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Track: Emergency Management & Public Safety
John Kaiser
San Diego State University
1077 Glenhill Road
El Cajon, CA 92020
Telephone: 619-594-8645
Fax: 619-594-4938
E-mail: jkaiser@typhoon.sdsu.edu
Dr. Richard Wright, Dr. David McArthur, Dr. Eric G. Frost
Using GIS to Predict Liquefaction Susceptible Sediments within a Portion of the Southern California Coastal Corridor
Defining Issue: Ground failures generated by liquefaction are one of the seismic hazards that brings great damage to property and community infrastructure, and loss of life. Recent geological investigations have identified previously unrecognized liquefaction features along portions of southern California's highly populated coastline between Los Angeles and San Diego. This coastal strip is densely populated, has extensive commercial development and is the principal corridor for many, critical lifelines essential to San Diego including highway, rail, natural gas, electricity, and fiber optic communications. GIS Solution: Existing drilling, trenching, and in-situ liquefaction prediction methods are deficient in that they are costly, time-consuming, and their results are limited in spatial extent. GIS offers a time and resource efficient method for predicting the occurrence and spatial dimensions of liquefaction prone areas. Urgently needed by risk assessment authorities, GIS allows regional predictions
using readily accessible public data sets. Methodology: The model demonstrates a GIS-based liquefaction prediction model that uses internally consistent and physically based variable weights to delineate liquefaction susceptible areas. The prediction model uses water table depth, particle size, and sediment compaction/cementation derived from existing geologic, soils engineering, and hydrologic data as predictive variables. Most importantly, the predictive variables are weighted using an internally consistent and physically based weighting scheme. Variable weights are scaled based upon their contribution to the liquefaction process as measured by each variable's effect upon a common liquefaction susceptibility measure, the standard penetration test blow count. This prediction method has a regional scope in contrast to alternative, site-specific methods, which are more costly. Software: The application was implemented using the ARCGRID and ARC modules of ArcInfo.
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