pure and applied geophysics

, Volume 157, Issue 6, pp 1059–1079

Applying Probability Determination to Refine Landslide-triggering Rainfall Thresholds Using an Empirical “Antecedent Daily Rainfall Model”

  • T. Glade
  • M. Crozier
  • P. Smith

DOI: 10.1007/s000240050017

Cite this article as:
Glade, T., Crozier, M. & Smith, P. Pure appl. geophys. (2000) 157: 1059. doi:10.1007/s000240050017

Abstract

—Rainfall-triggered landslides constitute a serious hazard and an important geomorphic process in many parts of the world. Attempts have been made at various scales in a number of countries to investigate triggering conditions in order to identify patterns in behaviour and, ultimately, to define or calculate landslide-triggering rainfall thresholds. This study was carried out in three landslide-prone regions in the North Island of New Zealand. Regional landslide-triggering rainfall thresholds were calculated using an empirical “Antecedent Daily Rainfall Model.” In this model, first introduced by, triggering rainfall conditions are represented by a combination of rainfall occurring in a period before the event (antecedent rainfall) and rainfall on the day of the event. A physically-based decay coefficient is derived for each region from the recessional behaviour of storm hydrographs and is used to produce an index for antecedent rainfall. Statistical techniques are employed to obtain the thresholds which best separate the rainfall conditions associated with landslide occurrence from those of non-occurrence or a given probability of occurrence.The resultant regional models are able to represent the probability of occurrence of landsliding events on the basis of rainfall conditions. The calculated thresholds show regional differences in susceptibility of a given landscape to landslide-triggering rainfall. These differences relate to both the landslide database and the difference of existing physical conditions between the regions.

Key Words: Landslides, probabilistic threshold determination, rainfall threshold, critical water content.

Copyright information

© Birkhäuser Verlag Basel, 2000

Authors and Affiliations

  • T. Glade
    • 1
  • M. Crozier
    • 2
  • P. Smith
    • 3
  1. 1.Department of Geography, University of Bonn, Meckenheimer Allee 166, 53115 Bonn, Germany.DE
  2. 2.Institute of Geography, School of Earth Sciences, Victoria University of Wellington, P.O. Box 600, Wellington, New Zealand.NZ
  3. 3.Institute of Statistics and Operations Research, School of Mathematical and Computing Sciences, Victoria University of Wellington, P.O. Box 600, Wellington, New Zealand.NZ