hydroclimatology” • THE “BOTTOM-UP” APPROACHComplementary Upscaling • FINAL THOUGHTS

9. I. RE-EXAMINING

10. http://acwi.gov/hydrology/Frequency/B17bFAQ.html#mixed“Flood magnitudes are determined by many factors, in unpredictable combinations. It is conceptually useful to think of the various factors as "populations" and to think of each year's flood as being the result of random selection of a "population”, followed by random drawing of a particular flood magnitude from the selected population.”

11. The Standard iid Assumption for FFA The standard approach to Flood Frequency Analysis (FFA) assumes stationarity in the time series & “iid” “ iid ” assumption: independently, identically distributed

12. Storm type  hydrograph Summer convective event The type of storm influences the shape of a hydrograph and the magnitude & persistence of the flood peak This can vary with basin size (e.g. convective events are more important flood producers in small drainage basins) Synoptic-scale winter event Tropical storm or other extreme event

13. In addition, extreme flow events can emerge from synergism in: • The way in which rainfall is delivered • in both space (e.g., storm movement, direction) • and time (e.g., rainfall rate, intensity) • over drainage basins of different sizes & orographies from Doswell et al. (1996)

14. FLOOD-CAUSING MECHANISMS Meteorological & climatological flood-producing mechanisms operate at varying temporal and spatial scales

15. HYDROMETEOROLOGY Weather, short time scales Local / regional spatial scales  Forecasts, real-time warnings vs. HYDROCLIMATOLOGY  Seasonal / long-term perspective  Site-specific and regional synthesis of flood-causing weather scenarios  Regional linkages/differences identifiedEntire flood history context  benchmarks for future events

16. Re-Examining the “iid” Assumption It all started with a newspaper ad . . . .

17. THE FFA“FLOOD PROCESSOR” With expanded feed tube – for entering all kinds of flood data including steel chopping, slicing & grating blades– for removing unique physical characteristics, climatic information, and outliersplus plastic mixing blade – to mix the populations together

18. Time-varying variances Both SOURCE: Hirschboeck, 1988 Alternative Conceptual Framework: Time-varying means • Mixed frequency distributions may arise from: • storm types • synoptic patterns • ENSO, etc. teleconnections • multi-decadal circulation regimes

19. II. RE-THINKING

20. FLOOD HYDROCLIMATOLOGYis the analysis of flood events within the context of their history of variation - in magnitude, frequency, seasonality - over a relatively long period of time - analyzed within the spatial framework of changing combinations of meteorological causative mechanisms SOURCE: Hirschboeck, 1988

21. “ Bottom–Up ” Approach(surface-to-atmosphere) • Observed Gage Record • Meteorological / Mechanistic / Circulation-Linked • Flood Hydroclimatology Framework / Link to Flood Distribution Flood Hydroclimatology Approach

22. 3 EXAMPLES: Flood Hydroclimatology in AZ

23. Sample Distributions of Peaks-above-Base (Partial Duration Series) events: Are there climatically controlled mixed populations within?

24. All Peaks Tropical storm Winter Synoptic Sumer Convective Santa Cruz River at TucsonPeak flows separated into 3 hydroclimatic subgroups Hirschboeck et .al. 2000

25. What does this time series look like when classified hydroclimatically? What kinds of storms produced the biggest floods?

26. Hydroclimatically classified time series . . .

27. Verde River below Tangle Creek Peak flows separated into 3 hydroclimatic subgroups Tropical storm Winter Synoptic All Peaks Sumer Convective Hirschboeck et .al. 2000

28. Historical Flood

29. Empirical plotting positions computed separately for each hydroclimatic type Annual floodpeaks only: Sample frequency curve defined by plotting observed flood magnitudes vs their empirical probability plotting positions, separated by flood type Probability analysis based on hydroclimatically separatedflood series Alila & Mtiraoui 2002

30. Thinking Beyond the Standardiid Assumption for FFA . . . . Based on these results we can re-envision the underlying probability distribution function for Arizona floods to be not this . . . .

31. . . . but this: Alternative Model to Explain How Flood Magnitudes Vary over Time Schematic for Arizona floods basedon different storm types Varying mean and standard deviationsdue to different causal mechanisms

32. HOW MIGHT CLIMATE CHANGE AFFECT THESE DISTRIBUTIONS?

33. Change in Frequency or Intensity of Tropical Storms? Tropical storm Octave Oct 1983 Some Important Flood-Generating Tropical Storms Latitudinal Shifts inWinter Storm Track? Roosevelt Dam Jan 1993 Winter flooding on Rillito in Tucson More Intense Summer Monsoon? Sabino Creek July 2006

34. . . . or this: El Nino year Blocking Regime Zonal Regime La Nina year Conceptual Framework forCirculation Pattern Changes When the dominance of different types of flood-producing circulation patterns changes over time, the probability distributions of potential flooding at any given time (t) may be altered.

35. . . . or this: Conceptual Framework for Low-Frequency Variations and/or Regime Shifts: A shift in circulation or SST regime (or anomalous persistence of a given regime) will lead to different theoretical frequency / probability distributions over time. Hirschboeck 1988

36. Flood Hydroclimatology for Floods of Record after Costa (1985)

37. Extreme Floods of Record evolved from: • uncommon (or unseasonable) locations of typical circulation features (a future manifestation of climate change?) • unusual combinations of atmospheric processes • rare configurations in circulation patterns (e.g. extreme blocking) • exceptional persistence of a specific circulation pattern.

38. EXAMPLE: Rare configurations in circulation patterns (extreme blocking) Lane Canyon flash flood

39. EXAMPLE:exceptional persistence of a specific circulation pattern. Jimmy Camp Creek flood of 1965

40. OVERALL: Unusually large floods in drainage basins of all sizes are likely to be associated with circulation anomalies involving quasi-stationary patterns such as blocking ridges and cutoff lows in the middle-level flow.

41. III. THE BOTTOM-UP APPROACH

42. DOWNSCALING Interpolation of GCM results computed atlarge spatial scale fields to higher resolution, smaller spatial scale fields, and eventuallyto watershed processes at the surface. Hirschboeck 2003 “Respecting the Drainage Divide” Water Resources Update UCOWR

43. “Scaling up from local data is as important as scaling down from globally forced regional models.” — Pulwarty, 2003

44. PROPOSED COMPLEMENTARY APPROACH:

45. RATIONALE FOR PROCESS-SENSITIVE UPSCALING: Attention to climatic driving forces & causes: -- storm type seasonality -- atmospheric circulation patternswith respect to: -- basin size -- watershed boundary / drainage divide -- geographic setting (moisture sources, etc.) . . . can provide a basis for a cross-scale linkage of GLOBAL climate variability withLOCALhydrologic variations at the individual basin scale . . .

46. Process-sensitive upscaling . . .can define relationships that may not be detected via precipitation downscaling • Allows the imprint of a drainage basin’s characteristic mode of interacting with precipitation in a given storm type to be incorporated into the statistics of the flow event’s probability distribution as it is “scaled up” and linked to model output and /or a larger scale flow-generating circulation pattern

47. IV. FINAL THOUGHTS

48. Is this evidence of climate change?

49. Extreme events have a legacy of confounding us!

50. Overall Recommendation: A systematic compilation of watershed-specific information about spatially and temporally varying hydroclimatic extremes is proposed as a starting place for making operationally useful decisions about prospective climatic changes.