, Volume 12, Issue 6, pp 1179–1196 | Cite as

Soil moisture and precipitation thresholds for real-time landslide prediction in El Salvador

  • Ari J. PosnerEmail author
  • Konstantine P. Georgakakos
Technical Note


Described is the development of a regional forecasting system for landslide hazard threat level, suitable for use operationally by forecasting and disaster management agencies. The system utilizes spatially distributed operational hydrologic models to estimate depth-integrated soil moisture on basin scales of order 160 km2, with forcing of remotely sensed and on-site precipitation data. The depth-integrated soil moisture data and the precipitation forcing are used together with regional databases of landslide occurrence to develop threshold curves in the precipitation/soil moisture space that allow the prediction of landslide hazard threat level on satellite-derived rainfall pixel scales. Predetermined susceptibility maps may then be used together with the real-time prediction of hazard threat level for a particular rainfall pixel to determine the slopes within the pixel that are more likely to fail in real time and to characterize a given pixel as susceptible or non-susceptible to landsliding for real-time prediction. The operational system development requires global satellite precipitation estimates with short latency, real-time precipitation data from sparse rain gauges in the region, and a regional database of historical landslide events with location and timing information. Parametric databases that support the operational hydrologic model consist of soil texture by depth and land-use/land-cover information. The case study presented is for the country of El Salvador. The study shows the feasibility of the regional system development and the validation of the assumed existence of a threshold curve in two-dimensional space consisting of the depth-integrated soil moisture and of the forcing precipitation. The resulting threshold curve, when examined with data from the period 2006–2011 in El Salvador, resulted in warnings of landslide occurrence with frequency that spanned the range between 1 and 5 % of the days for the basins identified to be susceptible to landsliding.


Landslide prediction Distributed soil moisture accounting Remote sensing of precipitation 



We wish to thank SNET staff Manuel Diaz and Mario Reyes. We also wish to thank the Editor and two anonymous reviewers for their constructive criticism to earlier versions of this article, which undoubtedly led to a clearer presentation.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Hydrologic Research CenterSan DiegoUSA
  2. 2.Scripps Institution of OceanographyUCSDLa JollaUSA

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