Using Cluster Analysis to Optimize Tsunami Evacuation Zones William Power, Biljana Luković GNS Science, Lower Hutt, New Zealand.

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Presentation transcript:

Using Cluster Analysis to Optimize Tsunami Evacuation Zones William Power, Biljana Luković GNS Science, Lower Hutt, New Zealand

GNS Science New Zealand tsunami sources Background Figures from: Integrated Tsunami Database for Pacific Distant/Regional Earthquakes Local Earthquakes

GNS Science Tsunami warnings Divide the coast into zones Assign a threat level for each zone, based on maximum predicted water level Example is based on shipping forecast zones – not optimised for tsunami Tsunami threat levels Source: Mw 9.1 Southern Peru (1868)

GNS Science Tsunami threat levels Source: Mw 9.1 Southern Peru (1868)

GNS Science

The Basic idea Fault 1 Fault 2 Max water level Fault 1 Max water level Fault 2 Cluster 1 Cluster 2

GNS Science Source locations

GNS Science

Colours indicate clusters

GNS Science

Problem The standard algorithms for computing clusters do not require the members of the cluster to be contiguous

GNS Science No relationship between separated clusters of the same colour

GNS Science Conclusions New Zealand is exposed to tsunami from many directions Different parts of the coast are more/less susceptible to different source regions In a warning system based around zones it is beneficial if the coast within each zone has a similar pattern of susceptibility Cluster Analysis is one route for classifying stretches of coast according to their susceptibility to different sources A drawback of conventional cluster analysis is that it does not constrain the clusters to be contiguous around the coast Approaches to adding the contiguity constraint are possible, but more work is required

GNS Science Acknowledgments NOAA – use of MOST and FACTS Diana Greenslade (BOM) – discussions about warning zones David Rhoades (GNS) – discussions about statistical analysis