NH003
Advancing Solid Earth Hazard Assessment Using Integrated Digital Twin Approaches
Session ID#: 249382
Session Description:
Solid Earth hazards such as earthquakes, volcanic eruptions, and tsunami pose severe risks, necessitating enhanced modeling and mitigation strategies. Digital twins (DTs) - advanced computational frameworks combining near real-time data assimilation, multi-scale physics-based modeling, and machine learning - offer new capabilities for understanding and forecasting these complex hazards. This session explores cutting-edge developments in DT applications, emphasizing integration across observational, experimental, and computational geosciences. We invite presentations addressing physics-based modeling techniques, data-driven methodologies, uncertainty quantification strategies, and case studies demonstrating DT effectiveness in real-world hazard assessment. Contributions are encouraged from seismology, volcanology, hydrothermal systems, geodynamics, engineering, data science, and computational infrastructure, highlighting advancements and implications for societal resilience. We specifically welcome discussion on computational efficiency, scalability, and interdisciplinary collaboration enabled by High-Performance Computing workflows. DTs require the synthesis of observational data, multi-physics modeling techniques including the development of simplified surrogate models, and large-scale uncertainty quantification to achieve predictive breakthroughs.
Co-Sponsor(s):
Index Terms:
1908 Cyberinfrastructure [INFORMATICS]
1910 Data assimilation, integration and fusion [INFORMATICS]
7290 Computational seismology [SEISMOLOGY]
8410 Geochemical modeling [VOLCANOLOGY]
Primary Convener: Alice-Agnes Gabriel, Scripps Institution of Oceanography, La Jolla, United States
Conveners: Margarete Ann Jadamec, University at Buffalo, Department of Geology; Institute for Artificial Intelligence and Data Science, Buffalo, NY, United States, Leif Karlstrom, University of Oregon, Department of Earth Sciences, Eugene, OR, United States and Mark D Behn, Boston College, Earth and Environmental Sciences, Chestnut Hill, United States
Tsunami Digital Twin : Progress and Applications to Japan and the US (1907047)
Shunichi Koshimura1, Yuichiro Tanioka2, Diego Melgar3, Brendan Crowell4, Ronald T Eguchi5, Yusaku Ohta6, Erick Mas1, Bruno Adriano1, Akihiro Musa7, Yoshihiko Sato8, Junko Yoshino9, Naoya Morimatsu1, Takayuki Suzuki8, Hiroyuki Takizawa7 and Hiroaki Kobayashi10, (1)Tohoku University, International Research Institute of Disaster Science, Sendai, Japan, (2)Hokkaido University, Sapporo, Japan, (3)University of Oregon, Department of Earth Sciences, Eugene, United States, (4)The Ohio State University, School of Earth Sciences, Columbus, United States, (5)ImageCat, Inc., Long Beach, CA, United States, (6)Tohoku University, Research Center for Prediction of Earthquakes and Volcanic Eruptions, Graduate School of Science, Sendai, Japan, (7)Tohoku University, Cyberscience Center, Sendai, Japan, (8)RTi-cast, Inc., Sendai, Japan, (9)NEC Corporation, Tokyo, Japan, (10)Tohoku University, Graduate School of Information Sciences, Sendai, Japan
A Digital Twin for identifying unrest and dike propagation patterns at Mount Etna volcano, Italy. (Invited) (1918507)
Chiara Paola Montagna1, Rebecca Bruni2, Erica De Paolo3, Martina Allegra3, Deepak Garg2, Flavio Cannavo4 and Paolo Papale2, (1)Istituto Nazionale di Geofisica e Vulcanologia, Palermo, Italy, (2)Istituto Nazionale di Geofisica e Vulcanologia, Pisa, Italy, (3)Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, Catania, Italy, (4)Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania - Osservatorio Etneo, Palermo, Italy
Digital Twin for tsunami disaster resilience, incorporating data Assimilation of ocean bottom pressure data - preparing for great Nankai earthquakes- (1944124)
Yuichiro Tanioka1, Rinda Ratnasari2, Takayuki Suzuki3, Shunichi Koshimura4, Akihiro Musa5, Naoya Morimatsu4, Yoshihiro Sato6 and Junko Yoshino7, (1)Hokkaido University, Sapporo, Japan, (2)Hokkaido University, Faculty of Science, Sapporo, Japan, (3)RTi-cast, Inc., Sendai, Japan, (4)Tohoku University, International Research Institute of Disaster Science, Sendai, Japan, (5)Tohoku University, Cyberscience Center, Sendai, Japan, (6)Tokyo City University, Yokohama, Japan, (7)NEC Corporation, Tokyo, Japan
The Virtual Earthquake Machine: Towards Digital Twins of Fault Zones (Invited) (1954854)
Ahmed E Elbanna, University of Illinois at Urbana Champaign, Department of Civil and Environmental Engineering, Urbana, United States, Mohamed Abdelmeguid, University of Illinois at Urbana Champaign, Urbana, IL, United States and Md Shumon Mia, University of Illinois at Urbana Champaign, Urbana, United States
Real Time High Fidelity Bayesian Inference and Forecasting of Tsunamis (Invited) (1990725)
Omar Ghattas1, Stefan Henneking1, Sreeram Venkat1 and Alice-Agnes Gabriel2, (1)University of Texas at Austin, Oden Institute for Computational Engineering and Sciences, Austin, United States, (2)Scripps Institution of Oceanography, University of California San Diego, Institute of Geophysics and Planetary Physics, La Jolla, United States
