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Natural Hazards

, Volume 79, Issue 3, pp 1825–1845 | Cite as

Normalized Landslide Index Method for susceptibility map development in El Salvador

  • Ari J. Posner
  • Konstantine P. Georgakakos
Original Paper

Abstract

El Salvador and Central America in general are highly prone to landsliding. In November 1998, Hurricane Mitch killed 240 people, displaced about 85,000 people, caused more than $600 million in economic losses, and damaged about 60 % of the nation’s roads (Rose et al. in Natural hazards in El Salvador. Geologic Society of America of special paper 375, Boulder, 2004). An understanding of susceptibility of locations to landsliding is critical for development and mitigation planning. This work presents the development of the Normalized Landslide Index Method which is a derivative of the bivariate statistical methods commonly used in landslide susceptibility assessment. The resultant map was amended through a tangential analysis, also commonly used in landslide susceptibility mapping, the Analytical Hierarchy Process (AHP), which reduces multi-criteria analysis to pair-wise comparisons. The assimilation of results from the AHP analysis into the statistically derived susceptibility map skewed the original results by emphasizing the extremes already found. It was determined that addition of AHP results did not increase the value of the derived susceptibility map. Finally, a physically based a priori approach to landslide susceptibility mapping, developed by El Salvador National Service of Territorial Studies, was compared to the statistically derived map developed herein. It was found that the a priori approach was not sufficiently discriminant to be useful for planners and regulators, as very large areas were designated high susceptibility that included areas with low slope angles. The development of the normalized landslide index is a significant improvement to the class of bivariate statistical strategies to assess regional landslide susceptibility.

Keywords

Landslide susceptibility Analytical Hierarchy Process Landslide index method Bivariate statistics El Salvador 

Notes

Acknowledgments

The authors are thankful to the UN World Meteorologic Organization and the US Agency for International Development for the support of this project. Additional support was provided by the Technology Transfer Program of the Hydrologic Research Center. The authors would also like to thank the staff at SNET (Mario Reyes and Manuel Diaz), El Salvador, for their cooperation in providing data, maps, references, and details about specific landslide events. This work could not have been accomplished without their help.

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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Hydrologic Research CenterSan DiegoUSA
  2. 2.Scripps Institution of OceanographyUniversity of California at San DiegoLa JollaUSA

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