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Performance analysis of Sebesi Island automatic water level station as tsunami confirmation system.

Authors :
Fatkhurrohman, Fatkhurrohman
Siregar, Masbah Rotuanta Tagore
Sugiarto, Sugiarto
Putra, Maulana
Source :
AIP Conference Proceedings; 2023, Vol. 2865 Issue 1, p1-7, 7p
Publication Year :
2023

Abstract

The December 22<superscript>nd</superscript>, 2018, Tsunami generated by Anak Krakatau landslide material in the Sunda Strait caused high casualties. There's a lack of warning because Indonesia's early warning system was designed to monitor Tsunamis caused by tectonic earthquakes but not by underwater landslides and volcanic eruptions, which can also generate Tsunami waves. As a government body, the Indonesian Meteorological, Climatological, and Geophysical Agency installed an automatic water level station to report the water level near Anak Krakatau volcano. This system consists of CS475 Campbell Scientific pulse radar and transmitted data every 1 minute to BMKG HQ using cellular communication. After deployment, we analyzed the performance of the instruments using Station Data Quality Assessment to obtain the system's characteristics to be deployed in other locations. The data quality quantification is based on various metrics evaluating data properties such as timing quality, noise ratio, relative tidal analysis, data gaps, glitches, and latency. The system has a performance of 8.12% gaps, 3.55% glitch, -0.04283 noise rate, and 1.5 min of data latency. To classify metric values from data properties analysis into grades, we implemented a grading curve scheme by calculating a scoring curve to which each metric value can be assigned. These grades are then used to make up the aggregate with a total of A grades on the Data Quality Assessment summary page. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2865
Issue :
1
Database :
Complementary Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
174492424
Full Text :
https://doi.org/10.1063/5.0182372