H54C:
Hydrologic Data Assimilation and Analysis Tools for Large Data Sets and Their Application in Hydrology II

Submit an Abstract to this Session



Session ID#: 34499

Session Description:
Applications and developments of hydrologic and land data assimilation (DA) studies are reported. Focus of contributions include: advances in methods to estimate/reproduce errors; integrating observations across diverse spatial and temporal scales; applications of DA systems on land/atmospheric/water and state/flux/parameter estimation; and implications in decision support systems. We encourage contributions related to hydrology missions and ground sensor networks as well as simultaneous use of multiple observation types (e.g., multi-satellite, multi-scale, conjunctive use of ground, airborne and satellite observations). Studies using collaborative field experiments that collect extensive datasets will also be reported along with the development of effective analysis tools. Examples of tools include novel data sampling and statistical methods, data fusion techniques, data mining approaches, and visualization schemes for large datasets. Potential applications of these tools include modeling evapotranspiration and other earth system processes, assessing flood and drought risk, characterizing the spatial variability of precipitation, and water resources management.
Primary Convener:  Barton A Forman, University of Maryland College Park, College Park, MD, United States
Conveners:  Joseph G Alfieri, USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory, Beltsville, MD, United States, Manuela Girotto, University of California Berkeley, Department of Environmental Science, Policy, and Management, Berkeley, CA, United States and Valentijn R N Pauwels, Monash University, Melbourne, Australia
Chairs:  Joseph G Alfieri, USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory, Beltsville, MD, United States, Barton A Forman, University of Maryland, College Park, MD, United States, Manuela Girotto, Universities Space Research Association, Columbia, MD, United States and Valentijn R N Pauwels, Monash University, Melbourne, Australia
OSPA Liaison:  Barton A Forman, University of Maryland, College Park, MD, United States

Cross-Listed:
  • A - Atmospheric Sciences
  • B - Biogeosciences
  • C - Cryosphere
  • EP - Earth and Planetary Surface Processes
Index Terms:

1805 Computational hydrology [HYDROLOGY]
1847 Modeling [HYDROLOGY]
1855 Remote sensing [HYDROLOGY]
1910 Data assimilation, integration and fusion [INFORMATICS]

Abstracts Submitted to this Session:

A 3-step framework for understanding the added value of surface soil moisture measurements for large-scale runoff prediction via data assimilation - a synthetic study in the Arkansas-Red River basin (217241)
Yixin Mao, University of Washington Seattle Campus, Seattle, WA, United States, Wade T Crow, USDA ARS, Hydrology and Remote Sensing Lab, Beltsville, MD, United States and Bart Nijssen, University of Washington Seattle Campus, Civil and Environmental Engineering, Seattle, WA, United States
Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates (Invited) (214350)
Hans Lievens1, Rolf H Reichle2, Qing Liu3, Gabrielle J.M. De Lannoy2, R. Scott Dunbar4, Seungbum Kim5, Narendra N Das6, Michael H Cosh7, Jeffrey P Walker8 and Wolfgang Wagner9, (1)Ghent University, Hydro-Climate Extremes Lab (H-CEL), Gent, Belgium, (2)NASA Goddard Space Flight Center, Greenbelt, United States, (3)NASA GSFC/SSAI Inc., Greenbelt, United States, (4)Jet Propulsion Laboratory, Pasadena, CA, United States, (5)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, (6)NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (7)U.S. Department of Agriculture ARS, Hydrology and Remote Sensing Laboratory, Beltsville, United States, (8)Monash University, Department of Civil Engineering, Clayton, VIC, Australia, (9)Vienna University of Technolog, Vienna, Austria
Mapping surface heat fluxes by assimilating GOES land surface temperature and SMAP products (231276)
Yang Lyu1, Susan C Steele-Dunne2 and Nick Van De Giesen2, (1)Delft University of Technology, Delft, Netherlands, (2)Delft University of Technology, Faculty of Civil Engineering and Geosciences, Delft, Netherlands
Integrated Data Assimilation For The Coupled Atmosphere-Land Surface-Subsurface Model TerrSysMP (237700)
Harrie-Jan Hendricks Franssen1, Wolfgang Kurtz2, Hongjuan Zhang2, Sebastian Gebler2, Dorina Baatz2, Stefan J Kollet3 and Harry Vereecken4, (1)Agrosphere Institute (IBG-3), Forschungszentrum Jülich, Jülich, Germany, (2)Agrosphere Institute (IBG-3), Forschungszentrum Jülich, Julich, Germany, (3)Forschungszentrum Jülich GmbH, Agrosphere Institute (IBG-3), Juelich, Germany, (4)Forschungszentrum Jülich, Institute of Bio and Geosciences (Agrosphere, IBG-3), Jülich, Germany
Multisource data assimilation in a Richards equation-based integrated hydrological model: a real-world application to an experimental hillslope (270844)
Matteo Camporese, University of Padova, Department of Civil, Environmental and Architectural Engineering, Padova, Italy and Anna Botto, University of Padova, Padova, Italy
Catchment Tomography – Joint Estimation of Surface Roughness and Hydraulic Conductivity with the EnKF (250407)
Dorina Baatz1, Wolfgang Kurtz1, Harrie-Jan Hendricks Franssen2, Harry Vereecken3 and Stefan J Kollet4, (1)Agrosphere Institute (IBG-3), Forschungszentrum Jülich, Julich, Germany, (2)Agrosphere Institute (IBG-3), Forschungszentrum Jülich, Jülich, Germany, (3)Agrosphere (IBG-3), Institute of Bio- and Geosciences, Forschungszentrum Jülich, Juelich, Germany, (4)Forschungszentrum Jülich GmbH, Agrosphere Institute (IBG-3), Juelich, Germany

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