H51O:
Computational Methods and Tools for Model–Data Integration Posters


Submit an Abstract to this Session


Session ID#: 49001

Session Description:
The widening accessibility of computational resources and expanding volumes of Earth science data are fueling the rise in data-driven research and discovery in Earth system science. A growing number of open source tools are being developed and used for model–data fusion, data assimilation, visualization and visual analytics, model benchmarking, and multi-model ensemble prediction experiments. Such Earth science models and supporting languages, tools, and analytics software are being deployed on large workstations, clusters, dynamically provisioned cloud services, and supercomputers. This session highlights innovative computational methods, open source software tools and related cyberinfrastructure for model-data integration and their application to address research challenges in hydrology and biogeosciences. Examples might include methodology development for model-data integration (e.g., data assimilation, uncertainty quantification, and model-informed experimental design), application of machine learning methods, assimilation of remote sensing data, language features, data management standards, user interface and visualization capabilities, and novel use cases for Open Science applications.
Primary Convener:  Dr. Forrest M Hoffman, PhD, Oak Ridge National Laboratory, Oak Ridge, TN, United States
Conveners:  Xingyuan Chen, Pacific Northwest National Laboratory, Richland, United States, Tianfang Xu, Arizona State University, School of Sustainable Engineering and the Built Environment, Tempe, United States and Hyungjun Kim, University of Tokyo, Bunkyo-ku, Japan
Primary Liaison:  Dr. Forrest M Hoffman, PhD, Oak Ridge National Laboratory, Oak Ridge, TN, United States
Chairs:  Dr. Forrest M Hoffman, PhD, Oak Ridge National Laboratory, Computational Sciences & Engineering Division, Oak Ridge, United States, Xingyuan Chen, Pacific Northwest National Laboratory, Richland, United States, Tianfang Xu, UIUC-Civil Engineering, Urbana, United States and Hyungjun Kim, University of Tokyo, Bunkyo-ku, Japan
OSPA Liaison:  Xingyuan Chen, Pacific Northwest National Laboratory, Richland, United States
Co-Organized with:
Hydrology, and Biogeosciences

Proposed Co-Organized Session with:
  • B - Biogeosciences
Index Terms:

0430 Computational methods and data processing [BIOGEOSCIENCES]
0466 Modeling [BIOGEOSCIENCES]
1849 Numerical approximations and analysis [HYDROLOGY]
1873 Uncertainty assessment [HYDROLOGY]

Abstracts Submitted to this Session:

