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The Effect of Early Flood Warnings on Mitigation and Recovery During the 2010 Pakistan Floods

Abstract

We estimate the effect of early warnings on the likelihood of households taking action to mitigate damages before the severe 2010 flood in Punjab, Pakistan. Using a survey of 640 households conducted after the floods, we find that face-to-face warnings significantly increase the probability of households taking any pre-flood mitigation action, while remote warnings such as television and radio announcements do not have a significant effect on taking any mitigation. For the most costly mitigation action of reinforcing the house structure, only warning from government officials or mosques significantly increases the likelihood of action. Receiving a warning and taking mitigation action reduces the actual loss of household structure value, and taking pre-flood mitigation action also significantly increases the likelihood of having recovered household possessions.

Keywords

  • Mitigation action
  • Pakistan
  • Household
  • Risk perception
  • Framework
  • Remote information sources

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Notes

  1. 1.

    EM-DAT Global Disaster Database: http://www.preventionweb.net/english/countries/statistics/?cid=129

  2. 2.

    http://www.punjab.gov.pk/?q=punjab_quick_stats

  3. 3.

    According to the MICS 2011, the districts where any households reported being affected by the floods in 2010 were Rajanpur, Muzaffargarh, Jhang, Layyah, DG Khan, Sargodha, Multan, Rahim Yar Khan, Bhakkar, and Bahwalpur.

  4. 4.

    A cluster was designated as flood affected only if all the households in the cluster responded to the question of being affected by the flood in 2010 with a “Yes.” This was done to make sure there are no errors due to the migration of households into and out of the cluster since 2010–2011, when the survey was conducted and only clusters where there is minimum likelihood of migration in and out are selected as flood affected.

  5. 5.

    Note that the MICS is a representative random sample of the total population, not a census of all households, so the percentage of flood-affected clusters calculated is approximate but based on the random sample.

  6. 6.

    Note, in using both the 2007–2008 and 2011 rounds of MICS, we have effectively restricted our sample to villages that were common in both rounds. Since the samples in both years were completely random, any villages that have been sampled in both rounds are also random – there is no reason to suspect any bias in the selection of these villages. Note also, that resampling the same villages in 2011 that were sampled in 2007–2008 does not mean that the same households were sampled, since the selection of households is random.

  7. 7.

    The propensity scores of the non-flooded villages do not exceed the propensity scores of the flooded villages by more than 30 % of the standard deviation of the scores.

  8. 8.

    This variable was measured with a hypothetical survey question asking about their preferences for a sum of money today or a larger sum six months in the future.

  9. 9.

    Our survey included measures of (self-reported) resilience in terms of losses experienced, loss recovery, and time to recovery of various possessions and livelihoods.

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Acknowledgments

The authors are grateful for financial support from the British Academy, the Lahore School of Economics, the Wharton School, and the Travelers Foundation.

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Correspondence to Ginger Turner .

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Turner, G., Said, F., Afzal, U., Campbell, K. (2014). The Effect of Early Flood Warnings on Mitigation and Recovery During the 2010 Pakistan Floods. In: Singh, A., Zommers, Z. (eds) Reducing Disaster: Early Warning Systems For Climate Change. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8598-3_13

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  • DOI: https://doi.org/10.1007/978-94-017-8598-3_13

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