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. 2015 Dec 29;10(12):e0144468.
doi: 10.1371/journal.pone.0144468. eCollection 2015.

Weather-Related Flood and Landslide Damage: A Risk Index for Italian Regions

Affiliations

Weather-Related Flood and Landslide Damage: A Risk Index for Italian Regions

Alessandro Messeri et al. PLoS One. .

Abstract

The frequency of natural hazards has been increasing in the last decades in Europe and specifically in Mediterranean regions due to climate change. For example heavy precipitation events can lead to disasters through the interaction with exposed and vulnerable people and natural systems. It is therefore necessary a prevention planning to preserve human health and to reduce economic losses. Prevention should mainly be carried out with more adequate land management, also supported by the development of an appropriate risk prediction tool based on weather forecasts. The main aim of this study is to investigate the relationship between weather types (WTs) and the frequency of floods and landslides that have caused damage to properties, personal injuries, or deaths in the Italian regions over recent decades. In particular, a specific risk index (WT-FLARI) for each WT was developed at national and regional scale. This study has identified a specific risk index associated with each weather type, calibrated for each Italian region and applicable to both annual and seasonal levels. The risk index represents the seasonal and annual vulnerability of each Italian region and indicates that additional preventive actions are necessary for some regions. The results of this study represent a good starting point towards the development of a tool to support policy-makers, local authorities and health agencies in planning actions, mainly in the medium to long term, aimed at the weather damage reduction that represents an important issue of the World Meteorological Organization mission.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. 500hPa geopotential height for each weather types (WT) classified by LAMMA-IBIMET for the period 1948–2011.
Fig 2
Fig 2. Work-flow of the Weather Type-related Floods and Landslides Risk Index (WT-FLARI) assessment.
Fig 3
Fig 3. Incidence of normalized features for each Italian region.
Fig 4
Fig 4. Mapping of the annual WT-related Floods and LAndslides Risk Index (WT-FLARI).
WT (Weather Type). WT-FLARI levels: red = Very High (WT-FLARI > 99th perc.); orange = High (95th perc. > WT-FLARI > 99th perc.); yellow = Moderate (95th perc. > WT-FLARI > 90th perc.); white = Low (WT-FLARI < 90th perc.)
Fig 5
Fig 5. Mapping of the autumn WT-related Floods and LAndslides Risk Index (WT-FLARI).
WT (Weather Type). WT-FLARI levels: red = Very High (WT-FLARI > 99th perc.); orange = High (95th perc. > WT-FLARI > 99th perc.); yellow = Moderate (95th perc. > WT-FLARI > 90th perc.); white = Low (WT-FLARI < 90th perc.)
Fig 6
Fig 6. Mapping of the spring WT-related Floods and LAndslides Risk Index (WT-FLARI).
WT (Weather Type). WT-FLARI levels: red = Very High (WT-FLARI > 99th perc.); orange = High (95th perc. > WT-FLARI > 99th perc.); yellow = Moderate (95th perc. > WT-FLARI > 90th perc.); white = Low (WT-FLARI < 90th perc.)
Fig 7
Fig 7. Mapping of the winter WT-related Floods and LAndslides Risk Index (WT-FLARI).
WT (Weather Type). WT-FLARI levels: red = Very High (WT-FLARI > 99th perc.); orange = High (95th perc. > WT-FLARI > 99th perc.); yellow = Moderate (95th perc. > WT-FLARI > 90th perc.); white = Low (WT-FLARI < 90th perc.)

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References

    1. Kunkel KE, Pielke JR, Changnon SA (1999) Temporal fluctuations in weather and climate extremes that cause economic and human health impacts: a review. Bull. A M. Meteorol Soc 80:1077–1099. doi:101175/1520-0477(1999)080-1077:TFIWAC-2.0.CO
    1. Kharin VV, Zwiers FW, Zhang X, Hegerl GC (2007). Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations. Journal Clim 20: 1419–1444. 10.1175/JCLI4066.1 - DOI
    1. Harmeling S (2010) Global climate risk index 2010. Who is most vulnerable? Weather-related loss events since 1990 and how Copenhagen needs to respond. Bonn, Germany, Germanwatch Breafing Paper. 20pp
    1. WHO (2010) Report Climate Change, extreme weather events and public health Copenaghen, WHO Regional Office for Europe; 37pp
    1. Trenberth KE (2011) Changes in precipitation with climate change. Contribution to CR Special 25 “Climate services for sustainable development” 47: 123–138. doi: 103354/cr00953

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