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Eve Gruntfest

Social Science and Flood Warnings. Eve Gruntfest. University of Colorado Colorado Springs ecg@uccs.edu M A P Societal Impact Workshop Bad Tolz October 24, 2002. Outline for today’s talk. The warning process

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Eve Gruntfest

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  1. Social Science and Flood Warnings Eve Gruntfest University of Colorado Colorado Springs ecg@uccs.edu M A P Societal Impact Workshop Bad Tolz October 24, 2002

  2. Outline for today’s talk • The warning process • What we have learned since the Big Thompson Flood and other flood warning tidbits • Where we go from here?

  3. Social science can no longer be an add on • Meteorologists, hydrologists and engineers and social scientists • Need for hydro-meteorologists Constant cooperation – a Must

  4. NATO ASI Ravello, ItalyNovember 8 – 17, 1999 • Intensive multidisciplinary discussions • Hydrologists, meteorologists, geographers, communication specialists, civil engineers • Representatives from 8 countries including Mexico, Uganda, Slovenia, and Ukraine, Greece, Italy, Poland, US, England • Book available Coping with Flash Floods

  5. Findings • Social science links need the most attention • Physical science and engineering advancements will only make a difference if research on warnings, warning response, and risk communication are better understood

  6. Fallacies of warning myths • People do not panic in response to warnings • People rarely get too much information • "Cry wolf" syndrome may not be applicable if previous misses are understood

  7. Public wants information from multiple sources • People actively seek to confirm risk

  8. Warning process components • Scientific component • Detection • Data assessment • Prediction • Informing

  9. Warning message components • Specific action • Location • Protective behavior • Time frames • Source of warnings

  10. Warning messages should be • Specific • Consistent • Accurate • Clear • as to location • actions to take • time before impact

  11. Public response components • Hear • Understand • Believe • Personalize • Decide to act • Respond

  12. Social science principals that complicate warning process • What people say and what they do may not be the same thing • The link between awareness of a hazard and taking action is not known

  13. People continue doing what they are doing and deny threats – • Panic is not typical • REMEMBER: people must understand, believe, personalize and then respond!

  14. An Evaluation of the Boulder Creek Local Flood Warning System (Colorado, US)www.udfcd.org/FWP/LFWSresearch.htm

  15. Report addressed • How much the public understands flood/flash flood terminology • How and how often the public wants to be warned • How the public will respond during a flash flood event • Where and how often the public obtains weather and flash flood information • To what degree false warnings will alter public response

  16. Knowledge of flood terminology Q. What does the term “100-year flood” mean? Q. Is your residence in the “100-year floodplain”? Q. What does a “flash flood watch” mean? Q. What does a “flash flood warning” mean? 30% answered all four questions correctly

  17. Knowledge of Boulder Creek floodplain residents ---

  18. Lessons from elsewhere • Maricopa County, AZ (Phoenix) • Italian case study

  19. The car is not a boat -- At .457 meters the vehicle moves downstream

  20. The truck won’t make it either

  21. Engineers and social scientists work together – here in Europe • Italian hydrologic engineer Enrica Caporali’s flood warning follow-up study Two flood warnings in October 1992 In December 1992 telephone survey of 518 residents

  22. Memory of the warnings – most heard more than one • 82% remembered the warnings • 28% remembered only one alarm • 54% remembered two

  23. After they heard thealarm • 43% did nothing • 29% moved vehicles • 83% judged the warnings positively High level of public satisfaction with warning -- but…. There was no flood!

  24. The Big Thompson Flood • Who lived? • Who died?

  25. The Big Thompson Flood 1976 • 140 dead • new focus for next generation of policy makers and scientists involved in flood mitigation -- especially in Front Range

  26. 1986 • Signs • FLASH FLOODS are recognized as different from slow rise floods • Fewer people • Real time detection • Increased vulnerability

  27. 2002 • ALERT user groups combine detection/response • New technologies • National Weather Service overpromises • Dams/infrastructure • Real time data

  28. False alarm research • Dow and Cutter (1998) • Hurricanes Bertha and Fran • Tsunami in Hawaii • Carsell (2001) • Ventura, CA false alarm

  29. Hurricanes Bertha and Fran • South Carolinians ordered to evacuate twice in 1996 • Impacts only in North Carolina • Would people evacuate next time? • What factors do they consider?

  30. Dow and Cutter –While residents do not find officials are “Crying Wolf”… • People search elsewhere for information to assess their own risk • Weather channel, quality of home construction, family situations, fear of delays in being allowed back home • “Official” sources are only some of many sources of information

  31. Tsunami in Hawaii • Calculation of cost of one false alarm: $58.2 million plus $2 million for personnel, airplanes, and moving ships Hawaii Dept. of Business, Economic Development & Tourism • Difference between normal day economic activity and day of false alert • What are costs if NO alarm is issued and there is tsunami?

  32. False alarm- Ventura, CA a siren test that went wrong- • Most said they would heed next siren • Confidence in warning process was not reduced • Served as a hands on practice for real emergency – family plans were developed Carsell’s 2001 findings

  33. High hopes for technology- Opportunities of real-time data What we do know? Great post - flood analysis---so what!?

  34. Alternate uses of ALERT data-important during droughts • Determine burn index • Calculate evapotranspiration rate • Help predict landslides • Satisfy EPA weatherrequirements for pesticide users • Hang glider wind predictions • FIRE WEATHER FORECASTS

  35. Recurrence interval? Are Warnings Possible? Likely?

  36. Killer flash floods are rare: Is each flood unique? Rainfall totals increased at the end of storm

  37. If 28 people die in Texas or France or 1000 people in India– were the warnings successful?

  38. How can we convince people they are better wet than dead?

  39. The last comprehensive research on warnings is 30 years old • What about cell phones, internet, private and public sources of information? • What about new “millennium” views of government?

  40. Future research goals • Evaluate impacts of • Demographic change • New and different sources of information • Test conventional wisdom about • False alarms/ close calls • Lead times

  41. Six questions • To what degree do earlier findings hold true today? • 2. How do new sources of technology affect the warning process? • 3. How do new data sources affect warning response? • 4. How do new attitudes toward government affect warning response?

  42. Six questions 5. How can warnings be better developed and transmitted to reduce losses? 6. How do false alarms and length of leadtimes influence public perceptions and actions?

  43. Research priorities • Calculate warning system benefits • Conduct coordinated post-audits • Address the false alarm issue in specific leadtimes

  44. Who will FINALLY fund these research projects? Calls for social science research are numerous!

  45. Key steps • Develop comprehensive warning strategies How can we develop and enforce mitigation policies without compromising economic growth? How can we change public and scientific thinking to be more long term in outlook? • Identify definitions- for flash floods, for service missions Provide incentives for graduate students • Research and workshops

  46. Who or what warning agency was most credible during the 1993 Midwestern U.S. floods?

  47. End users 1993

  48. End users 2002

  49. Expectations for 2012 • Numerous “natural” problem solving collaborations between social scientists, physical scientists, and practitioners • Many “measured” successes – reduced losses • Reduced vulnerability and integrated warning systems

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