Hybrid Modeling for Streamflow Prediction in the Guadalupe Basin, Texas (421242)
Maysara Ghaith, McMaster University, Department of Civil Engineering, Hamilton, ON, Canada and Zhong Li, University of Regina, Regina, SK, Canada
Bayesian model selection under computational time constraints: application to river modeling (449318)
Anneli Guthke1, Sergey Oladyshkin1, Farid Mohammadi2, Rebekka Kopmann3 and Wolfgang Nowak1, (1)University of Stuttgart, Stochastic Simulation and Safety Research for Hydrosystems (IWS/SC SimTech), Stuttgart, Germany, (2)University of Stuttgart, Department of Hydromechanics and Modelling of Hydrosystems (IWS), Stuttgart, Germany, (3)Federal Waterways Engineering and Research Institute (BAW), Karlsruhe, Germany
Computational Geophysical Approach to the Stochastic Inversion Modelling of Intracellular Copper Transport Kinetics and Steady-State Isotopic Fractionation within Saccharomyces Cerevisiae (420663)
Aaron Francis Wilkins, University of Calgary, Calgary, AB, Canada, Brandon Karchewski, University of Calgary, Department of Geoscience, Calgary, AB, Canada, Michael Wieser, University of Calgary, Physics and Astronomy, Calgary, AB, Canada and Vanina Zaremberg, University of Calgary, Biological Sciences, Calgary, AB, Canada
Coupling Iterative Ensemble Smoother and Multiple-Point Geostatistics for Dynamic Data Assimilation (356631)
Zhendan Cao and Liangping Li, South Dakota School of Mines and Technology, Rapid City, SD, United States
Development of ILS, Integrated Land Simulator (457135)
Tomoko Nitta1, Takashi Arakawa2, Akira Takeshima3, Misako Hatono4, Hisashi Yashiro5, Dai Yamazaki6 and Kei Yoshimura1, (1)The University of Tokyo, Institute of Industrial Science, Kashiwa, Japan, (2)Research Organization for Information Science and Technology, Shinagawa-ku, Japan, (3)The University of Tokyo, Bunkyo-ku, Japan, (4)Tohoku University, Sendai, Japan, (5)RIKEN Center for Computational Science, Kobe, Japan, (6)University of Tokyo, Institute of Industrial Science, Tokyo, Japan
Efficient Automatic Parameter analysis framework for Computationally Expensive Hydrodynamic models (464077)
Wei Xia1, Taimoor Akhtar1, Christine A Shoemaker1 and Manh Tuan Nguyen2, (1)National University of Singapore, Singapore, Singapore, (2)Public Utilities Board, Singapore, Singapore
Estimation of forest evapotranspiration in Korea – comparison machine learning and process-based approaches (436043)
Juhan Park, National Center for AgroMeteorology, Seoul, South Korea, Minseok Kang, Gangneung-Wonju National University, Department of Atmospheric and Environmental Sciences, Seoul, South Korea, Sungsik Cho, Seoul National University, Seoul, Korea, Republic of (South), Seung-Jae Lee, National Center for AgroMeteorology, Seoul National University, Seoul, South Korea, JungHwa Chun, National Institute of Forest Science, Seoul, South Korea, Joon Kim, Seoul National University, Department of Landscape Architecture & Rural Systems Engineering, Future Earth Program in Asia Center, Interdisciplinary Program in Agricultural and Forest Meteorology, Institute of Green Bio Science and Technology, Seoul, South Korea and Hyun Seok Kim, Seoul National University, Department of Forest Sciences, Seoul, South Korea
Harnessing the Power of Open Data and Analytics for Characterizing the Role of Hydrological Processes in the Spread of a Vector-borne Livestock Disease in Multiple Watersheds across the Western US (416327)
Heather Savoy, Jornada Basin Long Term Ecological Research Program, New Mexico State University, Las Cruces, NM, United States, Debra P C Peters, USDA-ARS, Las Cruces, NM, United States, Emile Elias, New Mexico State Univ, Las Cruces, United States, Angela M. Pelzel-McCluskey, USDA APHIS, Fort Collins, CO, United States, Luis Rodriguez, Florida State University, Earth, Ocean and Atmospheric Sciences, Tallahassee, United States, Justin D Derner, USDA ARS, Cheyenne, WY, United States and D. Scott McVey, USDA ARS, Manhattan, KS, United States
Hierarchical Bayesian Network: Application to Casual Inference in Photosynthesis Studies (449995)
Yi Xiao1,2, Xingyuan Chen3 and Xin-Guang Zhu1, (1)Institute of Plant Physiology & Ecology, SIBS, CAS, Shanghai, China, (2)Pacific Northwest National Laboratory, Richland, WA, United States, (3)Pacific Northwest National Laboratory, Richland, United States
A new approach to parameter estimation and modelling of isotopic effects during degradation and transport of groundwater contaminants (432413)
Landon J. S. Halloran1, Philip Brunner2 and Daniel Hunkeler2, (1)University of Neuchâtel, Neuchâtel, Switzerland, (2)University of Neuchâtel, Centre for Hydrogeology and Geothermics, Neuchâtel, Switzerland
Promoting advances in hydrological modeling through development of the open-source water quality modelling system RSPARROW (436268)
Lillian Gorman-Sanisaca, United States Geological Survey (USGS), Baltimore, MD, United States and Richard B Alexander, United States Geological Survey (USGS), Reston, VA, United States
Propagator networks and truth maintenance systems: blending physical constraints and data to understand land-atmosphere interaction in the pre-satellite and pre-FLUXNET era. (460717)
Adam Massmann, Columbia University of New York, Earth and Environmental Engineering, New York, NY, United States, Pierre Gentine, Columbia University, Department of Earth and Environmental Engineering, New York, United States and Martin Wild Sr, ETH Swiss Federal Institute of Technology Zurich, Institute for Atmospheric and Climate Science, Zurich, Switzerland
Sequential data-worth analysis coupled with ensemble Kalman filter for soilwater flow: A real-world case study (353901)
Yakun Wang, Wuhan, China
Surrogate-Based Bayesian Inverse Modeling of the Hydrological System: An Adaptive Approach Considering Surrogate Structural Error (349758)
Jiangjiang Zhang, Zhejiang University, Hangzhou, China, Laosheng Wu, University of California, Department of Environmental Sciences, Riverside, CA, United States and Lingzao Zeng, Zhejiang University, College of Environmental and Resource Sciences, Hangzhou, China
Watershed modelling framework, a programable tool for hydrologic simulation and analysis (467285)
Jaime Velez, Universidad Nacional de Colombia, Medellin, Geosciences, Medellin, Colombia, Dr. Nicolas Velasquez, University of Iowa, Iowa City, IA, United States and Carlos David Hoyos Ortiz, Sistema de Alerta Temprana del Valle de Aburra (SIATA);Universidad Nacional de Colombia, Sede Medellín, Departamento de Geociencias y Medio Ambiente/Geoscience and Environment Department, Medellín, Colombia; Universidad Nacional de Colombia, Sede Medellín, Departamento de Geociencias y Medio Ambiente / Geoscience and Environment Department, Medellín, Colombia

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