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Extremes: Frequency methods

Extremes: Frequency methods. With a focus on floods but methods applicable to other extremes: Rainfall, air temperature, wind speed, landslide, sea level …. Effects on flood frequency of climate variability & change Changing frequencies of extremes Charles Pearson NIWA, Christchurch.

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Extremes: Frequency methods

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  1. Extremes: Frequency methods • With a focus on floods but methods applicable to other extremes: • Rainfall, air temperature, wind speed, landslide, sea level …. • Effects on flood frequency of climate variability & change • Changing frequencies of extremes Charles Pearson NIWA, Christchurch

  2. Invercargill, 27 Jan. 1984 (photo: Southland Times)

  3. Otira River, NZ, May 1980 (photo: The Press)

  4. Cyclone Bola damage, NI east coast, March 1988

  5. Scour failure of the southern approach to the Rangitata River Railway Bridge, 4 January, 2002. The engine driver was lucky to escape from the cab.

  6. August 2005 European floods … Switzerland

  7. Southern Germany

  8. Derailed Train Austria

  9. Germany

  10. Lucerne, Switzerland

  11. Berne Switzerland

  12. South East France

  13. Effects on business … Austria

  14. Damaging floods keep happening in NZ: are we learning from our flood history? Queenstown, 29 Sept. 1878 Queenstown, 6 Nov. 1999 (photo: Otago Daily Times. Dunedin)

  15. Recent major NZ floods: • March, July 2007: Northland • July 2004 and 2005: • Bay of Plenty • February 2004: • Manawatu, Taranaki, Waiarapa, Turangi, Picton • Increased frequency? • Certainly increased media focus and public scrutiny • How do we gauge “frequency”?

  16. Frequency – Definition of “100-year return period event”? You choose: • Any event that causes damage and wide scale media interest! • Any subsequent, equally damaging event occurring only a few months later • Occurs on average once every 100 years • Has 1 chance in 100 of exceedance in any 1 year • Has 37% chance of not occurring in 100 years • Has 63% chance of occurring in 100 years • Has 13% chance of not occurring in 200 years • None of the above • Options 3-7 above

  17. Answer: 9. Options 3-7 Option 4: “1% AEP event” is best (“AEP” = Annual Exceedance Probability) because it is used to define return period (T = 1 / AEP), and should be used in preference to return period Return Period is also called “average recurrence interval”

  18. Frequency methods • Relate event magnitudes x to their probabilities of occurrence • Probability of occurrence can represented be F(x) = 1 –AEP, AEP or return period • For floods: • Estimate flood peak distribution F(x) for a river location from either: • A flood sample at the location • Fit a distribution F(x) to sample floods x • Flood records from nearby river locations

  19. “Plotting positions” • “Plotting positions” allow graphing of extremes (x) against F(x), AEP or return period • Note: Largest value plotted at T = 1.8 x n, where n is sample size • But wouldn’t the largest in n years have a return period of T = n? • It depends, and not for extremes. • But first, measuring floods ....

  20. Flood magnitudes: Challenges of measuring flood flows …

  21. Monitoring river levels & flows • River and lake water levels (15 mins) • River flows (“gauging” ~monthly) • >600 stations open (NIWA & councils) • >1500 NZ water level records (open and closed stations)

  22. Data transmitted to databases in real-time

  23. Waimakariri River at Old Highway Bridge

  24. Frequency methods: Annual maxima • Most common frequency analysis method • Sampling largest value per year • Fit an extreme value distribution

  25. Selection of annual maxima

  26. Waimakariri flood frequency

  27. Flood frequency exercise • Assume a 4,000 m3s-1 flood peak was measured at the Waimakariri yesterday. • What is your estimate of its probability of occurrence? • Write down a sentence describing the event’s frequency for a press release.

  28. Frequency methods: Partial Duration Series • Also called “peaks over a threshold” • Set flood threshold and / or no. of events per year • Select sample • Fit an “exceedance” distribution • Useful for short records, to double the sample size

  29. Frequency methods: Historical flood information • Augment continuous flood record with historical flood information: • Flood peak (e.g. flood marks) • Data range only • Flood date only – “extends” record length • Can fit distributions using this information • For the Waimakariri 4,000 m3s-1 flood peak, where would it plot if it was known to be the largest event in 100 years? What is your estimate of its AEP?

  30. “Regional” Frequency Methods • For where we don’t have data where we need it – mostly the case! • Transfer information from nearby stations to estimate required frequency relationship

  31. 1989 study: mean annual flood peak • Catchment Area, A (km2) • Qmean = 2 A0.8

  32. 1989 maps of Qmean / A0.8

  33. 1989 study - Maps of Q100 / Qmean

  34. Regional flood frequency revision • Underway …. • Making use of nearly 20 more years of flood peak flow data • Mapping of flood flow frequencies on river drainage networks (median annual flood, right)

  35. Climate impacts on flood frequencies? • Major flood events of 2004-07: how is climate affecting flood frequencies? • What impacts do climatevariability and “climate change” have on flood frequency?

  36. El Niño La Niña Climate variability -El Niño and La Niña (ENSO): Sea temperature difference from average • Cooler in tropics • Warmer in much of SW Pacific • SW movement of SPCZ • Warmer in tropics • Cooler in much of SW Pacific • NE movement of SPCZ • Eastward extension of TC region Southern Oscillation Index (SOI)

  37. Wind anomaly Wind anomaly Summer rainfall La Niña effect, % El Niño effect, %

  38. The likelihood of ENSO extremes appears to have shifted: in about 1947, 1977 and 1999

  39. Interdecadal Pacific Oscillation (IPO) (warm) (cool) 1978-1999 1947-1977

  40. Interdecadal Pacific Oscillation index

  41. Smaller floods: Rangitaiki R. The 100 yr flood estimate decreases by 34% from 710 to 470 m3/s. Flood peak (m3/s) before after 10 yr 100 yr

  42. No change: Whanganui R. before Flood peak (m3/s) after 10 yr 100 yr

  43. Bigger floods: Lake Te Anau after The 100 yr 3 day flood inflow estimate increases by 29% from 2750 to 3550 m3/s. before 10 yr 100 yr

  44. Bigger floods: Waihopai River The 100 yr flood estimate increases by 114% from 64.4 to 134 m3/s. Or, the 100 yr estimate becomes a 3 yr estimate. after before 10 yr 100 yr

  45. What about climate change? • Warmer temperatures • Heavy rain more frequent • Predicted Precipitation Changes (%), 1980s to 2030s, 6 models • Size of return period changes?

  46. In conclusion … • Floods and extremes can’t be prevented • Essential to keep monitoring • Update frequency magnitude relationships regularly (annually & after major events) • Update NZ regional methods every decade • AEPs / return periods can change with time

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