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Natural Hazards

, Volume 61, Issue 1, pp 143–153 | Cite as

Slope units-based flow susceptibility model: using validation tests to select controlling factors

  • E. Rotigliano
  • C. Cappadonia
  • C. Conoscenti
  • D. Costanzo
  • V. Agnesi
Original Paper

Abstract

A susceptibility map for an area, which is representative in terms of both geologic setting and slope instability phenomena of large sectors of the Sicilian Apennines, was produced using slope units and a multiparametric univariate model. The study area, extending for approximately 90 km2, was partitioned into 774 slope units, whose expected landslide occurrence was estimated by averaging seven susceptibility values, determined for the selected controlling factors: lithology, mean slope gradient, stream power index at the foot, mean topographic wetness index and profile curvature, slope unit length, and altitude range. Each of the recognized 490 landslides was represented by its centroid point. On the basis of conditional analysis, the susceptibility function here adopted is the density of landslides, computed for each class. Univariate susceptibility models were prepared for each of the controlling factors, and their predictive performance was estimated by prediction rate curves and effectiveness ratio applied to the susceptibility classes. This procedure allowed us to discriminate between effective and non-effective factors, so that only the former was subsequently combined in a multiparametric model, which was used to produce the final susceptibility map. The validation of this map latter enabled us to verify the reliability and predictive performance of the model. Slope unit altitude range and length, lithology and, subordinately, stream power index at the foot of the slope unit demonstrated to be the main controlling factors of landslides, while mean slope gradient, profile curvature, and topographic wetness index gave unsatisfactory results.

Keywords

Landslide susceptibility Univariate multiparametric model validation Mapping units 

Notes

Acknowledgments

The research, whose results are here shown and discussed, was carried out in the framework of the Ministry of University funded project (PRIN2007) “EROMED”, national coordinator Prof. G. Rodolfi, local responsible Prof. V. Agnesi. C. Cappadonia, C. Conoscenti, D. Costanzo, and E. Rotigliano have commonly shared all the parts of the research. V. Agnesi has participated to the final interpretation of the data. The authors wish to thank three anonymous reviewers for having given great insight and a number of suggestions useful in improving the quality and readability of this paper. Clare Hampton has linguistically edited the final version of this text.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • E. Rotigliano
    • 1
  • C. Cappadonia
    • 1
  • C. Conoscenti
    • 1
  • D. Costanzo
    • 1
  • V. Agnesi
    • 1
  1. 1.Dipartimento di Scienze della Terra e del MareUniversità degli Studi di PalermoPalermoItaly

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