An Optimized Array Configuration of Tsunami Observation Network Off Southern Java, Indonesia. Issue 9 (3rd September 2019)

• Record Type: Journal Article
• Authors: Mulia, Iyan E.; Gusman, Aditya Riadi; Williamson, Amy L.; Satake, Kenji
• Is Part Of: Journal of geophysical research. Volume 124:Issue 9(2019)
• Page Start: 9622
• Page End: 9637
• Publication Date: 2019-09-03
• Subjects: tsunami -- observation network -- forecast -- inversion -- optimization; Geomagnetism -- Periodicals; Geochemistry -- Periodicals; Geophysics -- Periodicals; Earth sciences -- Periodicals; 551.1
• DOI: 10.1029/2019JB017600
• Languages: English
• ISSNs: 2169-9313

Abstract

Abstract: Historical records have proven that the southern coasts of Java, Indonesia, are prone to tsunamis. The existing tsunami observing system using bottom pressure gauges, also known as tsunameters, composes a global network but is too sparse for regional tsunami forecasts. The nearest tsunameter to Indonesia is located approximately 500‐km offshore, which is not very useful for the area, particularly for a tsunami source in eastern part of the Sunda megathrust. Here we propose a methodology to optimally place offshore tsunameters with the main consideration of operational costs, which is proportional to the number of observation points. We use a stochastic slip model of earthquakes with M w 8.8–9.2 to generate multiple tsunami source realizations representing possible future events in the region. Based on the sources, we then identify a potential zone where an early tsunami detection is feasible. Furthermore, empirical orthogonal functions derived from tsunami simulations are used to determine the initial locations for tsunameter placement inside the specified zone. Finally, we apply an optimization scheme to improve the initial locations that facilitates both tsunami forecasts and source characterizations through a tsunami waveform inversion analysis. Our result indicates that six tsunameters are sufficient to efficiently cover the major seismogenic region in the study area. Key Points: The study proposes an efficient design of tsunami observation network off southern coast of Java, Indonesia We utilize optimizations to determine the best observation locations for multiple earthquake models (Mw 8.8‐9.2) The result suggests locations of six tsunameters that can provide accurate tsunami forecasts and source characterizations