Rainfall Threshold for Landslides Prediction with Excel only

Using Excel for ID, IE and Antecedent thresholds for early-warning systems, landslides & geo-hydrological risk analysis

Rainfall Threshold for Landslides Prediction with Excel only
Rainfall Threshold for Landslides Prediction with Excel only

Rainfall Threshold for Landslides Prediction with Excel only free download

Using Excel for ID, IE and Antecedent thresholds for early-warning systems, landslides & geo-hydrological risk analysis

In this course, we go through the development and validation of precipitation rainfall threshold step-by-step.

You will learn how to effectively build, apply and validate the most powerful Precipitation thresholds, and much more:  [Excel sheet and Articles are available for the exercise application purposes]

  1. What is all about with experience sharing : focus on that thresholds that Induces Landslides

  2. How to prepare the data for threshold analysis

  3. Errors and Uncertainties

  4. Correlation between station records

  5. Spatial pattern analysis for incidents and stations


    a. Compute the Distance Matrix [distance matrix, rename the source stations as text and target as ID]

    b. Compute Nearest Neighbor Analysis [shared nearest neighbor clustering, high no.= less groups]

    c. Select  points by delete unwanted and outliers

  6. Correlation analysis

  7. Precipitation Threshold Analysis that Induces Landslides types

      a. ID, IE,

      b. E-Date, I-Date,

      c. Antecedents and others

  8.Reliability index

  9.Processing steps : first comes first

  10.Temporal analysis

Tools: Microsoft excel and open source GIS software QGIS.

Data used in the tutorial, is strictly protected under copyright law of Landslides (Journal of the International Consortium on Landslides). Please cite the article below:

 Althuwaynee O F., Asikoglu O. & Eris E. (2018) ”Threshold contour production of rainfall intensity that                  induces landslides in susceptible regions of northern Turkey “ Landslides. DOI   : 10.1007/s10346-        018-0968-2