Preprints
https://doi.org/10.5194/nhess-2018-269
https://doi.org/10.5194/nhess-2018-269
22 Oct 2018
 | 22 Oct 2018
Status: this preprint was under review for the journal NHESS but the revision was not accepted.

A Methodology For Optimal Designing Of Monitoring Sensor Networks For Tsunami Inversion

Joaquín Meza, Patricio A. Catalán, and Hiroaki Tsushima

Abstract. A methodology to optimize the design of an offshore tsunami network array is presented, allowing placement of sensors to be used in a Early Tsunami Warning System framework. The method improves on previous methods by including multiple tsunami parameters as a measure of the predictive accuracy through a single cost function. The use of different tsunami parameters allows for a network which is less subject to biases found when using a single parameter. The resulting network performance was tested against an historical event, suggesting that having such a network in place could have provided meaningful information for the hazard assessment. The low number of sensors required may be useful in implementing such networks in places where funding of denser arrays might be of concern.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Joaquín Meza, Patricio A. Catalán, and Hiroaki Tsushima
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Joaquín Meza, Patricio A. Catalán, and Hiroaki Tsushima
Joaquín Meza, Patricio A. Catalán, and Hiroaki Tsushima

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Short summary
A methodology to optimize the design of an offshore tsunami network array is presented, allowing placement of sensors to be used in a Early Tsunami Warning System framework. The method includes multiple tsunami parameters as a measure of the predictive accuracy through a single cost function. The resulting network performance was tested against an historical event, suggesting that having such a network in place could have provided meaningful information for the hazard assessment.
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