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Empirical fragility and vulnerability curves for buildings exposed to slow-moving landslides at medium and large scales

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Abstract

Slow-moving landslides yearly induce huge economic losses worldwide in terms of damage to facilities and interruption of human activities. Within the landslide risk management framework, the consequence analysis is a key step entailing procedures mainly based on identifying and quantifying the exposed elements, defining an intensity criterion and assessing the expected losses. This paper presents a two-scale (medium and large) procedure for vulnerability assessment of buildings located in areas affected by slow-moving landslides. Their intensity derives from Differential Interferometric Synthetic Aperture Radar (DInSAR) satellite data analysis, which in the last decade proved to be capable of providing cost-effective long-term displacement archives. The analyses carried out on two study areas of southern Italy (one per each of the addressed scales) lead to the generation, as an absolute novelty, of both empirical fragility and vulnerability curves for buildings in slow-moving landslide-affected areas. These curves, once further validated, can be valuably used as tools for consequence forecasting purposes and, more in general, for planning the most suitable slow-moving landslide risk mitigation strategies.

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Acknowledgements

The authors are grateful to the National Basin Authority of Liri-Garigliano and Volturno (NBA-LGV) rivers and, in particular, to the General Secretary Dr. Vera Corbelli for providing all the thematic maps and the damage survey fact-sheets of the study area. The authors wish also to thank Italian Ministry of the Environment and Protection of Land and Sea and, in particular, Dr. Salvatore Costabile for providing the PSI data over NBA-LGV deriving from the “Piano Straordinario di Telerilevamento Ambientale.” The SAR image dataset used in the paper for the case study of Lungro was provided by European Space Agency (ESA) under the CAT-1 Project on “Calibration of the Synthetic Aperture Radar (SAR) measures with Integrated Monitoring Networks (IMoN), and extended uses in homogeneous geological contexts” (C1P.5618) and the project carried out using COSMO-SkyMed® PRODUCTS, © ASI (Italian Space Agency), provided under license of ASI (prot. no. 0000155 dated January 12, 2015). The Lungro case study is part of the Project DTA.AD003.077.001 “Tipizzazione di eventi di dissesto idrogeologico” of the CNR Department of “Scienze del Sistema Terra e Tecnologie per l’Ambiente.”

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Authors and Affiliations

  1. Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084, Fisciano, SA, Italy

    Dario Peduto, Settimio Ferlisi & Gianfranco Nicodemo

  2. Institute for Electromagnetic Sensing of the Environment, National Research Council of Italy (IREA–CNR), Via Diocleziano 328, 80124, Naples, Italy

    Diego Reale

  3. Via Ventaglieri, 77, 80135, Naples, Italy

    Giovanni Pisciotta

  4. Research Institute for Geo-Hydrological Protection, National Research Council of Italy (IRPI–CNR), Via Cavour 4/6, 87036, Rende, CS, Italy

    Giovanni Gullà

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  1. Dario Peduto
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  5. Giovanni Pisciotta
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Correspondence to Dario Peduto.

Appendix

Appendix

This appendix is devoted to show the results of the Kolmogorov–Smirnov (K–S) goodness-of-fit test that was performed in order to check the work hypothesis of using the cumulative log-normal distribution for describing the probability of reaching/exceeding a given damage level within the fragility curve construction.

Figure 12a shows the K–S test carried out on fragility curves derived for vulnerable areas composed by masonry building aggregates in the area analyzed at medium scale. The results confirm that the above work hypothesis is acceptable since the values of the maximum distances (D max) between the considered log-normal distribution function for each damage level and the related empirical distribution function—defined according to the K–S test—are always lower than the critical values (D crit) provided by Kolmogorov–Smirnov for all significance levels (α).

Similarly to the analysis carried out at medium scale, the reliability of the used cumulative log-normal distribution function was checked using the K–S test for the fragility curves derived for Lungro area. Also, in such a case, the obtained results confirm the validity of the adopted work hypothesis (Fig. 12b).

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Peduto, D., Ferlisi, S., Nicodemo, G. et al. Empirical fragility and vulnerability curves for buildings exposed to slow-moving landslides at medium and large scales. Landslides 14, 1993–2007 (2017). https://doi.org/10.1007/s10346-017-0826-7

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