Presentation Information
[Poster 1-19]Challenges in developing observation-informed, high-resolution coastal digital twins: A model case in Ofunato Bay, Japan
*Helen Stewart1 (1. Space Environment and Energy Laboratories, NTT, Inc. (Japan))
Japan’s numerous coastal bays and inlets support fisheries, aquaculture, tourism, and coastal infrastructure that are central to regional economies. However, these environments are undergoing rapid change as ocean warming and shifts in regional circulation alter marine ecosystems and the distribution and productivity of fisheries resources [1]. Coastal digital twins could support adaptation by combining localized observations with satellite products, regional ocean datasets, and high-resolution numerical ocean models into integrated, predictive tools for environmental management. However, fragmented datasets, limited real-time data coverage, uncertain boundary conditions, and the need to represent interacting physical, biogeochemical, and ecological processes across scales remain major obstacles to implementing coastal digital twins [2].
Our group aims to develop coastal digital twins by combining observation-derived datasets with high-resolution ocean simulations. As an initial test case, we focus on Ofunato Bay, located in northeastern Japan. The bay has accumulated observational datasets, including multi-decadal hydrographic monitoring, current measurements, nutrient and chlorophyll records, and spatially resolved metagenomic surveys [3–5]. These datasets provide a basis for examining long-term changes in the bay’s physical environment and ecosystems, which support oyster and scallop aquaculture. Ofunato Bay is influenced by interacting river discharge, seasonal stratification and engineered exchange through its narrow entrance [4–5], making it a complex test environment for coupled physical and ecosystem modelling. We discuss approaches for integrating these observations with numerical simulations and identify the remaining barriers to developing functional, observation-informed coastal digital twins.
References
[1] Fisheries Agency (2025). “FY2024 White Paper on Fisheries: Summary”. MAFF, Government of Japan.
[2] Tzachor, A. et al. npj Ocean Sustainability 2.1 (2023): 16. doi: 10.1038/s44183-023-00023-9
[3] Kakehi, S. (2017). Fisheries Oceanography, 26(2), 114–127. doi: 10.1111/fog.12184.
[4]Yamada, Y. et al (2017). Journal of Oceanography, 73, 11–24. doi: 10.1007/s10872-015-0336-y.
[5] Reza, M. S. et al. (2018). Gene, 665, 185–191. doi: 10.1016/j.gene.2018.04.074.
Our group aims to develop coastal digital twins by combining observation-derived datasets with high-resolution ocean simulations. As an initial test case, we focus on Ofunato Bay, located in northeastern Japan. The bay has accumulated observational datasets, including multi-decadal hydrographic monitoring, current measurements, nutrient and chlorophyll records, and spatially resolved metagenomic surveys [3–5]. These datasets provide a basis for examining long-term changes in the bay’s physical environment and ecosystems, which support oyster and scallop aquaculture. Ofunato Bay is influenced by interacting river discharge, seasonal stratification and engineered exchange through its narrow entrance [4–5], making it a complex test environment for coupled physical and ecosystem modelling. We discuss approaches for integrating these observations with numerical simulations and identify the remaining barriers to developing functional, observation-informed coastal digital twins.
References
[1] Fisheries Agency (2025). “FY2024 White Paper on Fisheries: Summary”. MAFF, Government of Japan.
[2] Tzachor, A. et al. npj Ocean Sustainability 2.1 (2023): 16. doi: 10.1038/s44183-023-00023-9
[3] Kakehi, S. (2017). Fisheries Oceanography, 26(2), 114–127. doi: 10.1111/fog.12184.
[4]Yamada, Y. et al (2017). Journal of Oceanography, 73, 11–24. doi: 10.1007/s10872-015-0336-y.
[5] Reza, M. S. et al. (2018). Gene, 665, 185–191. doi: 10.1016/j.gene.2018.04.074.
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