© 2022 California Institute of Technology. Government sponsorship acknowledged. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsements by the United States Government or the Jet Propulsion Laboratory, California Institute of Technology. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Federated Digital Twins for Flood Prediction and Analysis NASA AIST IDEAS: Thomas Huang1, Cedric David1, Gary Doran1, Jason Kang1, Grace Llewellyn1, Kevin Marlis1, Miles Milosevich (intern)1, Stepheny Perez1, Wai (William) Phyo1, Joe T. Roberts1, Catalina M. Oaida Taglialatela1 | Sujay V. Kumar2, Nishan Biswas2 | Paul Stackhouse3, David Borges3, Madison P. Broddle3, Bradley MacPhserson3 SCO FloodDAM DT: Raquel Rodriguez Suquet4, Simon Baillarin4, Frederic Bretar4,5, Gwendoline Blanchet4, Peter Kettig4 | Sophie Ricci6, Andrea Piacentini6, Thanh-Huy Nguyen6 | Guillaume Valladeau7, Jean-Christophe Poisson7 | Alice Froidevaux8, Antoine Guiot8, Romane Raynal8, Huynh Thanh-long8, Christophe Fatras9, Sylvain Brunato9, Eric Guzzonato9 [1] NASA Jet Propulsion Laboratory, Caltech Institute of Technology; [2] NASA Goddard Space Flight Center; [3] NASA Langley Research Center; [4] Centre National d’Etudes Spatiales; [5] Space Climate Observatory; [6] CECI, CERFACS/UMR5318-CNRS; [7] Vortex.IO; [8] QuantCube; [9] Collecte Localization Satellites Abstract Water resource science is multidisciplinary in nature, and it not only assesses the impact from our changing climate using measurements and modeling, but it also offers science-guided, data-driven decision support. An Earth System Digital Twin (ESDT) is a dynamic, interactive, digital replica of the state and temporal evolution of Earth systems. It integrates multiple models along with observational data, and connects them with analysis, AI, and visualization tools. Together, these enable users to explore the current state of the Earth system, predict future conditions, and run hypothetical scenarios to understand how the system would evolve under various assumptions. NASA’s Advanced Information Systems Technology (AIST) Integrated Digital Earth Analysis System (IDEAS) project partners together with the France’s Science for Climate Observatory (SCO) FloodDAM Digital Twin effort is to establish an extensible architectural solution to develop digital twins of our physical environment for Earth Science. The joint effort delivers a formal system architecture with mechanisms for the outputs of one model to feed into others; for driving models with observation data; and for harmonizing observation data and model outputs for analysis. The work presents a multi-agency joint effort to deﬁne and develop digital twin for Earth system that includes continuous integration and harmonization of the latest measurements, assimilates model simulations, AI-driven scenario-based actionable predictions, and dynamic integration of the most recent, relevant observations, here with an initial focus on water resources and ﬂood analysis case studies for proof of concept. Automate Access to Many Repositories and Services Acquire Observation and Analysis Decision Support and Science Planning Forecast and Prediction Assimilation and Numerical Models AI-based Analysis Harmonize Observation and Model Data Access and Analysis FloodDAM FloodDAM NASA Advanced Information Systems Technology IDEAS: Integrated Digital Earth Analysis System got ideas? Data-Driven Community-Driven Professional Open-Source Analysis-Driven New Observing Strategies Analytic Collaborative Frameworks Latest Observations Numerical Models Actionable Predictions Federated Architecture Multi-Agency Multi-Center Multi-Computing On-demand Product Generation Clearance: CL#23-3441 Mississippi River 2019-03 - 2019-08 Garonne River 2022–01-01 - 2022-01-31 Observations & Analysis Apache