About

About SIMUSTI

SIMUSTI. The Multi-Source Tsunami Information System 1.0, or SIMuSTi 1.0, is a non-seismic tsunami evaluation system based on both numerical and physical modeling. This system was developed from lessons learned from past non-seismic (multiple-source) tsunami events, such as the 2018 Palu tsunami, and is presented in a web-based platform with geospatial information. It is accessible to various stakeholders to help assess the potential impacts of non-seismic (multiple-source) tsunamis.

SIMUSTI (Indonesia Multi-Source Tsunami Information System) is an integrated digital platform designed to serve as a centralized hub for information and a comprehensive database of non-seismic (multi-source) tsunami models. This platform was developed to support reliable decision-making in response to tsunami events that are not caused by tectonic earthquakes, such as those triggered by underwater landslides, volcanic eruptions, or other atypical sources. By combining various data and modeling components, SIMUSTI aims to enhance understanding and preparedness for non-seismic tsunami risks in Indonesia, a region characterized by complex geological hazards.

SIMUSTI integrates three key components: a historical database of documented non-seismic tsunami events, a scenario database based on seismotectonic analysis of potential future events, and a suite of numerical and physical models simulating non-seismic tsunamis. This comprehensive approach allows SIMUSTI to provide not only retrospective insights but also forward-looking simulations that inform future risk assessments. The inclusion of models for landslide-generated and volcanic tsunamis strengthens early warning systems and provides a scientific foundation for rapid, informed decision-making by disaster management authorities and stakeholders.

Key features of SIMUSTI:

1. Historical Database: Information of past (documented) non-seismic tsunamis
2. Scenario Database: Various numerical models of non-seismic tsunamis based on seismotectonic analysis
3. Benchmark: PALU & SUNDA STRAIT. Results from geological and geophysical studies at PALU and SUNDA STRAIT Cases.
4. Physical Modeling: Results from physical modeling at tsunami flume lab
5. Animation Videos: for education materials
6. LS-FORCE SIMUSTI: Near real-time mechanism of tsunamigenic landslide (Coming soon)

About DEFORMUSTI Project

DEFORMUSTI is an IDRIP project aiming in understanding tsunamigenic landslides (or multiple source tsunamis) in Indonesia that requires a comprehensive, multidisciplinary approach, integrating geology, geophysics, and tsunami sciences. This collaboration is essential to accurately assess and model landslide-triggered tsunamis and to improve predictive capabilities. Careful analysis of modeling parameters for tsunamis generated by landslides is crucial. Both numerical and physical models need to capture the unique dynamics of multi-source tsunamis, incorporating variable parameters like landslide volume, slope, velocity, and underwater topography. Formulation in the context of this project goes beyond merely writing equations; it involves systematically translating diverse input parameters, such as geological interpretation, bathymetry, coastal topography, geophysical data, and seismotectonic analysis, into a coherent model framework. This process ensures that the tsunami simulation is both accurate and actionable, enabling better forecasting and decision-making during emergencies. DEFORMUSTI is designed to provide strengthening of the Indonesia Tsunami Early Warning System (InaTEWS) related to multiple source tsunamis.

Center for Multi-Source Tsunami Studies (CMSTS) IDRIP STMKG

CMSTS is a study center that provides information and research about the multiple-source tsunami. It will help as a center to support decision-making related to early warning in the case of multiple-source tsunamis. This center is equipped with hardware and software designed to analyze and create simulations of multiple source tsunamis.

Contact Person:

Dimas Salomo J. Sianipar, Ph.D. (Assistant Professor - STMKG)

Email: dsj.sianipar@stmkg.ac.id

Haekal A. Haridhi, Ph.D. (Associate Professor - TDMRC USK)

Email: haekal.azief.haridhi@usk.ac.id